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3D Locomotion Biomimetic Robot Fish with Haptic Feedback

by

Zhenying Guan (B. Eng)

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

Deakin University

July, 2012

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Acknowledgments The work in this thesis is a culmination of my efforts strongly

backed by the support of many people to whom I am deeply grateful.

I owe a great deal to my supervisor, Prof. Saeid Nahavandi for

guiding and training me through my entire tenure as a student at the

Centre for Intelligent Systems Research, Deakin University. I also

appreciate my associate supervisor, Weimin Gao, who gave me

elaborative direction on my robot fish research project, especially on

the Computational Fluid Dynamics (CFD) simulation of the robot fish.

I deeply admire my advisors’ patience in putting up with my research

inexperience and helping me understand the technical concepts

involved in my work.

I would like to thank the students and staff at the Institute for

Technology Research and Innovation, Deakin University, for providing

me with all the technical, administrative and emotional support that I

asked for.

I am deeply grateful to my husband and parents for providing me

with the moral support to complete postgraduate studies. Without their

encouragement and love I would not have been able to finish my PhD

study with so many achievements.

I would like to thank everyone who helped to make this possible.

It has been an incredible journey of self-discovery, and I love every

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last one of you.

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Abstract Underwater exploration is becoming the focus of many scientific

research projects. The superior swimming ability of fish, and the great

tactile ability of human beings bring an idea of developing haptic robot

fish systems, which would help expand human competence to discover

the mystery of the underwater world. The primary goal of this thesis is

to develop a biomimetic robot fish and to build a novel haptic robot

fish system based on the kinematic modeling and CFD hydrodynamic

analysis of the robot fish.

The biomimetic robot fish was built based on the prototype of a

carangiform fish, which has a good balance of velocity, acceleration

and controllable properties. This robot fish cannot only get abundant

information, especially visually, but also transfer the massive amount

of information to the upper console by an information relay system

floating on water. An innovative biomimetic motion library was also

established to help users make the control scheme more efficient.

A haptic robot fish system was innovated with a new interactive

force feedback, which comes from two kinds of simulation results, the

kinematic modeling (using Lagrangian method) and CFD

hydrodynamic analysis (simulated by Fluent® 6.3.26). It supports

users in understanding the hydrodynamic properties around the robot

fish more deeply than in other common visualization systems based

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only on graphical visualization of hydrodynamic analysis. One can feel

the force imposed on the robot fish in water and also can observe the

field distribution maps, such as velocity and pressure on need for

hydrodynamic analysis.

The most important contribution of this thesis is the successful

three-dimensional (3D) computational fluid dynamic simulation of the

biomimetic robot fish by Fluent® 6.3.26, where User-Defined Function

(UDF) was used to define the movement of the robot fish; Dynamic

Mesh was used to mimic the fish swimming in water. Hydrodynamic

analysis has been done to get comparative data about the

hydrodynamic properties of those guidelines and to improve the design,

remote control and flexibility of the underwater robot fish.

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Vita Publications arising from this thesis include:

Z. Guan, C. Zhou, Z. Cao, N. Gu, M. Tan and S. Nahavandi, “A 3-D

locomotion biomimetic robot fish with information relay”,

Lecture Notes in Computer Science, Springer Berlin / Heidelberg,

Vol. 5314/2008, pp 1135-1144

Z. Guan, W. Gao, N. Gu and S. Nahavandi, "3D Hydrodynamic

Analysis of Biomimetic Robot Fish", 11th International

Conference on Control, Automation, Robotics and Vision

(ICARCV), Singapore, Dec. 2010, pp 793 – 798

"3D Dynamic Computational Fluid Dynamics (CFD) modeling and

Hydrodynamic Analysis of Biomimetic Robot Fish" is going for

the journal of Robotica. This paper will probe deeply into the

hydrodynamic properties of the robot fish, and the mathematic

method of describing the robot fish tail movements will be

improved.

"A Novel Robot Fish System with Haptic Interaction" is going for

Journal of Field Robotics. This paper will demonstrate the novel

haptic robot fish system design. Force sensors are going to be

applied to measure force in real-time; this will help the robot fish

perceive the fluent force around it and make instantaneous

swimming strategies to avoid vortexes or to save energy by

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complying with currents liking similar to real fish movements.

The haptic interactions will be set up according to these force

measurements as well. For example, the users can feel the force

on the robot fish and send control commands to the robot fish via

a PHANTOM Omni Haptic Device.

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Contents Acknowledgments.......................................................................................................... 1

Abstract .......................................................................................................................... 3

Vita ................................................................................................................................. 5

Contents ......................................................................................................................... 7

Figure List .................................................................................................................... 10

Table List ..................................................................................................................... 12

Abbreviations: .............................................................................................................. 13

1. Introduction ............................................................................................................. 15

1.1. Motivation ................................................................................................... 15

1.2. Goal and Methods ....................................................................................... 17

1.3. Outline of the Thesis ................................................................................... 19

1.4. Contributions ............................................................................................... 20

2. Literature Review .................................................................................................... 23

2.1. Background to Underwater Robot and Haptic Development ...................... 23

2.1.1. Underwater Robot Development ......................................................... 23 2.1.1.1. Background of Autonomous Underwater Vehicle ................... 24

2.1.1.2. Development of Remotely Operated Underwater Vehicles ..... 26

2.1.1.3. Hybrid Remotely Operated Underwater Vehicle ..................... 29

2.1.1.4. Shortcomings of Remotely Operated Underwater Vehicles and Autonomous Underwater Vehicles........................................... 30

2.1.2. Biomimetic Robot Fish Design ........................................................... 31 2.1.3. Haptics and Application ...................................................................... 35

2.2. Fish Propulsion Theory ............................................................................... 42

2.3. Research into Underwater Biomimetic Robots ........................................... 47

2.4. Kinematics and Locomotion Control of robot fishes .................................. 49

2.5. Hydrodynamic Analysis of Underwater Robot ........................................... 55

2.6. Haptics for Underwater Applications .......................................................... 57

2.7. Summary ..................................................................................................... 59

3. Design of a Biomimetic Robot Fish ........................................................................ 61

3.1. Problem Formulation ................................................................................... 61

3.2. The Biomimetic Robot Fish ........................................................................ 62

3.3. Mechanical Structure ................................................................................... 65

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3.3.1. Support Frame ..................................................................................... 65 3.3.2. Actuation Unit ..................................................................................... 69 3.3.3. Communication Unit ........................................................................... 71 3.3.4. Control and Sensing Units and Accessories ........................................ 71

3.4. Control system ............................................................................................. 73

3.5. Biomimetic motion library .......................................................................... 74

3.5.1. Realisation of Propulsion..................................................................... 76 3.5.2. Swimming Direction Control .............................................................. 77 3.5.3. Diving Control ..................................................................................... 79

3.6. Prototype of the Robot Fish ......................................................................... 80

3.7. Conclusions ................................................................................................. 81

4. Kinematic Modeling of Biomimetic Underwater Robot Locomotion .................... 82

4.1. Introduction ................................................................................................. 82

4.2. Problem Formulation ................................................................................... 83

4.3. Outline of the Lagrangian Method .............................................................. 84

4.4. Kinematic Modeling of the Robot fish ........................................................ 87

4.4.1. Geometry Simplification of the Robot Fish ........................................ 87 4.4.2. The Lagrangean Equation of the Robot Fish ....................................... 90

4.5. Fluid Modeling the Robot Fish ................................................................... 93

4.6. Kinematic Modeling Results ....................................................................... 95

4.7. Conclusion ................................................................................................... 97

5. Hydrodynamic Analysis of the Biomimetic Robot Fish & Application on the Haptic Robot Fish System ....................................................................................... 99

5.1. Introduction ................................................................................................. 99

5.2. Problem formulation .................................................................................. 100

5.3. 3D Hydrodynamic Model .......................................................................... 100

5.3.1. Biomimetic Robot Fish and Pool Geometries ................................... 100 5.3.2. Mesh Scheme ..................................................................................... 101

5.3.2.1. Requirements and Conditions of Mesh Scheme ..................... 101

5.3.2.2. Logical Division of Fluid Domain ......................................... 102

5.3.2.3. Mesh Scheme Specific Implementation ................................. 103

5.3.3. Mathematic Description of the Robot Fish Locomotion ................... 104 5.3.3.1. Conditions of 3D Mathematic Description............................. 105

5.3.3.2. Robot Fish Tail Waving Description ...................................... 107

5.3.3.3. Implement of the Robot Fish Tail Movement with Fluent® ... 108

5.4. Hydrodynamic Analysis ............................................................................ 110

5.4.1. Design Properties of the Robot Fish .................................................. 110

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5.4.2. Pressure Distribution around the Swimming Robot Fish .................. 113 5.4.3. Velocity Distribution around the Swimming Robot Fish .................. 116 5.4.4. Forces of the Swimming Robot Fish ................................................. 118

5.5. Haptic Application on the Robot Fish ....................................................... 119

5.5.1. Issues to Be Solved ............................................................................ 120 5.5.2. Haptic Robot Fish System Framework .............................................. 121 5.5.3. 3D Virtual Display Design ................................................................ 124 5.5.4. Haptic Robot Fish System Force Feedback Method ......................... 125

5.5.4.1. Preset Database Based on Computational Fluid Dynamics (CFD) Simulation Results .................................................................. 126

5.5.4.2. Possibility of Real-time Calculation Based on Kinematic Modeling ................................................................................ 126

5.5.4.3. Further Haptic Robot Fish System Design ............................. 127

5.6. Underwater Experiments ........................................................................... 127

5.7. Conclusion ................................................................................................. 129

6. Analysis and Discussion on Kinematic Modeling and Computational Fluid Dynamics (CFD) Hydrodynamic Simulation ........................................................ 131

6.1. Introduction ............................................................................................... 131

6.2. Distinguishing Features of Kinematic Modeling ...................................... 131

6.3. Distinguishing Feature of Computational Fluid Dynamics (CFD) Analysis ..................................................................................................... 132

6.4. Comparison between Kinematic Modeling and Computational Fluid Dynamics (CFD) Hydrodynamic Analysis ............................................... 133

6.5. Conclusion ................................................................................................. 136

7. Conclusions and Future Works ............................................................................. 138

7.1. Conclusions ............................................................................................... 138

7.2. Future Works ............................................................................................. 140

References .................................................................................................................. 143

Appendix (published papers) ..................................................................................... 162

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Figure List Chapter 2 Figure 2:1: First Torpedo, 1866 [3] ............................................................................. 24 Figure 2:2: Cutlet, Rov, 1950s [13] ............................................................................. 27 Figure 2:3: Nereus Can Switch Between Free-Swimming And Tethered

Configurations, 2007 [15] ............................................................................... 30 Figure 2:4: Robotuna, Mit [21] Figure 2:5: Robopike, Mit [22] .................... 32 Figure 2:6: Northeastern University’s Undulatory Underwater Robot [26] ................ 34 Figure 2:7: Underwater Robot Experiment Platform, The Harbin Institute Of

Technology [40] ................................................................................................. 34 Figure 2:8: Biomimetic Dolphin, Peking University [41] ........................................... 34 Figure 2:9: Two Robot Fish Playing Ball, Institute Of Automation Chinese Academy

Of Sciences [42] ................................................................................................. 34 Figure 2:10: Professor Massimo Bergamasco Of The Scuola Superiore Di Studi

Universitari In Pisa, Italy, Demonstrating The Results Of His Early Exoskeletal System, Funded By The European Commission As Part Of An Esprit Ii Project Known As Glad-In-Art (Glove-Like Advanced Devices In Artificial Reality) [45] ..................................................................................................................... 39

Figure 2:11: The Teletact Ii Pneumatic Tactile Feedback Glove Developed By The Uk’s National Advanced Robotics Research Centre And Airmuscle Limited, Showing An Early Palmar Feedback Concept [45] ........................................... 40

Figure 2:12: The Surgical Procedures Definition And Task Analyses Conducted By The Ent Department Of Manchester’s Royal Infirmary [45] ............................. 41

Figure 2:13: Four Fish Swimming Propulsive Models [54] ........................................ 44 Figure 2:14: A: Distributed Autonomous Swimming Robot (3 Agents); .................... 52 Figure 2:15: Princeton 3d Multi-Vehicle Experimental Test-Bed (Left); ................... 53 Figure 2:16: Photograph And Schematic Of Side View Of Fish Design (Left); ......... 54 Chapter 3 Figure 3:1: Biomimetic Robot Fish System................................................................. 64 Figure 3:2: The Head Of The Biomimetic Robot Fish ................................................ 66 Figure 3:3: Internal Connection ................................................................................... 67 Figure 3:4: External Connection. The Left One Is Used For The Connection Of The

First 3 Links; The Right One Is Used For Connecting The Last Link And Caudal Fin. ......................................................................................................... 68

Figure 3:5: Support Board ........................................................................................... 68 Figure 3:6: Caudal Vertebra ......................................................................................... 69 Figure 3:7: Sanwa Servo Rs-995 [112] ........................................................................ 70 Figure 3:8: The Block Diagram Of The Control System ............................................. 73 Figure 3:9: Links Fitting Fish’s Body-Wave ............................................................... 76 Figure 3:10: The Corrected Fish Body Wave Curve ................................................... 78 Figure 3:11: The Moment Analysis Of Barycenter-Adjustor ...................................... 79 Figure 3:12: The Functional Prototype Of The Biomimetic Robot Fish ..................... 80

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Chapter 4 Figure 4:1: Robot Fish Joint-Link Structure ................................................................ 88 Figure 4:2: Simplified Coordinates Of The Robot Rish And Its Parameters Definition

............................................................................................................................ 89 Figure 4:3: The Five Links Robot Fish And Some Parameters Definition .................. 90 Figure 4:4: Simulation Results Of Forces Acting On The Robot Fish In Forward

Motion ................................................................................................................ 97 Chapter 5 Figure 5:1: Mesh Of The Biomimetic Robot Fish ..................................................... 104 Figure 5:2: Mesh Scheme For The Region Close To Robot Fish .............................. 104 Figure 5:3: The Outline Of The Robot Fish ............................................................... 105 Figure 5:4: Parameters Of The Robot Fish Tail (Unit: Mm) ..................................... 106 Figure 5:5: Node Movement ...................................................................................... 107 Figure 5:6: Meshes On Robot Fish Body .................................................................. 108 Figure 5:7: M-View ................................................................................................... 110 Figure 5:8: Velocity Vectors On The Robot Fish Surface ......................................... 111 Figure 5:9: The Pathlines Of The Robot Fish ............................................................ 112 Figure 5:10: Hydrodynamic Analysis – Pressure ...................................................... 112 Figure 5:11: Pressure Contours Of The M-View At 4 Locomotion Times (N×M–2) (A)

Approaching The Left Maximal Rotation Position (T = 0.1 S); (B) Intermedial Position During Oscillating Motion (T = 0.25 S); (C) Going On Intermedial Position During Oscillating Motion (T = 0.4 S); (D) Approaching Right Maximal Rotation Position (T =0.55 S). (It Is Supposed That A Robot Fish Locomotion Period Begin From The Position T=0 According The Equation 1) .......................................................................................................................... 113

Figure 5:12: Velocity Distribution ............................................................................. 117 Figure 5:13: Forces In X And Z Directions ............................................................... 119 Figure 5:14: The Framework Of Haptic Robot Fish System ..................................... 122 Figure 5:15: Virtual Display And Haptic Operating .................................................. 123 Figure 5:16: Command In Virtual Interface .............................................................. 124 Figure 5:17: The Image Sequence Of The Robot Fish Turning ................................ 128

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Table List Chapter 5 Table 5.1: Parameters For Dynamic Mesh ................................................................ 109 Table 5.2: Oscillating Frequency (Hz) Versus Speed (M/S) Of Straight Swimming 128

Chapter 6 Table 6.1: Comparison Between The Kinematic Modeling And Cfd Analysis ........ 134 Table 6.2: Comparison In Special Properties Between The Kinematic Modeling And

Cfd Analysis ..................................................................................................... 135

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Abbreviations:

3D: three-dimensional

ABE: Autonomous Benthic Explorer

AUSS: Advanced Unmanned Search System

AUV: Autonomous Underwater Vehicle

BCF: Body and/or Caudal Fin

CCD: charge-coupled device

CFD: Computational Fluid Dynamics

CMOS: Complementary Metal Oxide Semiconductor

CURV: Cable-Controlled Underwater Recovery Vehicle

DPIV: Digital Particle Image Velocimetry

EPFL: The Swiss Federal Institute of Technology Lausanne

FRP: Fiberglass-Reinforced Plastics

GLAD-IN-ART: Glove-like Advanced Devices in Artificial

Reality

IERAPSI: Integrated Environment for Rehearsal and Planning of

Surgical Interventions

MCU: Micro Control Unit

MIPS: Million Instructions Per Second

MIT: The Massachusetts Institute of Technology

MPF: Median and/or Paired Fin

MSMs: Master-Slave Manipulators

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NMRI: National Maritime Research Institute

NSF: National Science Foundation

REMUS: Remote Environmental Measuring UnitS

POD: Proper Orthogonal Decomposition

RISC: Reduced Instruction Set Computing

ROV: Remotely Operated Underwater Vehicle

SPURV: Self Propelled Underwater Research Vehicles

UDF: User-Defined Function (in software Fluent®)

WHOI: Woods Hole Oceanographic Institution

WRCS: the world rectangular coordinate system

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1. Introduction

1.1. Motivation

Water covers 71% surface of the Earth, totaling 1,400M cubic

kilometers in volume[1]. Biotic and mineral resources in oceans and on

the bottom of seas are so abundant that the scientists are deeply

attracted to this area. There has been a growing interest in exploring

underwater objects in areas such as oceanographical observation,

underwater archaeological exploration, leak detection in pipelines, the

search for mines as well as toxic wastes, for environmental issues,

scientific study, commercial exploitation of the ocean and security

reasons. It is important to engage in this research area and establish key

enabling technologies to protect and exploit underwater resources more

efficiently. The need for the use of underwater robotic systems has

become more apparent. As a matter of fact, underwater robotics

represents a fast growing research area and there are promising

industry opportunities that will benefit from the developments of

advanced technologies in various subsystems and explorations of the

potential application areas such as computer technology,

microelectronic techniques, network techniques, new materials, sensors

and algorithms. Tremendous progress in robotics technology has

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unleashed new opportunities for developing underwater robots to

overcome the challenging scientific and engineering problems caused

by the unstructured and hazardous underwater environment. From the

Autonomous Underwater Vehicle (AUV) to the Remotely Operated

underwater Vehicle (ROV), and even hybrid ROVs, many kinds of

underwater robots have come into the world. But in comparison with

real fish, they are so awkward that they cannot reach and handle

complex underwater circumstances.

In nature, the great and secret biological world gives scientists

some inspirations. Biomimetic robots are the grand products of this

development; their abilities are copied from the Earth's greatest

examples of success, living organisms. They tend to function better in

the unpredictable real world than in the controlled artifice of a

laboratory. Researchers also introduce biomimetics into the design of

underwater vehicles such as biomimetic robot fishes. These have

significant advantages, for example, their silence in moving, high

energy efficiency, and great maneuverability when compared to

conventional propeller-oriented propulsive underwater mechanisms.

Biomimetic robot fish has been given a certain of properties

currently, such as 3D controllable free swimming, the automatic

avoidance of obstacles, the ability to obtain visual information,

communicate with an upper sole and network with other robot fish.

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However, to imitate all genuine fish behaviors with robotized systems

is a huge challenge, especially being able to design a kind of robot fish

with a haptic function that realizes fluent force perception and makes

real-time swimming strategies to avoid vortexes or save energy by

complying with currents. Although considerable progress has been

achieved by many researchers in both biomimetic robot fish and

haptics, the joining of both of these technologies in underwater

exploration still remains due to the impenetrable nature of the

underwater environment. Underwater robot fish with touch sensation

will bring an innovative expansion in underwater explorations, for

example, remote texture analysis and sample collection especially in

muddy water, which are hardly realized by other technologies except

haptics. This thesis would join haptics in underwater robot fish to bring

an innovation in this field.

1.2. Goal and Methods

Underwater exploration is becoming the focus of many scientific

investigations. The superior swimming ability of natural fish and the

great tactile ability of human being bring an idea of developing a kind

of haptic robot fish system, which would help expand human

competence in uncovering underwater world mysteries. Both of the

technologies of biomimetic robot fish and haptics have arisen in past

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twenty years. Researchers started to develop haptic interaction with

biomimetic robot fish, an emerging field of investigation. The primary

goal of this thesis is to develop a biomimetic robot fish, from which a

novel haptic biomimetic robot fish system will be built up.

The biomimetic robot fish was built based on the prototype of a

carangiform fish, which has a good balance of velocity, acceleration

and controllable properties. It has a barycenter-adjustor for

descending/ascending motion and multiple sensors for obtaining

environmental information from around the robot fish. It may

communicate with the outside by an information relay system on water.

Combining the movements of the tail, and the structure for descending

and ascending, the robot fish can simulate the 3D controllable free

swimming of real fish in water. This robot fish cannot only get

abundant information, especially visually, but also transfer the massive

amount of information to the upper console via wire/wireless

communication. An innovative biomimetic motion library was also

established to help users make the control scheme more efficient.

In order to make haptic biomimetic robot fish, force feedback is

quite important and currently comes from two kinds of simulation

results, the kinematic modeling (using Lagrangian method) and CFD

hydrodynamic analysis (simulated by Fluent® 6.3.26). The former is

suitable for real-time force feedback calculation and produces a good

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solution for online mechanical analysis. The latter studies the

hydrodynamic properties of the robot fish which can meet the detailed

information requirements of operators. The added tactile sensation

function makes it possible for an operator to have interaction with the

fish and for robot fish to have the ability to feel currents, an innovation

in the biomimetic robot fish field.

1.3. Outline of the Thesis

The thesis is organised into 7 chapters:

Chapter 1 is a brief introduction to the thesis project, which will

reveal the importance of setting the haptic biomimetic robot fish

system.

Chapter 2 reviews the research in underwater robotics, biomimetic

robot fish and haptics development which helps indentify the ideas in

the growth of the relative fields.

Chapter 3 introduces the biomimetic robot fish mechanics, the

hardware and software design in detail which is the basis of the haptic

biomimetic robot fish system.

Chapter 4 presents the kinematic modeling of the robot fish

locomotion and the simulation results, which is a form of simplified

modeling and can be used online to provide force feedback for the

haptic biomimetic robot fish system.

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Chapter 5 elaborates the 3D hydrodynamic analysis of the robot

fish in CFD and the modeling consequences; and describes the haptic

application on the robot fish. This is the essential part of the thesis.

Chapter 6 compares the advantages and disadvantages of the

kinematic modeling & CFD hydrodynamic analysis which will help

readers choose the right simulation method to support their studies.

Chapter 7 contains the conclusions and some outlook on possible

further research activities in the area of this thesis.

1.4. Contributions

The requirement of developing technologies of biomimetic robot

fish and the flourishing of haptics, provides an infinite possibility of

research into a new product, a haptics robot fish system, which will

gather the advantages of biomimetic robot fish and haptics together.

This thesis’ main contributions are in the following areas:

The first contribution of the thesis is that a functional biomimetic

robot fish based on the prototype of a carangiform fish was built up. It

has a biomimetic tail to simulate the carangiform tail, a

barycenter-adjustor for descending/ascending motions, multiple

sensors, and it may communicate with the outside by a wire connected

information relay system floating on the water. Combining the

movements of the tail and the structure for descending and ascending,

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the robot fish can simulate the swimming of real fish in water. An

innovative biomimetic motion library is established which helps users

make the control scheme more efficient.

The second contribution is that the kinematic modeling for the

robot fish using Mathematics® software was developed. It was built up

according to the relationship between the generalized force in

Lagrange's equation of the second kind, and the fluid force. The

modeling provides a simple and time-efficient way to calculate the

force on the swimming robot fish.

The third contribution is that the thesis represents a 3D

computational fluid dynamic simulation of the biomimetic robot fish

by Fluent® 6.3.26. The UDF is used to define the movement of the

robot fish and Dynamic Mesh is used to mimic the fish swimming in

water. Hydrodynamic analysis has been done, aimed at getting

comparative data about the hydrodynamic properties of those

guidelines to improve the design, remote control, and flexibility of the

underwater robot fish.

The last but not the least contribution of this thesis, is that a novel

haptic robot fish system is established using the data of CFD

hydrodynamic analysis and kinematic modeling as the force feedback.

Users can feel the force on the robot fish via a PHANTOM Omni

Haptic Device. The velocity, pressure field distribution and any other

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further information of the robot fish hydrodynamic properties will be

provided according the need of users.

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2. Literature Review

The aim of this chapter is to provide a systematic overview of the

robot fish development process, including fish propulsion theory,

underwater robot research status, kinematics and locomotion control of

robot fish, hydrodynamic analysis of underwater robot and haptic

development.

2.1. Background to Underwater Robot and Haptic

Development

2.1.1. Underwater Robot Development

The underwater robot research field has emerged quickly in recent

years. There are two main categories of underwater robots:

Autonomous Underwater Vehicle (AUV) and Remotely Operated

underwater Vehicle (ROV). The former is a robotic device that is

driven through the water by a propulsion system, controlled and piloted

by an onboard computer and maneuvered in three dimensions. The

latter is controlled or remotely controlled by a human operator via a

cable or wireless communication on a ship or on the ground.

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2.1.1.1. Background of Autonomous Underwater Vehicle

The history of underwater robot technology can date back to the

first torpedo (Figure 2:1) designed in 1866, which was driven by

compressed air carrying an explosive charge. A simple hydrostatic

valve acted directly on the elevator to hold the torpedo at a

pre-determined depth. If one ignores the fact that it carried an

explosive charge, it might be considered the first AUV [2].

Figure 2:1: First Torpedo, 1866 [3]

The first “true” underwater vehicle was developed in the late

1950s by Stan Murphy, Bob Francois and Terry Ewart of the Applied

Physics Laboratory at the University of Washington to help them

obtain oceanographic data along precise trajectories and under ice [4].

This work led to the development and operation of the Self Propelled

Underwater Research Vehicle (SPURV) in the early 60’s [5].

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Following the development of SPURV I, which was acoustically

controlled from the surface and could autonomously run at a constant

pressure, sea saw between two depths, or climb and dive up to 50

degrees, over 400 SPURVs were researched and developed.

In 1983 an Advanced Unmanned Search System (AUSS) [6] was

developed by SPAWAR (its predecessor was the Naval Ocean System

Center) in response to the sinking of the USS Thresher, the USS

Scorpion and the H bomb loss of Palomares. It had an acoustic

communication system that transmitted video images through the water.

This system brought about the concept of using multiple controllable

freely swimming vehicles to improve system performance.

In 1990s the underwater robot technology developed rapidly and

operated world-wide. There were some leading underwater projects:

Odyssey (1992, The Massachusetts Institute of Technology,

MIT), was operated under ice and used in support of

experiments demonstrating the Autonomous Ocean Sampling

Network [7, 8]

Autonomous Benthic Explorer (ABE, in the mid 1990’s,

Woods Hole Oceanographic Institution, WHOI) carried six

thrusters which made it a highly maneuverable vehicle in all

three dimensions. ABE is an excellent platform to perform

near bottom surveys in rough terrain [8, 9].

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Theseus (1996, International Submarines Engineering, Ltd.)

was designed for laying optical fiber cables in ice-covered

waters [10]. It operated in either depth-keeping mode or

bottom-following mode.

Remote Environmental Measuring Units—REMUS (1994,

WHOI) [11], were made up of a number of small, low cost,

controllable freely swimming vehicles operated jointly or

independently, which could offer an appropriate technology

for gathering data in the coastal and open ocean.

After 2000, more and more underwater projects are in research or

commercial use, covering a large area of exploration, wrecking,

military, and fishery. But the actions of AUVs are limited by the

onboard computer operation and AUVs are generally designed for

surveys. ROV is made for direct multipurpose interaction.

2.1.1.2. Development of Remotely Operated Underwater

Vehicles

ROVs are unoccupied, highly maneuverable and operated by a

person aboard a vessel. They are linked to a ship by a tether

(sometimes referred to as an umbilical cable), a group of cables that

carry electrical power, video and data signals back and forth between

the operator and the vehicle. High power applications often use

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hydraulics and electrical cabling. Most ROVs are equipped with at

least a video camera and lights. Additional equipment is commonly

added to expand the vehicle’s capabilities. These may include sonars,

magnetometers, a still camera, a manipulator or cutting arm, water

samplers, and instruments that measure water clarity, light penetration

and temperature.

In the 1950s the Royal Navy used "Cutlet"(Figure 2:2), which

might be the first ROV, a remotely operated submersible, to recover

practice torpedoes. The US Navy funded most early ROV technology

in the 1960s, named the " Cable-Controlled Underwater Recovery

Vehicle" (CURV) [12], to perform deep-sea rescue operations and

recover objects from the ocean floor. Building on this technology base

the offshore oil & gas industry created the work class ROVs to assist in

the development of offshore oil fields.

Figure 2:2: Cutlet, ROV, 1950s [13]

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More than a decade after ROVs were first introduced, they

became essential in the 1980s when much of the new offshore

development exceeded the reach of human divers. During the mid

1980s the marine ROV industry suffered from serious stagnation in

technological development caused, in part, by a drop in the price of oil

and a global economic recession. Since then, technological

development in the ROV industry has accelerated and today ROVs

perform numerous tasks in many fields. Their tasks range from the

simple inspection of sub-sea structures, pipeline and platforms to

connecting pipelines and placing underwater manifolds. They are

extensively used both in the initial construction of a sub-sea

development and the subsequent repair and maintenance.

ROV are widely used for underwater tasks as they have several

characteristics:

(1) There is no limited operation time as the cable associating the

ROV with the over water controller provides the ROV with

continuous energy.

(2) The operator directly controls and operates the ROV on the

water surface making many complex control problems easily.

(3) ROVs can be used for underwater operations which are not

achieved at this stage by AUV. For example, ROVs can

collaborate with manned submersibles to complete salvage

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missions of crashed aircraft or submarines.

2.1.1.3. Hybrid Remotely Operated Underwater Vehicle

Recently, a new type of deep-sea robotic vehicle called Nereus,

hybrid ROV, (Figure 2:3) made by WHOI has successfully reached the

deepest part of the world's ocean. The dive to 10,902 meters (6.8 miles)

occurred on 31st May, 2009, at the Challenger Deep in the Mariana

Trench in the western Pacific Ocean [14]. The Nereus underwater

vehicle was designed to perform scientific survey and sampling to the

full depth of the ocean. Its depth capability is significantly deeper than

that of other present operational vehicles; the second deepest

underwater vehicle can dive to 7,000 m maximum depth. Nereus is a

hybrid ROV that means it can be operated in the modes of both AUV

and ROV. AUV mode was used for broad-area survey and has the

capabilities of exploring and mapping the sea floor with sonars and

cameras, while ROV enables close-up imaging and sampling. The

ROV configuration incorporated a lightweight fiber-optic tether for

high-bandwidth, real-time video and data telemetry to the surface,

enabling high quality teleoperation. A manipulator, lightweight

hydraulic power unit, and sampling instruments were added to provide

sampling capabilities.

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Figure 2:3: Nereus can Switch Between Free-swimming and Tethered

Configurations, 2007 [15]

2.1.1.4. Shortcomings of Remotely Operated Underwater

Vehicles and Autonomous Underwater Vehicles

Previous research into underwater vehicles focused on Remotely

Operated Vehicles (ROVs), Autonomous Underwater Vehicles (AUVs)

and underwater manipulators (Hybrid ROV). Rapid development on

ROVs and AUVs boosted underwater robot technology. But ROVs and

AUVs still cannot travel as efficiently and quietly as a real fish can.

The key technology in the design of underwater vehicles is the

propulsion system. Traditional propellers employ screw propellers,

rotary jets or impellers. They have the following shortcomings:

(1) Low efficiency in energy utilization, which is the reason why

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an underwater robot is often designed in an unwieldy shape

carrying huge energy supply units.

(2) Big structure size and large weight which makes it difficult to

control due to the lack of flexibility and mobility.

(3) Large disturbance on the environment which would make it

hard to achieve data for its worsening the visibility of water

and disturbing the biological environment.

(4) Poor hidden performance makes it almost impossible to obtain

biological data by close observation or perform some specific

tasks.

(5) Inflexible movement, which creates a big problem when it

works in a small space or needs to response quickly and

flexibly.

To meet the needs of the development of marine science,

scientists are looking for other high-efficient and flexible underwater

propulsion modes [16].

2.1.2. Biomimetic Robot Fish Design

In recent years, with bionics and robotics research, underwater

biomimetic propulsion technology became a hot spot in AUV study. It

provides new ideas for developing high-efficient, high maneuverability,

low noise and easily concealed underwater propulsion [17-19].

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Therefore, biomimetic robot fish, a new type of underwater biomimetic

robot, has attracted great attention because of its silence in moving and

its energy efficiency when compared to conventional

propeller-oriented propulsive mechanisms.

MIT successfully developed an eight-link, fish-like

machine-RoboTuna (Figure 2:4), which was the first biomimetic tuna.

RoboTuna and the subsequent RoboPike (Figure 2:4) [18, 20] projects

attempted to create AUVs with increased energy savings and longer

mission duration by utilizing a flexible posterior body and a flapping

foil (tail fin).

Figure 2:4: RoboTuna, MIT [21] Figure 2:5: RoboPike, MIT [22]

In Nagoya University, Guo developed a kind of underwater micro

robot by using Ionic Conducting Polymer Film (ICPF) actuator [23,

24]. Mitsubishi Heavy Industries (MHI) created a robotic replica of the

rarely-seen coelacanth which died out millions of years ago and was

known only from fossils [25]. Scientists in Northeastern University

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developed an underwater lamprey-like robot (Figure 2:6) [26]

employing SMA and links structure to mimic an lamprey’s undulated

propulsion. The Swiss Federal Institute of Technology Lausanne

(EPFL) constructed AmphiBot I, a biologically inspired amphibious

snake-like robot capable of crawling and swimming [27, 28]. Both the

structure and the controller of the robot are inspired by elongate

vertebrates. K H Low designed a robot fish with undulating fins

[29-31]. The Harbin Institute of Technology conducted underwater

robot research that imitated the propulsion mechanical structure of fish

fins and constructed an experiment platform using elastic module

(Figure 2:7) [32]. The National University of Defense Technology, Xie

et al. investigated the Long Flexible Fin Undulation equipment, which

was based on the undulatory calisthenics of Gymnarchus niloticus’s

long flexible dorsal fin [33]. Peking University developed a

biomimetic dolphin (Figure 2:8) and built a series of experiments and a

test platform [34]. The Institute of Automation Chinese Academy of

Sciences studied the control and the coordination of robot fish (Figure

2:9) [35-39].

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Biomimetic robot fish brought revolutionary processes to the

development of underwater robots, especially in the propulsion area.

They can mimic the movement of a fish in nature and significantly

enhance the efficiency of biomimetic robot fish propulsion. But the

flexibility of a fish and its ability to perceiving the water current is hard

to be realized in robot fish. How to give underwater robots the tactile

capacity to obtain water current information is a new research topic. In

next section, haptics development will be reviewed.

2.1.3. Haptics and Application

Haptic feedback refers to sensing and manipulation through touch,

often referred to as simply "haptics". There have been several efforts to

define terminologies for haptics[43, 44]. While there is no difference

between haptic and tactile in most dictionary definitions[45], many

researchers and developers use haptic to include all haptic sensations

and limit the use of tactile to mechanical stimulation of the skin. The

science of haptics and the creation of haptic devices depend on

knowledge of the human body, especially its capability to sense both

touch to the skin and kinaesthetic activity in the limbs and body joints

[46]. When referring to mobile phones and similar devices, this means

the use of vibrations from the device's vibration alarm to denote that a

touch screen button has been pressed. In this particular example, the

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phone would vibrate slightly in response to the user's activation of an

on-screen control, making up for the lack of a normal tactile response

that the user would experience when pressing a physical button. The

resistive force that some "force feedback" joysticks and video game

steering wheels provide is another form of haptic feedback[47].

A haptic interface is a feedback device that generates sensation to

the skin and muscles, including a sense of touch, weight and rigidity

[48]. Compared to ordinary visual and auditory sensations, haptics is

difficult to synthesize. But the sense of touch is vital for understanding

the real world. The haptic interface to enhance computer-human

interaction has been applied in many areas including computer-assisted

and simulated surgery, autonomous exploration of hazardous or remote

environments, undersea salvage, enabling technologies, micro/nano

manipulation, education and design. It mainly went through following

transversions [49]:

(1) Early haptic interface archetype

In the mid-1990s, terms such as teleoperation, telepresence,

robotics, telerobotics and supervisory control had been used

interchangeably since researchers accepted the definitions considering

the systems aspects of controlling remote robotic vehicles and

manipulators [50, 51]. The history of the haptic interface dates back to

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this period, when a master-slave system was proposed by Goertz

(1952)[48]. Haptic interfaces were established out of the field of

tele-operation which was then employed in the remote manipulation of

radioactive materials. The ultimate goal of the tele-operation system

was "transparency". That is, a user interacting with the master device

in a master-slave pair should not be able to distinguish between using

the master controller and manipulating the actual tool itself. Early

haptic interface systems were therefore developed purely for

telerobotic applications.

(2) Early bilateral manipulators

Bilateral Master-Slave Manipulators (MSMs) , with the same

functions as today’s desktop haptic feedback systems, permit safe,

remote handling of irradiated material under direct human control and

supported by direct (lead-window) and indirect (closed-circuit TV)

vision.[52]

(3) Servo manipulators

Servo manipulators were designed to incorporate ac-driven servos,

connected back-to-back, to provide force reflection, having the

advantages of being mobile (cable linkages) and possessing large load

carrying capacities.

(4) Exoskeletons

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Exoskeletons originated partly as “Man Amplifiers”, capable,

through direct human slaving, of lifting and moving heavy loads.

Because of the emergence of a range of lightweight, low-cost body

systems developed under the Virtual Reality (VR) banner, the

exoskeleton received renewed interest in the early 1990s as a means of

registering body movement in a virtual environment and, importantly,

as a technique for feeding haptic data back to the immersed user [53].

Figure 2:10 shows the GLAD-IN-ART (Glove-like Advanced Devices

in Artificial Reality) project. The system was designed to record both

the pose and configuration of angles of the user's hand. Then the

manipulation performed by the human hand was replicated in 3D

computer world model.

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2.2. Fish Propulsion Theory

In nature, a fish adjusts itself to its hydrodynamic environment

and becomes a perfect swimming expert through years of evolution.

Fish can achieve tremendous propulsive efficiency and excellent

maneuverability with little loss of stability by coordinating its body,

fins and tail. Researchers believe that these remarkable abilities can

inspire innovative designs to improve the performance, especially

maneuverability and stabilization, of underwater robots. It also could

bring forward a revolutionary change in future navigation propulsion.

Many researchers studied fish body structures and swimming

characteristics and fruitful results have been achieved through

long-term research activities.

In 1926, Breder classified fish swimming locomotion into two

generic categories on the basis of the movement of temporal features

[17, 55]:

(1) Periodic (or steady or sustained) swimming, characterized by

a cyclic repetition of the propulsive movements. Periodic

swimming is employed by fish to cover relatively large

distances at a more or less constant speed.

(2) Transient (or unsteady) movement that includes rapid starts,

escaping maneuvers and turns. Transient movement lasts

milliseconds and is typically used for catching prey or

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avoiding predators.

In 1984 P. Webb put forward a detailed method of classifying fish

swimming propulsive models according to the different part of the

body which a fish uses to swim [56-58]. Fish propulsive models can be

categorized into:

(1) Body and/or caudal fin (BCF) model. It can achieve greater

thrust and acceleration

(2) Using median and/or paired fin (MPF) propulsion. It is

generally employed at slow speeds, offering greater

maneuverability and better propulsive efficiency

The BCF model can be subdivided into the eel model (Figure 2:13

(a)), the sub-caranginae model (Figure 2:13 (b)), the caranginae model

(Figure 2:13 (c)) and the caranginae plus crescent shape caudal fin

model (Figure 2:13 (d)) based on the ratio of the locomotion part

length to the whole length of the fish body.

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(a) (b) (c) (d)

Figure 2:13: Four Fish Swimming Propulsive Models [58]

In 2000, M. Triantafyllow research group of MIT pointed out in

the overview of fish propulsive mechanism study [59, 60]:

(1) The three-dimensional (3D) unsteady flow mechanics model

describing the fish tail trace is incomplete.

(2) Vorticity control is one of the most important key factors for

fish swimming highly efficiently and at a high velocity. In

1991 Tokomaru et al. found that fish can use unsteady body

motion and unsteady forcing in the flow for efficient vorticity

control [61]. This was confirmed theoretically [62] and

experimentally [63] in 1994. As to a high-aspect ratio flapping

foil, five prime parameters affect its propulsion capability: (a)

the amplitude of heave motion compared with the chord length;

(b) the feathering parameter (ratio of pitching angle compared

with the maximum angle of attack induced by the heave

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motion); (c) the phase angle between heave and pitch; (d) the

reduced frequency; and (e) the relative position of the pitching

axis. The Strouhal number and the nominal angle of attack

may be used instead of the reduced frequency and feathering

parameter.

The Strouhal number is a nondimensionalized frequency,

defined in analogy with bluff body flows as S = / (2- 1)

where f is the frequency of oscillation, A is the width of the

wake (often approximated by the lateral total excursion of the

foil), and U is the velocity of motion. Because the width of the

wake is not a priori known, the lateral excursion of the foil is

often used to determine the Strouhal number. The optimum

range of Strouhal number—between 0.25 and 0.35—is found

for certain specific profiles used in the research of

Triantafyllou et al. [63]; in other cases, different values may be

obtained.

(3) The flow about the fish body and the tail and the formation of

a reverse Kármán Street in the wake have been observed by

using experimental Digital Particle Image Velocimetry (DPIV)

[64, 65]or calculated by an inviscid numerical formulation[66].

(4) The rapidity and efficiency of the fishes’ swimming are

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relative to the “C” shape movement of the fish body[67, 68],

where the fish is bent into a “C” shape at the end of the first

contraction of the lateral musculature.

Based on the steady flow theory, Taylor calculated the fluid

dynamics of a swimming fish, which is the early resistance model[69].

Afterwards, kinematic models were built up close to the actual fish

movement. Lighthill developed the mathematic model analyzing

carangiform fish propulsion movement according to the

small-amplitude potential theory for the first time [70]. Wu

investigated two-dimensional (2D) waving plate theory by using

potential flow theory and linearized boundary conditions [71]. This

theory treats fish as elastic plates so as to analyse the hydrodynamic

features of the carangiform fish. Lighthill built a model based on

elongated-body theory (an extended version of inviscid slender-body

theory) to study the carangiform propulsion mechanism [72]. Later, the

large-amplitude elongated-body theory [73] was propounded to analyse

the irregular amplitude of the tail. Chopra et al. brought forward

two-dimensional theory [74] to evaluate the propulsion of the lunate

tail of large aspect ratio. this is a complement to the large-amplitude

elongated-body theory of Lighthill.

Considering the biomechanical properties of swimming fishes and

the dynamic characteristics of its structure, Videler et al. put forward

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the thin body theory being specific to fish with a small ratio of its body

length to its lateral amplitude[75]. With the assumption that the

stiffness of the fish longitudinally bending is a constant, Cheng et al.

lodged the waving plate theory and dynamic beam theory [76].

Triantfyllou [18, 59, 77] found that the jet formed behind the fish body

played an important part in propulsion. Tong developed the 3-D

waving plate theory (3DWDP) based on the 2-D waving plate theory

and a semi-analytic semi-numeric method was adopted to obtain the

3-D nonstationary linear solutions [78].

These seminal works provided a firm theoretical basis for

studying the swimming of fish and gave insight into the basic

swimming propulsive mechanisms. It made the development of

underwater biomimetic robots possible.

2.3. Research into Underwater Biomimetic Robots

With the development of propulsive theories and robotic

technologies, the research into a biomimetic robot fish with high

velocity, high efficiency and high maneuverability is a hotspot. It may

provide significant insights into both the theory and application of

underwater robotics. Observations show that a fish in nature can

achieve great propulsive efficiency and excellent maneuverability

through the coordinated motion of the body, fins, and tail. In 1994,

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RoboTuna (Figure 2:4), the first robotic fish in the world was

successfully developed, demonstrated that the power required to propel

the swimming fish-like body was significantly smaller than that

required to drag the body straightforward with the same speed [18, 20].

McIsaac et al. developed an underwater eel robot [79, 80] and analysed

its kinematics and kinetics. National Maritime Research Institute

(NMRI) developed a high-performance and multi-purpose fish robot,

UPF-2001 [81], whose length is 0.97m made up of 2 links. It can

swing maximum at 12Hz and swim at 0.97m/s. UPF-2001 already has

had the ability of 3D locomotion with pectoral fins and rubber,

realizing diving, turning and so on. Xiao et al. designed an arithmetic

of point-to-point fuzzy control based on a control response table with

Max-Min inference in Matlab. This met the needs of research into

real-time cooperation and coordination of multiple Biomimetic

Robot-fish. [82]. Wang et al. developed the biomimetic dolphin and

built a series of experiments on a test platform to explore the

coordination method for multiple robot fish in underwater transport

tasks[83].

Previous underwater biomimetic robots mimicked many of the

good properties of real fish, but an important function, apperceiving

currents, cannot be enforced without haptic functions. In this thesis,

haptic function for underwater biomimetic robots will be explored

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based on a fully functional biomimetic robot fish. It was designed

according to the prototype of the carangiform fish with a carangiform

tail for propulsion, a barycenter-adjustor for diving, an information

relay system on water for information transmission with an upper

console and sensors for detecting information. The locomotion control

of a robot fish is a major factor for investigation in robot fish. In the

following section, the Kinematics and Locomotion Control of robot

fish will be reviewed.

2.4. Kinematics and Locomotion Control of robot fishes

Based on the research of fish movement mechanism and the

prototypes, researchers carried out much investigation work into a

variety of dynamics, kinematics and motion control of the robot fish

prototypes. Triantafyllou et al. [18, 77] and Barrett et al. [20] measured

the force distribution on the swimming 8-joints, swing-wing-propelled

Robotuna. The experimental results demonstrated that the power

required to propel an actively swimming, streamlined, fish-like body is

significantly smaller than the power needed to tow the body straight

and rigid at the same speed. The drag reduction was caused exclusively

by the actively controlled transverse motion when the phase speed of

the body wave was greater than the forward speed. In the same period,

Barrett et al. [84] developed a self-optimizing motion controller based

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on a genetic algorithm, which effectively used evolutionary principles

to search for the main seven parameters of the robot fish movement

mechanical model and that exponentially optimized swimming

performance.

Kato et al. [85] studied the control of the pectoral fins propulsive

mechanical model applied on Black Bass. Harper et al. [86] developed

a model for the dynamics of oscillating foil propulsion when springs

are used in series, with actuators to reduce energy costs. Explicit

expressions were derived for spring constants which are optimal in this

sense. Kelly et al. [87] proposed a planar model for the swimming of

the carangiform fish based on reduced Euler-Lagrange equations for

the interaction of a rigid body and an incompressible fluid. Hirata et al.

[88] designed a form of three-link robotic fish to analyse the

carangiform-like swimming. They also experimentally verified a

sample quasi-steady fluid flow model for predicting the thrust

generated by the flapping tail.

Morgansen et al. [89] realized trajectory tracking for an

experimental planar carangiform-like robotic fish system by applying

the nonlinear control methods to generate the system input. Saimek at

el [90] proposed a practical maneuvering control strategy for an

aquatic vehicle using an oscillating foil as a propulsor, where the

control task was decomposed into the off-line step of motion planning

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and the on-line step of feedback tracking.

In order to achieve an autonomous system which could adaptively

behave through learning in the real world, Iilima et al. [19] constructed

a distributed autonomous swimming robot (Figure 2:14). This

consisted of a mechanically linked multi-agent and an adopted adaptive

oscillator method, called a general decision making for distributed

autonomous systems (DASs). This robot could complete a target

approach including obstacle avoidance via a modified Q-learning,

where plural Q-tables were used alternately according to dead-lock

situations. As shown in Figure 2:14-A and Figure 2:14-B, each round

float (diameter: 15 cm) was taken as one agent, and a three-agent

version was demonstrated here. Each agent had four solar panels that

functioned as light sensors, a CPU, and an angular controlling servo

motor that were located at the pivot of each joint between neighboring

agents. Two-channel serial ports were used for communication

between agents. Moving force was generated by pushing water aside

with fins. Additionally, for structural necessity, the robot had a dummy

agent at one end of the chain carrying battery cells for driving the

robot.

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Figure 2:14: A: Distributed Autonomous Swimming Robot (3 agents);B:

Structure of an Agent [19]

Supported by the National Science Foundation (NSF) from 2000,

Princeton University began to study the dynamics of the coordinated

movements among several Underwater Gliders[91]. They aimed to

establish an autonomous, cooperative multi-glider system to achieve

the monitoring of the Monterey Bay ecosystem. Figure 2:15 shows the

Princeton 3D multi-vehicle experimental test-bed. The

multi-underwater-glider system, Princeton Grouper, could be

teleoperated. Leonard et al. proposed a framework for coordinated and

distributed control of multiple autonomous vehicles using artificial

potentials and virtual leaders [92, 93]. Artificial potentials defined the

interaction control forces between neighboring vehicles and were

designed to enforce a desired inter-vehicle spacing. A virtual leader

was a moving reference point that influenced vehicles in its

neighborhood by means of additional artificial potentials which were

used to manipulated group geometry and direct the motion of the group.

Based on artificial potentials and virtual leaders, Ogren et al. put

forward a stable coordination strategy for vehicle formation missions

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involving group translation, rotation, expansion and contraction [94].

Symmetry in the framework was exploited to partially decouple the

mission control task into a formation management subtask and a

manoeuver management subtask. The designed dynamics of the virtual

leaders played a key role in satisfying the mission and ensuring the

stability and convergence properties of the formation.

Figure 2:15: Princeton 3D Multi-Vehicle Experimental Test-bed (left);

Experimental Pool (right) [95]

McIsaac et al. [79, 96] built up a symmetrical structure eel-like

robot based on the Lagrangian model to verify a simplified dynamic

model and open-loop control routines. Lie group method was

employed to simplify the model and a series of motion results was

obtained. Boyer et al. [97] set up the dynamic model of a continuous

three-dimensional swimming eel-like robot based on the

“geometrically exact beam theory”. It allowed the computation of the

motion of the eel and the control torque distribution from the

knowledge of the desired internal deformation imposed on its body.

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The Nonlinear Dynamics and Control Lab of University of Washington

[98] realized the depth control on their fin-actuated untethered

autonomous vehicles. Morgansen et al. [89, 99] at Control and

Dynamical Systems Lab of California Institute of Technology designed

oscillatory controls for mechanical systems (Figure 2:16), which could

measure the data of the system in real-time. They also made use of

employing the nonlinear control methods to control the complex fluid

in the fluctuating propulsion. The use of this type of feedback was

shown to work quite well in simulation. A slightly modified version of

the controller demonstrated convergence with a simple forward

swimming trajectory in experiments.

Figure 2:16: Photograph and Schematic of Side View of Fish Design (left);

Photograph from Rear and Schematic of Top View of Fish Design (right) [89]

Every modeling above had their own distinguishing feature. But

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for the special requirements of the simulation of the haptic biomimetic

robot fish, another suitable modeling method had to be found. In this

thesis, the kinematic modeling for the biomimetic robot fish will be set

up using Lagrangian method based on a simplified link structure of the

machine, a typical series structure. The kinematic modeling provided a

real-time motion analysis result for the robot fish.

2.5. Hydrodynamic Analysis of Underwater Robot

It should be noted that most existing control algorithms of robot

fish are based on a simplified propulsive model that only provides a

rough prediction of the effect of hydrodynamics on robot fish. To

obtain an accurate prediction of the hydrodynamic force on robotic fish,

it is necessary to conduct dynamic analysis of the surrounding fluid by

computational fluid dynamics (CFD) [100].

CFD analysis has been widely used in many areas, including

vehicle design, aircraft design and ground robot developments due to

the following reasons [101]:

(1) CFD simulations can be a useful tool for designers to

understand the complex physics of the flow phenomena

involved in the fluid dynamics.

(2) CFD simulations require less time than field tests.

Moreover, different models can be tested with CFD

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simulation before actual prototype models are created for

tests.

(3) CFD also provides detailed visualization of the flow field,

which is difficult to be obtained by experimental facilities.

CFD simulations and analyses of robot fish have been studied in

the past years. Zhang et al. [102] investigated fluid dynamics, pressure

and velocity distribution, and the production of forces associated with

an undulatory mechanical fin. Tangorra et al. [103] also employed

CFD simulation, together with stereo DPIV and Proper Orthogonal

Decomposition (POD), to estimate the hydrodynamic force generated

by the complex component motions of their biorobotic pectoral fin and

to analyse its hydrodynamics. The fins studied by Zhang et al. and

Tangorra et al. were important factors in the development of propulsive

devices that would make an underwater robot fish have the ability to

produce and control thrust like highly maneuverable fish.

Mohammadshahi et al. [104] evaluated hydrodynamic forces of a

fish-like swimming robot by using a two-dimensional (2D) CFD model;

this provided important results in optimizing performance parameters

in the process of design and fabrication. However, 2D model of robot

fish cannot offer abundant tri-dimensional information when compared

to 3D simulation. Anton et al. [105] adopted CFD modeling and

examined the flow field, the produced thrust, and the bending moments

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at the joints of two-link tails of a robot fish. However, the two-link tail

fins were assumed to be rigid, thin and light. In reality, popular

biomimetic robot fish bodies are soft and quite flexible. Listak et al.

[106] created a 3D computer model for a biomimetic robot and

simulated the ideal ellipsoid with Gerris which helped them find an

ideal robot fish body with low drag and improved the design, although

without detailed analysis of the simulation results.

In this thesis, to produce significant information on flow pattern,

velocity and pressure fields, and to provide an insight into both the

design and the application of robot fishes, a 3D CFD simulation was

investigated for the robot fish prototype [107] using Fluent® 6.3.26.

2.6. Haptics for Underwater Applications

The idea of using touch as a means of communication was

popularized by Craig et al. [108] and Sherrick [109]: “Our

understanding of how simple patterns combine to yield the complexity

needed to increase channel capacity for continuous information

streams is still primitive”. Haptic feedback technology development

went from telepresence to virtual reality (referring to section 2.1.3).

New technologies from the area of virtual reality (VR) now allow

computer users to use their sense of touch to feel virtual objects.

Unlike traditional interfaces that provide visual and auditory

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information, haptic interfaces not only generate mechanical signals that

stimulate human kinesthetic and touch channels, but also provide

humans with the means to act on their environment. This is defined as

the association of gesture to touch and kinesthesia to provide for

communication between the humans and machines[110].

Researchers recently began to use haptic devices to study physical

interaction with virtual environments and enhance the ability of

performing a variety of complex computer interaction tasks [111-113].

Underwater haptic application is necessary when visual

information is difficult to obtain due to unclear water or poor light

especially in manned underwater machines. Taketsugu et al. presented

a teleoperation of construction machines with haptic information

substituting for visual information in underwater applications [114]. It

was applied to manned underwater backhoes using electric control

valves, articulation angle sensors and a reaction force sensor. The

components control technologies included the visualization of haptic

images, force feedback and similar figure controllers. They obtained

good results in both 2D and 3D level experiments on land. Further

research on its underwater application is expected to be done.

It is common that people apply force sensors in an underwater

machine to test the force for haptic force feedback. Yoshinori D. et al.

presented a method for very rapidly estimating and displaying forces in

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haptic interaction with water[115]. They simulated the dynamics of

water which was decomposed into two parts. One was a linear flow

expressed by a wave equation used to compute water waves. The other

was a more complex nonlinear flow around the object precomputed by

solving Navier-Stokes equations and stored in a database. The

precomputed non-linear flow and the linear flow were combined to

compute the forces due to water. Their method provided the real-time

display of the forces acting on rigid objects due to water. But they still

have limitations, such as their inability to take into account for

randomness due to turbulent flow, cannot correctly compute the forces

for a rotating pointer object, and cannot accurately reproduce the forces

for the pointer object with other near objects.

There are few published techniques for haptic interaction and

rendering with fluids. In this thesis, two kinds of simulation methods

for calculating the force on the robot fish when it swims in water are

presented. The results were used for the haptic interaction with the

haptic robot fish system.

2.7. Summary

In this chapter, a systematic review on the development of

underwater robot fish, haptic technology and their extensions were

provided. Both the expertise of underwater robot fish and haptics have

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achieved great growth. However, combining these together to obtain a

new haptic robot fish system is an innovation. It would bring

underwater research many benefits, for example, the tactile interaction

for users feeling the force the robot fish gets in water; easier control of

the robot fish via the direct haptic feedback and the detection of data of

the current surrounding the robot fish to help it autonomously evade

dangerous currents.

In the remainder of the thesis, the hardware and software design

of the biomimetic robot fish, its CFD simulation results and the

framework of the haptic robot fish system will be demonstrated.

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3. Design of a Biomimetic Robot Fish

A novel medium size biomimetic robot fish (62 centimetres in

length) with a carangiform tail for propulsion and barycenter-adjustor

for diving were designed based on the analysis of propulsion and

maneuvering mechanisms for carangiform swimming. It integrated an

information relay system on water for information transmitting and

kinds of sensors, infrared sensors, press sensor and CCD camera, for

information processing. It has the most functions in this dimension of

robot fish. This chapter presents the detailed design of the biomimetic

robot fish including the mechanical structure diagram, the control

system design and the biomimetic motion library conception [107]. It

is the basis of the development of the novel haptic biomimetic robot

fish.

3.1. Problem Formulation

The carangiform fish was chosen as the prototype of the

biomimetic robot fish. There were several difficult tasks in the design

of the fish:

(1) The following properties were required for the design of the

support frame (aluminum exoskeleton + head):

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good water proof qualities to let the robot fish swim under

water; the ability to carry and protect a variety of inside units,

keeping the same volume when the robot fish changes

swimming depth, and with a function to mimic the tail shape

transformation of a real fish.

(2) The realization of real-time communication between the robot

fish and the upper console was an important issue in this

project. Abundant data, especially from the camera, should be

transferred to the upper console in a real time way. But general

wireless signals cannot transfer far because of bad underwater

signal attenuation.

(3) The ability to control the free swimming of the robot fish,

especially the descending and ascending motions. Realizing an

up-down motion in a 3-D workspace is quite hard for a small

robot fish prototype because of the limited volume of the robot

fish body. In future applications, autonomous motion control is

surely necessary for robot fish. All motions that a real fish has

should be considered to be implemented on robot fish.

3.2. The Biomimetic Robot Fish

The biomimetic robot fish actualizes the carangiform swimming

method via the coordinated movement of the four links driven by

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motors. Four links are used in this robot fish for the mean between the

maneuverability and redundancy of the mechanism and the control and

construction of the robot. As shown in Figure 3:1, the biomimetic robot

fish was made up of the following parts:

A sensing unit including 3 infrared sensors, an underwater

press sensor, and a charge-coupled device (CCD) camera)

A control unit composed of the Micro Control Unit (MCU)

and peripherals

A communication unit involving an optical transmitter, an

optical receiver, wireless modules, optical fiber cable and

other cables

An actuation unit which consisted of a pitch motor and 4 tail

motors

A support frame containing an aluminum exoskeleton and a

head

Accessories ranging from Li-polymer batteries, waterproofed

skin and a caudal fin

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Figure 3:1: Biomimetic Robot Fish System

The robot fish has a clipper-built head, a flexible body and a

caudal fin. The rigid head is made from FRP (Fiberglass-Reinforced

Plastics). Inside, MCU, batteries, sensors and peripherals are installed.

The flexible body is built by four links jointed together by an

aluminum exoskeleton which is driven by four tail motors and

airproofed by a waterproofed skin. The flexible body cooperates with

the caudal fin which simulates the movement of the carangiform fish

tail causing the robot fish to swim forward. At the same time, in order

to maintain balance when the robot fish is swimming in water, some

weights are fitted into the robot fish’s body.

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3.3. Mechanical Structure

3.3.1. Support Frame

Each part of the robot fish has quite different properties, as

following:

(1) The robot fish head:

The head, made of 5 mm thick FRP, is composed by two parts

joggled together and sealed by glue. The structure makes it easy to

install the MCU, batteries, sensors and peripherals into the space inside

the robot fish head. (Figure 3:2. Please note: In all mechanical

drawings of this chapter, the surface roughness is 12.5 and the

tolerance is ±0.1 without any special indication.)

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Figure 3:2: the Head of the Biomimetic Robot Fish

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(2) The flexible body:

The flexible body is built of four motor driving links. Every motor

is mounted in two pieces of aluminum exoskeleton including an

internal connection (Figure 3:3) and an external connection (Figure

3:4), which are called one link. Every two adjacent links are connected

together by a 2 mm thick aluminum support board (Figure 3:5), which

doubles for propping up the outside waterproofed skin and shaping the

fish tail.

Figure 3:3: Internal Connection

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Figure 3:4: External Connection. The left one is used for the connection of the

first 3 links; the right one is used for connecting the last link and caudal fin.

Figure 3:5: Support Board

(3) The caudal fin:

The shape of the caudal fin is similar in shape to a swordfish’s tail,

which looks like a crescent as show in Figure 3:1. It is made of a tough,

thin plastic plate and fixed to the last external connection by a caudal

vertebra (Figure 3:6).

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Figure 3:6: Caudal Vertebra

3.3.2. Actuation Unit

To realize a controllable freely swimming robot, Sanwa Servo

RS-995 (Figure 3:7) was chosen for the robot fish motor as it has

excellent performance when compared to other types of motors. The

actuation unit of the robot fish is made up of one pitch motor and four

tail motors (refer to Figure 3:1)

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Figure 3:7: Sanwa Servo RS-995 [116]

The four tail motors drive the four links and the caudal fin to

mimic the swing of the tail of carangiform fish which causes the robot

fish to swim forward. Section 3.5.1 will expound the method as to how

the motors are controlled.

There are several methods to implement a descending or

ascending motion such as changing gravitation (Buoyancy), pectoral

fins, changing body shape and changing the barycenter[117].

Considering the features of these methods and the difficulties of their

realization, changing the gravity center was chosen to realize the robot

fish’s 3-D movement. A barycenter-adjustor was then designed and

implemented. It is driven by a motor and can swing to different angles

to change the gravity center of the whole robot fish. The robot fish can

pitch to swim upwards or downwards with this shift in the gravity

center. This will be discussed in detail in section 3.5.3.

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3.3.3. Communication Unit

Due to the limitation of the information processing capability of

the robot fish, it was necessary to design a communication system

between the robot fish and the outside. There are several methods of

the information transmission in the robot fish. One is to utilize wireless

equipment, which only works above the water surface because of

severe attenuation of the electromagnetic wave in water. The robot fish

has to swim only on water or ascend to the water surface to exchange

the data with the upper console. Another is to connect the robot fish

with the upper console by a cable directly; this can assure transfer

speed and accuracy. However, this method will limit the robot fish. In

this project, a buoyage information relay is presented. It is used as a

communication relay that connects the robot fish by cables on one

hand and communicates with the upper console by wireless on the

other.

3.3.4. Control and Sensing Units and Accessories

The processor of the robot fish MCU is ATmega128, a low-power

Complementary Metal Oxide Semiconductor (CMOS) 8-bit

microcontroller based on the Atmel AVR enhanced Reduced

Instruction Set Computing (RISC) architecture. By executing powerful

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instructions in a single clock cycle, the ATmega128 achieves

throughputs approaching 1 Million Instructions Per Second (MIPS) per

1 MHz, allowing the power consumption versus processing speed to be

optimized.

Several kinds of sensors equip the robot fish for autonomic

control and environmental monitoring. Firstly, three infrared sensors

mounted on the left, front and right side of the robot fish head are used

to detect obstacles. This is processed by MCU directly and keeps the

fish swimming safely. Secondly, the water depth information can be

gained by a pressure sensor set on the body; the robot fish can get

feedback about depth data for diving depth control. Thirdly, a camera

is installed on the fish head to provide abundant information in front of

the fish.

Some accessories, such as Li-polymer batteries (7.4V), and a

waterproofed skin are necessary for the normal work of the robot fish.

It is obvious that the capacity of the batteries should be as big as

possible but the volume and the mass should be as low as possible.

Two groups of batteries supplied power to the robot fish: one group for

the motors and the other one for the electro circuits. A rubber skin was

applied to protect the robot fish tail and satisfy the flexibility

requirement.

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3.4. Control system

The control system is shown in Figure 3:8. The MCU, using the

uCOS-II real-time operating system based on the minimal system of

Mega128, sends task-related PWM signals to the tail motors to control

its motion and to pitch the motor to change the fish’s center of gravity.

It exchanges the information with the outside via the buoyage

information relay.

Figure 3:8: The block diagram of the control system

There are two kinds of data: One is the mass visual record from

CCD camera, the other is the digital signal including the information

provided by other sensors and commands from the upper console. They

are transmitted separately. The digital signals are sent to the buoyage

information relay via normal cable after being converted into RS232

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Serial signal and then sent out by low frequency wireless module and

received by the upper console later. Vice versa, the digital signals may

be sent to the robot fish by the upper console via this information relay

system. At the same time, the visual signals are converted into light

signals and sent to the buoyage information relay via optical fiber cable,

where the light signals are resumed into electronic signals and then

sent out by high frequency wireless module. The upper console

receives the information and extracts it to make decisions for remote

control. The result of vision processing and the target identification

reflects the information of the environment and goals.

With the information from sensing units, the robot fish may make

decisions independently or execute a task after combining with the

commands from the upper console.

3.5. Biomimetic motion library

According to the behaviors of real fish and the specifics of

biomimetic robot fish, a biomimetic motion library was designed based

on the mechanical structure and the control system. The robot fish

adjusts its poses in water by controlling the oscillatory frequency of the

tail and the position of the gravity center. Accordingly, the motion

library includes acceleration, deceleration, uniform motion, turn, dive,

and even includes swimming backwards. Different combinations of

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these motions may be chosen according to the task required to be

executed.

The biomimetic motion library was established on the different

effects of the robot fish tail motion. Researchers point out that there is

an implied travelling wave in the body of swimming fish which runs

from its neck to tail [85, 118]. The wave amplitude increases gradually,

appears as the curvature of the fish’s spine and muscle and travels

faster than the fish’s forward movement. The robotic fish is devised

according to carangiform propulsion model whose propulsive wave

curve starts from the fish’s inertia center to its caudal link. It is

assumed that this kind of curve can be described by Eq. 3.1 [70, 84].

)])][sin([(),( 221 tkxxcxctxybody ω++= 3.1

where bodyy is the transverse displacement of fish body, x is the

displacement along main axis, k is the body wave number and

λπ2=k ,λ is the body wave length, 1c is the linear wave amplitude

envelope, 2c is the quadratic wave amplitude envelope, ω is the

body wave frequency, T/2πω = . A sample of the fish body wave

curve is shown in Figure 3:9.

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Figure 3:9: Links fitting fish’s body-wave

The parameters ( )ωλ,,, 21 cc are chosen to determine the proper

body wave. Four hinge links were adopted to simulate the locomotion

of fish tails Figure 3:1, the robot fish’s oscillatory part can be modeled

as a planar serial chain of links at an interval of 0 to π2×R along the

axial body displacement, where R is defined as the length ratio of the

fish's oscillating part to the whole sine wave. Let the length of each

link be )4,3,2,1( =jI j , the ratio of them be 4321 ::: llll , and the link

angle between 1−jl and jl be jϕ [119]. With the jϕ changing,

the fish's oscillatory part undulates along the travelling wave as Eq. 3.1

expressed. Impetus is produced when the speed of body wave

propagation exceeds the speed of the fish swimming forward [85, 118].

3.5.1. Realisation of Propulsion

The acceleration, deceleration and uniform motion are realized by

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changing the swing frequency of the robot fish tail. This is realized by

sending different signals to the motors driving the links of the tail.

Increasing the duty ratio of the PWM signal to the tail motors results in

the increase of the tail's swing frequency which increases the fish’s

swimming speed. On the contrary, reducing the duty ratio of the PWM

signal will result in the deceleration of the speed. If the tail motor

rotates uniformly, the robot fish will swim at uniform velocity [5].

In addition, the robot fish can be considered to realize swimming

backwards according to the study on kinematics and kinetics of the

Europe eel [120].

3.5.2. Swimming Direction Control

The orientation control is realized by superimposing different

link’s deflection. It is necessary to ensure that the oscillating rule

matches Eq. 3.1 in turning, so the arc is chosen as the oscillating axis

of the links. Correcting Eq. 3.1 gets Eq. 3.2 [121, 122]:

2 2 21 2( , ) [( )][sin( )]bodyy x t c x c x kx t R x Rω= + + + − − 3.2

where R is the radius of the tail axis, which is connected with the

turning radius. A sample of the corrected fish body wave curve is

shown in

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1l

2l3l

4l

( )dm

( )dm

Figure 3:10.

1l

2l3l

4l

( )dm

( )dm

Figure 3:10: The Corrected Fish Body Wave Curve

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3.5.3. Diving Control

As described above, the robot fish pitch uses the

barycenter-adjustor to change its posture [120]. As shown in Figure

3:11, O0 and O1 are respectively the initial position of buoyancy (FB)

centre and the gravity centre. m is the weight of the adjustor. M is the

fish weight without m. r is the length of the turning arm. When the

pitch motor turns θ (clockwise, assumed to be “+”), the

barycenter-adjustor moves forward. As a result, the robot fish’s gravity

centre moves forward to O1' and the robot fish gets a pitch angle α,

together with the tail’s swinging movement, it will swim downwards.

Figure 3:11: The Moment Analysis of barycenter-adjustor

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3.6. Prototype of the Robot Fish

Figure 3:12 gives a functional prototype of the biomimetic robot

fish with a flexible tail for propulsion, a barycenter-adjustor for diving

control and an information relay system for communicating to the

upper console. The hard head made of FRP contains and protects the

important MCU, batteries, sensors and peripherals. Three infrared

sensors are mounted on the left, front and right side of the robot fish

head for the detecting of obstacles, a pressure sensor is set on the body

for depth data feedback and a camera is installed on the fish head for

the obtaining of visual information. Jtag and recharge interface are also

mounted on the head for the convenience of software updating and

battery recharging. The whole robot fish size is about 620×160×80

mm3.

Figure 3:12: The functional prototype of the biomimetic robot fish

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3.7. Conclusions

In this chapter, a fully functional biomimetic robot fish with a

carangiform tail for propulsion and barycenter-adjustor for diving was

designed based on the analysis of propulsion and maneuvering

mechanisms for carangiform swimming. An information relay system

on water was designed for information transmission with the upper

console. The sensor information processing of the fish were studied.

The following two chapters will respectively demonstrate the

kinematic modeling and CFD simulation of the robot fish and a new

idea of adding haptics into the robot fish system will be described. This

will let the operator feel the force that the robot fish get when it is

swimming in water.

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4. Kinematic Modeling of Biomimetic Underwater Robot Locomotion

This chapter proposes a kinematic modeling method for the

biomimetic underwater robot locomotion in order to develop a simple

model to quickly analyse the swimming robot fish.

4.1. Introduction

The kinematic performance of underwater robot fish has been

studied, including the analysis of thrust forces and frictional forces, the

control the movement of robot fishes and to develop useful

applications [79, 97, 123]. McIsaac K. A., et al. [79] gave a Lagrangian

model, reduced by Lie group symmetries, for a symmetrical structured

robot eel. Boyer F., et al. [97] presented a dynamic modeling of a

continuous three-dimensional swimming eel-like robot. Morgansen K.

A., et al. [89] studied nonlinear control methods of robot fish

locomotion.

A kinematic modeling of biomimetic underwater robot

locomotion is offered. In this kinematic modeling method, a

Lagrangian function is built for free swimming robot fish based on a

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simplified geometric model as coupling the kinematic law of

continuous motion and the forces acted on the robot fish cannot be

calculated respectively. The fluid force acting on the robot fish is

divided into three components: the pressure on links, the approach

stream pressure and the frictional force. The movement of the robot

fish can be obtained by solving the second kind Lagrangian equation

and the fluid force. The forward motion of the swimming robot fish is

simulated and verified by experiment.

4.2. Problem Formulation

As the robot fish swimming action involves the kinematics of its

body and the hydrodynamic interaction with the surrounding fluid, it is

difficult to formulate a precise mathematical model by purely

analytical approaches. Kinematics and hydrodynamics modeling is one

of the most difficult tasks in robot fish research. Researchers have

focused on studying the mechanical movement of fishes. Most of the

obtained results are described by complex differential equations on the

theoretical analysis, but not on the kinematics, which cannot be used

conveniently for robot fish motion analysis and control.

On the other hand, the locomotion of fish in nature is continuous

and smooth due to the movements of a large number of spinal joints

smoothed by fish muscles. But in most robot fish, the machines are

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applied to simulate a small number of joints in the spine of fish and the

motors are used to simulate the muscle motion of fish. Four joints are

used in this case so the robot fish cannot be regarded as a smooth form,

but a cascade of multi-joint movement.

The basic theory for modeling the biomimetic robot fish is to

build the Lagrangian function unrelated with the internal force based

on the structure of four cascaded joints. The generalized forces from

the second kind Lagrange's equation are equal to the fluid forces

calculated according to the hydrodynamics. Then a series of partial

differential equations can be built to solve the movement of the robot

fish.

4.3. Outline of the Lagrangian Method

Robot dynamics is concerned with the relationship between the

forces and torque acting on a robot mechanism and the accelerations

they produce. To make the robot accelerate, the drive must provide

sufficient force and torque to drive the robot movement. Establishing

dynamic equations for the robot to determine the force, mass and

acceleration, and their relationship with the torque, moment of inertia

and angular acceleration, will be useful for the calculation of the

required force to complete a specific motion. Kinematic analysis of the

robot will help designers determine the external maximum load and

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select the appropriate drives.

As the mechanical structure of the robot fish is quite similar to the

multi-joint series structure of industrial robots, the dynamics analysis

and modeling will be mainly based on Lagrange mechanics and

Newton's mechanics. For industrial robots with multi-degrees of

freedom and three-dimensional mass distribution, using Lagrangian

mechanics can create a well-structured robot dynamic equation.

Lagrangian mechanics is a method that describes a time derivative and

system variables derivative based on the energy item. The Lagrangian

for classical mechanics is taken to be the difference between the kinetic

energy and the potential energy, as Eq. 4.1:

PKL −= 4.1

where, L is the Lagrangian function, K is the system kinetic energy, P

is the potential energy.

For an industrial robot, in Eq. 4.1, K is the total kinetic energy of

the motion arm, P is the total potential energy of the motion arm. So

the Lagrangian-Euler function is obtained:

ii i

d L Ldt q q

τ⎡ ⎤∂ ∂= −⎢ ⎥∂ ∂⎣ ⎦&

4.2

in which, L is the Lagrangian function, iτ is the system generalized

force or torque, iq is the system variables, iq& is the first derivative of

the system variables, 1, 2, , i n= K .

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For industrial robots, iτ is the generalized force or torque which

works on the ith joint in the system to drive the ith member bar, iq is

the generalized coordinates for the operating arm, iq& is the first

derivative of the generalized coordinates for the operating arm. Known

from Eq. 4.2, a group of generalized coordinates should be selected

which can easily and accurately describe the system. Because the angle

of the rotating joint and the displacement of the moving joint of the

industrial robot can be measured by potentiometers, encoders and other

kinds of sensors, the industrial robot generalized coordinates are

usually defined by the angle and the displacement of the joints.

As the robot fish keeps a continuous locomotion in water and gets

coupled fluid forces, which cannot be calculated independently, the

Lagrange function was established for free moving robot fish

according to the mechanical characteristics of the joint structure. The

fluid forces that the robot fish suffers in water were also simplified into

the side pressure, the facing flow resistance, and the friction resistance.

According to the above second Lagrange equation, I solved the robot

fish real-time motion, calculated the kinematic parameters and then

offered the simulation results of its various movement strategies. The

optimal parameters of the robot fish locomotion were obtained

according to this simulation calculation. Finally, the simulation results

were verified by experiments made on a global test platform with

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visual positioning of the robot fish.

4.4. Kinematic Modeling of the Robot fish

4.4.1. Geometry Simplification of the Robot Fish

The propeller of the robot fish developed in this study is

essentially different from the traditional AUV, and there is not any

existing model for the movement. To analyse, control and optimize the

motion of the robot fish, a motion model is needed. This robot fish is a

typical serial link robot, in which the relationship between its

movement and energy can be represented by the Lagrange equations.

The robot fish has a significant difference to general robots in

kinematics. It has neither any fixed base (such as the fixed point of a

robot arm), nor any fixed reference system (such as the ground

reference system of a mobile robot) in its motion. The robot fish

swimming in water is completely free and the locomotion of each joint

interacts with water which determines the magnitude and direction of

the fluid forces. The forces also determine the robot fish’s movement.

In another word, the kinematics and dynamic properties are

interdependent and a combined solution is required.

Some assumptions are made to simplify the simulation:

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(1) The body of the robot fish can be treated as five plates jointed

together [79, 123].

(2) The robot fish swims in still water, and it is not affected by the

reflection wave from the environment.

(3) The deformation of the robot fish can be ignored except for

the motion of the joints.

The robot fish can be treated as being made up of three simple

parts: a hard head, a flexible tail and a crescent-shaped caudal fin. The

head moves passively to some extent, and the tail in the mechanical

point of view is designed to be a multi-joint series-connected structure.

The robot fish joints are redefined. The head and the tail are no longer

distinguished so that all parts are considered as links [79, 89, 96, 99],

as shown in Figure 4:1:

Figure 4:1: Robot Fish Joint-link Structure

Two coordinates, a world rectangular coordinate system (WRCS)

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and a polar coordinate system, are given to describe the robot fish

motion, shown in Figure 4:2. XOY is the WRCS. Another coordinate

is the polar coordinate system with the pole O at the first joint and the

polar axis pointing in the tail’s initial direction when the fish is in a

naturally laxative status.

Axial Body Displacement 1l 2l 4l

3l

2φ3φ

5l

Figure 4:2: Simplified Coordinates of the Robot Rish and its Parameters

Definition

The traveling body-wave is decomposed into two parts: the

time-independent spline curve sequences in an oscillation period,

which is described by Eq. 4.3, and the time-dependent oscillating

frequency, which is described as Eq. 4.4

)])][sin([(),( 221 tkxxcxctxybody ω++= 4.3

21 2

2( , ) [( )][sin( )]bodyy x i c x c x kx iMπ= + ±

4.4

But it is too difficult to calculate above equations, the joint angles

are defined as Eq. 4.5:

( ) sin( )i i it A tφ ω ψ= + 4.5

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where iA is ith link’s amplitude, iψ is ith link’s phase, 1, ..., 1i N= − ,

N is the number of links. Both of them can be calculated from Eq. 4.3

as Eq. 4.6:

1 12

1 22 2 2

1 22 2

1

2

( ( ) )( )

i i

i j jN Nn n

j jn ni

i jj

AmpA c l c lc l c l

k lψ

+ +

= =

= =

+

=

= ++

=

∑ ∑∑ ∑

∑4.6

Where, Amp is adjustable caudal swinging amplitude,and

21 2

2 2

( )N N

j jn n

c l c l= =

+∑ ∑ is normalization coefficient.

4.4.2. The Lagrangean Equation of the Robot Fish

rr1ϕ

3θ4θ

2ϕ 3ϕ

1 1( , )g gx y

1 1( , )f fx y2 2( , )f fx y

5θ4ϕ

Figure 4:3: The Five Links Robot Fish and Some Parameters Definition

Figure 4:3 shows the links at a moment under the coordinate

systems. XOY is the WRCS. In the figure, li is the length of ith link of

the robot fish. θi is the angle between ith link and the polar coordinate,

φi is the angle between the ith link and the extension line of the (i-1)th

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link. Both of them are anti-clockwise positive. ( ,f fi ix y ), ( ,g g

i ix y ) and

( ,i ix y ) are the center of form,the center of gravity and the extreme

point near fish head of the ith link, respectively. Fi is the force the ith

link suffers, which will be decomposed into several component forces

in the following analysis. The joint angle φi is pre-given according to

the fish swimming mechanism.

The potential energy is a constant, E, while the robot fish swims

in water. The kinetic energy of each link is the sum of the kinetic

energy of translation under WRCS and the kinetic energy of rotation

under the centre-of-mass system, so the Lagrange’s function is defined

as Eq. 4.7:

( ) ( )( ) ( )

2 2

1 1

22 2

1 1

1 12 21 12 2

N N

i i i ii iN N

g gi i i i i

i i

L m v I E

m x y I E

ω

θ

= =

= =

= + +

= + + +

∑ ∑

∑ ∑ && &

4.7

where,mi is the mass of the ith link,Ii is the moment of inertia of the ith

link under the centre-of-mass system. 1 1 2, , x y θ are selected as the

generalized coordinate, let 1 1 2, , X x Y y θ= = Θ= . gil is the distance

between ( 1 1,i ix y− − ) and ( ,g gi ix y ). They can be written into:

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1 1 1 1

1 1 1 1

2 2 2

2 2 2

1 1 21

2

1

2

1

2

( ) cos

( )sin

cos

sin,

cos cos 3

sin sin 3

3

g g

g g

g g

g g

ig gi j j i i

j

ig gi j j i i

j

i

i jj

x X l l

y Y l l

x X l

y Y l

x X l l i

y Y l l i

i

θθ

θθ

θ ϕ θ

θ θ

θ θ

θ ϕ

=

=

=

⎧ = − −

= − −

= +

= += Θ − = Θ

⎨= + + ≥

= + + ≥

= Θ + ≥

⎪⎪⎪⎪⎪⎪⎪⎪

⎪⎪⎪⎪⎪⎪⎪⎪⎩

4.8

Rewrite the Lagrange’s function into ( , , )L L X Y= Θ :

( ) ( )( )( ) ( )

( ) ( ) ( )( )( )

2

1 1 1

2 2

2 2 1

2

1 1 1

2 22 2 2

1 ( - ) - sin -21 1sin -2 21 - - - cos -21 1- cos2 2

g

g

g

g

L m X l l

m X l I

m Y l l

m Y l I

ϕ ϕ

ϕ

ϕ ϕ

= + Θ Θ

+ + Θ Θ + Θ

+ Θ Θ

+ Θ Θ + Θ

&& &

& && &

&& &

& &

2

-1

3 2

2-1

3 2

2-1

3 2

1 cos cos2

1 sin sin2

12

N ig

i j j i ii j

N ig

i j j i ii j

N N

i i ji j

dm X l ldt

dm Y l ldt

dI Edt

θ θ

θ θ

ϕ

= =

= =

= =

⎡ ⎤⎛ ⎞+ + +⎢ ⎥⎜ ⎟

⎢ ⎥⎝ ⎠⎣ ⎦

⎡ ⎤⎛ ⎞+ + +⎢ ⎥⎜ ⎟

⎢ ⎥⎝ ⎠⎣ ⎦

⎡ ⎤⎛ ⎞+ Θ + +⎢ ⎥⎜ ⎟

⎢ ⎥⎝ ⎠⎣ ⎦

∑ ∑

∑ ∑

∑ ∑

4.9

thus the Lagrange's equations of the second kind are:

X

Y

d L LFdt X Xd L LFdt Y Y

d L LMdtΘ

∂ ∂⎧ = −⎪ ∂ ∂⎪ ∂ ∂⎪ = −⎨ ∂ ∂⎪

∂ ∂⎪ = −⎪ ∂Θ ∂Θ⎩

&

&

&

4.10

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where, XF , YF and MΘ are the components on X-axis and Y-axis of

the resultant of forces and the resultant moment on ( 1 1,x y ) respectively.

4.5. Fluid Modeling the Robot Fish

The fluid forces acting on the robot fish are decided by its

instantaneous movement. A fluid drag model is employed to analyse

the forces perpendicular to the surface of the swimming robot fish,

which has been used extensively in the case of the large Reynolds

number in the literature [79, 89, 96, 124, 125]. That is:

2sgn( )( )F v vμ ⊥ ⊥= − 4.11

where, 12

CSμ ρ= is the drag coefficient, ρ is the density of water, C is

shape coefficient and S is effective area. v ⊥ is the projection of the

velocity along the direction perpendicular to the surface.

The forces acting on the robot fish are divided to three

components: pressure on links, approach stream pressure and friction:

(1) The pressure on links: the fluid force on the robot fish’s ith link

when it swings:

2

sgn( )i i i i iF v v v vμ μ⊥ ⊥ ⊥ ⊥ ⊥ ⊥ ⊥= − = − 4.12

where, iF ⊥

is the pressure on ith link, iv⊥

is the projection of the

velocity of ith link along the perpendicular direction, and u⊥ is the

drag coefficient with C of flat plate type [9], and:

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sin cosf f

i ii i i

dx dyvdt dt

θ θ⊥ = − 4.13

where,

1 1 1 1

1 1 1 1

2 2 2

2 2 21

2

( )cos

( )sin

cos

sin

cos cos 3

f f

f f

f f

f f

if f

i j j i ij

x X l l

y Y l l

x X l

y Y l

x X l l i

θθ

θθ

θ θ−

=

⎧ = − −⎪

= − −⎪⎪ = +⎪⎨

= +⎪⎪⎪ = + + ≥⎪⎩

1

2

1

2

sin sin 3

3

if f

i j j i ij

N

i jj

y Y l l i

i

θ θ

θ ϕ

=

=

⎧ = + + ≥⎪⎪⎨⎪ = Θ + ≥⎪⎩

4.14

where, f

il is the length from ( 1 1,i ix y− − ) to ( ,f fi ix y ).

(2) The approach stream pressure: It is introduced because the

water pushes on the cross section of the robot fish when the robot fish

swims forward.

1 1 1F u v v= = = == − 4.15

where, 1 1 1cos sinv X Yθ θ= = +& & is the projection of the velocity of the first

link along the parallel direction, and u = is drag coefficient with the

type of bullet[110]. Considering the cross-sectional area of the second

link is much smaller than the first, the flow’s effect is reduced and 2F=

is ignored.

(3) The friction drag: There is friction drag acting on the surface

of the robot fish which is parallel to the body. It is often evaluated

empirically (30%-50% of the approach stream pressure). 50% is

selected because of the unsmooth surface of the robot fish.

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1 1 150%2f

uF F v v=

= = == = − 4.16

The composition of forces on the X-axis and Y-axis are:

( )1 11

cosN

xx i f

i

F F F F θ=

=

= + +∑

4.17

( )1 11

sinN

yy i f

i

F F F F θ=

=

= + +∑

4.18

The composition of moment act on the joint is:

1 1

( ) ( )N N

x f y fi i i i

i i

M F y Y F x XΘ= =

⎡ ⎤= − − + −⎣ ⎦∑ ∑

4.19

From Eq. 4.16-4.18 and 4.10 the differential equation group of

, , ,X Y tΘ can be obtained:

( )

( )

1 11

1 11

1 1

cos

sin

( ) ( )

Nx

X i fiN

yY i f

iN N

x f y fi i i i

i i

d L LF F F Fdt X Xd L LF F F Fdt Y Yd L LM F y Y F x Xdt

θ

θ

=

=

=

=

Θ= =

∂ ∂⎧ = − = + +⎪ ∂ ∂⎪∂ ∂⎪ = − = + +⎨ ∂ ∂⎪

⎪ ∂ ∂ ⎡ ⎤= − = − − + −⎪ ⎣ ⎦∂Θ ∂Θ⎩

∑ ∑

&

&

&

4.20

The equations can be solved by numerical method with boundary

conditions at initial time. The action of the robot fish depends on the

cooperation among all of the joint angles.

4.6. Kinematic Modeling Results

The experiments were implemented according to Eq. 3.1where

c1=0.05, c2=0.09 and k=0.5, in the pool of 4.0m×3.0m×0.75m. Figure

4:4 gives the simulation results of forces acting on the robot fish in

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forward motion with Amp =π / 4, Aturn =0, f = 10/7 Hz. The simulation

scalar velocity was stabilized on 0.179531 m/s (similar to the

experiment velocity of 0.18 m/s). Its direction deflected a little from

the original one because the component force in the X-axis direction

was asymmetric.

In next chapter, the force will be compared with the CFD

simualtion results.

5 10 15tHsL

-2

2

4

6

8FxHNL

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Figure 4:4: Simulation results of forces acting on the robot fish in forward

motion

4.7. Conclusion

In this chapter, the Kinematic Modeling of the robot fish was

5 10 15tHsL

-4

-2

2

FyHNL

5 10 15tHsL1

2

3

4

5

6

FHNL

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presented. The multi-joint robot fish was simplified as the link

structure. Basing on this typical series structure, the Lagrangian

method was introduced for analysis. On one hand, the Lagrangian

energy function for the robot fish in the freedom movement was

written according to the robot fish functional principle and the

geometry. On the other hand, the fluid forces of the robot fish were

simplified into three components: the link positive pressure, incident

flow resistance and friction resistance, which were calculated

according to the principles of hydromechanics. Finally, a kinematics -

mechanics combined equation for the robot fish was obtained by

uniting the generalized force and fluid force according to their

relationship in the Lagrange equation on which the real-time motion

can be solved.

The kinematic modeling simulation provided the real-time forces

for the forward swimming robot fish and was verified by experiment.

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5. Hydrodynamic Analysis of the Biomimetic Robot Fish & Application on the Haptic Robot Fish System

5.1. Introduction

Most existing control algorithms for robot fish are based on a

simplified propulsive model, which only provides a rough prediction of

the effect of hydrodynamics on robot fish. To obtain an accurate

prediction, it is necessary to conduct dynamic analysis of the

surrounding fluid by CFD [100].

This chapter presents a 3D CFD simulation for the biomimetic

robot fish. Fluent® and UDF are used to define the movement of the

robot fish. The Dynamic Mesh is used to mimic the fish swimming in

water. Hydrodynamic analysis produces significant information on

flow pattern, velocity and pressure fields to help readers understand the

internal information on the hydrodynamic properties of the robot fish.

This is also used to improve the design, remote control and flexibility

of the underwater robot fish. The 3D CFD simulation is investigated

for the robot fish prototype using Fluent® 6.3.26.

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5.2. Problem formulation

CFD simulation processing large amount data is time consuming.

The first target is the method of reducing the number of the mesh

nodes and elements created for the geometries. Another important

issue to be resolved is how to mimic the body motion of the robot fish.

The irregular profile of the robot fish brings difficulties into

generating the geometries and the mesh for its 3D CFD simulation.

The type and the number of the elements used in the simulation will

directly affect computation efficiency and accuracy.

The 3D flexible body deformation of the fish swimming in water

is so complex that all nodes need be controlled exactly to describe the

motion of the robot fish. The law of the robot fish motion should be

found to help researchers redefine and program in order to control

every node on the robot fish to mimic its real swimming motion.

5.3. 3D Hydrodynamic Model

5.3.1. Biomimetic Robot Fish and Pool Geometries

The 3D geometry and the meshes of the robot fish were generated

by Gambit (V2.3.16). In the current study, the effect of the connection

cable between the robot fish and the buoyage information relay was

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ignored to simplify the robot fish model.

The dimension of the robot fish is 0.62m×0.16m×0.08m (length ×

max high × max width). To allocate enough space for approach

accurate hydrodynamic properties, a pool was designed to be

9m×9m×4m. The pool walls were defined as moving walls and their

local velocities depend on the fluid velocity. The main currents were

backward flow generated by the locomotion of the fish tail so that the

robot fish was located at the centre of the vertical cross section of the

pool, while the distance between the fish head and the pool inlet was

1.53m.

5.3.2. Mesh Scheme

5.3.2.1. Requirements and Conditions of Mesh Scheme

In the last 30 years, CFD has achieved significant progress and is

considered to be very close to its maturing stage in the computation of

flows around airplanes at designed conditions. It also can solve the

simulation problems for geometrically complex and largely moving

and deforming bodies. The Dynamic-Mesh Method is an automatic

mesh generation method that controls the grid moves accompanied

with body movement and deformation. This method will be used to

control the nodes on the robot fish surface in the simulation which will

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conduct the effect of the robot fish motion. When the water around the

robot fish is squeezed and stretched, the hydrodynamic force can be

calculated.

However, the Dynamic Mesh method was used for the processing

of the couple between the robot fish changing shape and the water.

Tetrahedron mesh elements must be chosen in the concerned area. This

kind of element has more elements and less accurate calculation than

any other kinds of mesh elements. An elaborate planned mesh scheme

is needed made up of tetrahedron, and other kinds, of mesh elements. It

will be expatiated later.

5.3.2.2. Logical Division of Fluid Domain

As discussed above, tetrahedron mesh elements were only used

for the cube area (0.91m×0.7m×0.4m) close to the robot fish, while

Quant mesh elements as big as possible were used for other areas to

reduce the number of elements. The distance between the small cube

with tetrahedron elements and the inlet was 1.42 m. This meshing

scheme, with high qualified tetrahedron around the robot fish, would

give enough space to process meshing and approach a lower number of

meshes to reduce computational time.

On the other hand, hexahedral elements were selected to fill the

rest of the volume of the water, which could produce highly accurate

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calculation with smaller numbers of mesh elements than that of the

tetrahedron elements. The mesh grew at the rate of 1.5 ratio from the

cube around the robot fish to the walls of the pool.

5.3.2.3. Mesh Scheme Specific Implementation

The mesh sizes are determined based on the characteristics of

fluid dynamics of the water close to the fish:

Reynolds number,

5Re 1.1 10ULv

= = × 5.1

The thickness of the boundary,

14.64 0.00865( )Re

L mσ = × × =

5.2

where U=0.18 m/s (it is the experimental velocity of the robot fish)

L=0.62 m (the length of the robot fish)

v=1.01×10-6 m·kg·s (water viscosity)

To reach an accurate calculation of the forces acting on the fish

surface and to reduce the number of meshes, a boundary schema with a

growing rate of 1.4 ratio and 4 layers was applied for mashing the

hydrodynamic boundary of the robot fish. According to Eq. 5.2, the

size of the minimum grids adhered to the robot fish is 2 mm.

An effective mesh schedule was produced with the above settings,

which proved that logical division of the fluid domain works

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excellently in this project.

Finally, this simulation contained a total of 189683 nodes and

837773 elements for the fluid domain. Figure 5:1 & Figure 5:2 show

the mesh distribution in the fluid area and a close view around the fish.

Figure 5:1: Mesh of the Biomimetic Robot Fish

Figure 5:2: Mesh scheme for the region close to Robot Fish

5.3.3. Mathematic Description of the Robot Fish Locomotion

In this section, how to mimic the robot fish locomotion in CFD

simulation will be introduced.

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5.3.3.1. Conditions of 3D Mathematic Description

Figure 5:3 and Figure 5:4 respectively describe the 3D geometric

outline of the robot fish and the parameters of its tail.

Figure 5:3: The outline of the Robot Fish

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Figure 5:4: Parameters of the Robot Fish Tail (Unit: mm)

Every point on the robot fish tail can be defined by mathematical

equations easily when it is in a natural relaxed status which will be the

initial status of the robot fish. The motion law of the robot fish tail

centerline is described by Eq. 3.1. But the 3D fish tail is quite flexible,

which creates a problem in controlling the movement of every point on

the surface of robot fish tail to mimic the action of the robot fish. If the

mathematical description of the robot locomotion can be found, UDF

can be used to realize this aim and the DEFINE macro of

DEFINE_GRID_MOTION[126] will work well in the control of every

slight motion of the robot fish tail.

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5.3.3.2. Robot Fish Tail Waving Description

In describing the position of every node on the robot fish surface,

the most important thing is the relationship between it and its

neighboring nodes. The node motion rules are specified as follows

according to the characteristics of the swimming robot fish (refer to

Figure 5:5):

(1) A node always tries to keep the same projection position on

the centerline and the same distance to the centerline.

(2) A node cannot change the location sequence and will keep a

certain distance with its neighbor nodes.

(3) Every node always keeps its original horizontal position.

(4) The centerline of the robot fish is flexible but not elastic. The

surface of the robot fish tail is unlimitedly flexible.

Figure 5:5: Node Movement

According the above assumptions for node movement, one can

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program and control the position of every node on the robot fish tail

using UDF.

5.3.3.3. Implement of the Robot Fish Tail Movement with

Fluent®

As discussed above, the oscillation of the fish tail (moving part-1)

and the caudal fin (moving part-2) as shown in Figure 5:6, are complex

and flexible, and the DEFINE macro DEFINE_GRID_MOTION was

chosen to describe the movement of the fish tail and the caudal fin. A

program was developed based on Eq. 3.1 and c1=0.05, c2=0.09 and

k=0.5.

Figure 5:6: Meshes on Robot Fish Body

To couple accurately the posture of the fish body in time, the

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performance of the dynamic mesh is quite important in the simulation.

Smoothing and Remeshing mesh method was used here. The relative

parameters used are listed in Table 5.1.

A commercial CFD code, Fluent® 6.3.26 with a standard k–

epsilon turbulent model, and standard wall functions, were used in all

simulations. Table 5.1: Parameters for dynamic mesh

Mesh Methods

Parameters Setting

Items Setting

Smoothing

Spring Constant Factor 0.05

Boundary Node Relaxation 0.8

Convergence Tolerance 1e-05

Number of Iterations 100

Remeshing

Minimum Length Scale (m) 0.00072372

Maximum Length Scale (m) 0.0008

Maximum Cell Skewness 0.8

Maximum Face Skewness 0.79

Size Rmesh Interval 1

Size Function Resolution 1

Size Function Variation 48.94077

Size Function Rate 0.7

In this section, the 3D body swing of the robot fish was

successfully imitated using UDF, which is the solid foundation of the

fluent simulation. The rules of the nodes motion on the robot fish tail

were prompted. This is simple and can be used in any kind of model of

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robot fish movement.

5.4. Hydrodynamic Analysis

In the simulations, the robot fish oscillates its tail and caudal fin at

T = 0.7s (swinging period). The pressure distribution will be analysed

on the horizontal cross section of the pool at the middle position

(M-view), as in Figure 5:7

Figure 5:7: M-View

5.4.1. Design Properties of the Robot Fish

1. Velocity effect on the robot fish. Figure 5:8 shows the velocity

vectors on the robot fish surface when it stops in steady flow,

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coming from its head to tail at velocity of 0.1 m/s. The

conclusion can be drawn easily that the robot fish’s shape is

excellent with no disorder flow on the fish surface and that it

is suitable for swimming in water.

Figure 5:8: Velocity Vectors on the Robot Fish Surface

2. The Pathline of the Robot Fish. Figure 5:9 (the same condition

with item 1) shows flow velocity profiles along the robot fish

surface. It indicates that the surface of the robot fish is

clipper-built and will get high performance in water.

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Figure 5:9: The Pathlines of the Robot Fish

3. Hydrodynamic analysis – pressure. Figure 5:10 (the same

condition with the above item 1) manifests that there are two

kinds of point: one is stagnation point, a normal point, where

the robot fish meets the coming flow; and the other is shoulder

point need to be enhanced in next outline design.

Figure 5:10: Hydrodynamic analysis – pressure

The above results illustrate that the outline design of the robot fish

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is quite good. In the next step, we will enter the hydrodynamic analysis

of the robot fish.

5.4.2. Pressure Distribution around the Swimming Robot

Fish

Figure 5:11: Pressure Contours of the M-view at 4 Locomotion Times (N×m–2) (a) approaching the left maximal rotation position (t = 0.1 s); (b) intermedial position

during oscillating motion (t = 0.25 s); (c) going on intermedial position during oscillating motion (t = 0.4 s); (d) approaching right maximal rotation position (t =0.55

s). (It is supposed that a robot fish locomotion period begin from the position t=0 according the Equation 1)

Figure 5:11 shows the pressure contours at four locomotion times

(“The right” / “the left” means the side of the right / left hand when one

(a) 0.1s (b) 0.25s

(c) 0.4s (d) 0.55s

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stands on the point of the robot fish’s inertia centre and faces to the

fish head. ):

At t = 0.1s (Figure 5:11(a)), the fish tail and the caudal fin are

swinging from the right to the left and almost reach the

maximal displacement. On the left side of the fish tail and the

caudal fin, a bigger positive pressure is generated and a wider

distribution than the right side can be found. Especially, the

positive pressure focuses mostly on the rear of the tail, which

generates forces pointing to the right-front of the fish. These

positive pressures are generated as the water is extruded by the

movement of the fish tail and the caudal fin. Also, they grow

bigger along the direction from the fish tail to the caudal fin

due to the growing up amplitudes of the fish tail and the

caudal fin oscillating. This also implies that a tip vortex can be

generated near the edge of the robot fish caudal fin and

considerable fluid is pushed into the downstream region on the

left side of the caudal fin.

At t = 0.25s (Figure 5:11(b)), the robot fish body and the

caudal fin are already swinging back from the left to right.

This action pushes the water away, so a positive pressure is

exerted and widely distributes on the right side of the fish tail

and the caudal fin. Immediately after the anticlockwise stroke

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began, which is a change of the fish tail swinging direction,

one observes a small positive pressure distribution on the right

side of the caudal fin and a negative pressure distribution on

its left side. This shows the generation of the thrust. The

direction of the thrust is left-front according the angle of the

robot fish body posture.

At t = 0.4s (Figure 5:11(c)), the fish tail and the caudal fin

keep swinging from the left to the right. The positive pressure

grows and turns to the left side of the robot fish. On the other

side of the robot fish body, the negative pressure decreased.

This demonstrates that the robot fish achieves a larger

right-front direction thrust.

At t = 0.55s (Figure 5:11(d)), the fish tail and the caudal fin

keep on swinging from the left to the right and its body

reaches almost the most flexible position. The positive

pressure grows up quickly and distributes on both the left side

of the middle tail and the right side of the caudal fin. On the

contrary, a negative pressure distributes on the right side of the

tail. At this point, the robot fish achieves the largest forward

direction thrust during the whole period.

After the period described above, the fish tail and the caudal

fin continue to swing for the next half period.

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According to the above analysis, the resulting forces that the robot

fish acquired by periodically oscillating its tail and caudal fin can be

divided into two types, the fluctuant thrust at forward direction and the

drag at left-right direction.

5.4.3. Velocity Distribution around the Swimming Robot

Fish

The velocity contours of the robot fish at critical instants are

shown in Figure 5:12 during the oscillation, using the same instants

and views as the ones for pressure contours analysis.

At t = 0.1s (Figure 5:12(a)), a counter-rotating vortex is

observed. This vortex is shed from the distal edge (especially

the tip edge of the tail fin) on the robot fish. The shedding of

vortex may be one of the main effects on the pressure

distribution at the robot fish surface mentioned in the pressure

analysis.

At t = 0.25s (Figure 5:12(b)), a thin clockwise vortex sheds

from the tip of the caudal fin at the beginning of the fish tail

and the caudal fin reverse motion.

At t = 0.4s (Figure 5:12(c)), one observes a clockwise vortex

at the right middle side of the fish tail. The shedding of this

vortex into the wake leads to a momentary increase in the

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thrust.

At t = 0.55s (Figure 5:12(d)), a large anticlockwise vortex

sheds at the left middle side of the fish tail. Two clockwise

vortexes are shed at the right side of the upper tail and the

caudal fin. The shedding of these vortexes into the wake leads

to larger increase in the thrust than the one at t = 0.4s.

After the periods described above, the robot fish will endure the

next similar half period.

Figure 5:12: Velocity Distribution

(a) 0.1s (b) 0.25s

(b) 0.4s (d) 0.55s

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5.4.4. Forces of the Swimming Robot Fish

The robot fish oscillates its tail and caudal fin at T = 0.7s

(swinging period). After ten swinging periods, the inlet velocity

becomes stable and is about 0.18m/s, which is the same as the

experiments. This says the simulation is valid. Figure 5:13 shows the

forces exerted on the robot fish along with X and Z axis directions. In

the X-axis direction, the fish suffers a much bigger force than in the

Z-axis direction. The composite of the forces in the X axis direction are

almost zero generated by the swing movement of the fish tail and the

caudal fin. It will be counteracted by the force arisen from the

movement of inside motors. The force in the Z-axis direction is always

positive. This is caused by the movement of the fish tail and the tail fin.

The robot fish will be driven by the force in the Z-axis direction.

Moreover, the force in the Z-axis direction is about 3N, which is

coincident with the results from the Kinematic Modeling simulation

(referring Figure 4:4. Please note: Z-axis is equivalent to X-axis in the

Kinematic Modeling simulation. X-axis is equivalent to Y-axis in the

Kinematic Modeling simulation)

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Figure 5:13: Forces in X and Z Directions

5.5. Haptic Application on the Robot Fish

Haptic application has been a popular development in kinds of

areas in the field of robotics. To easily control the robot fish movement,

let operators feel the force and study the hydrodynamic properties of

the robot fish when it is swimming in water, a 3D interactive

visualization haptic robot fish system with haptic feedback was

designed in this section. The model was manipulated to visualize the

effects of force feedback using the most advanced industry haptic

device – a SensAble Technologies PHANTOM Omni – to provide

continual force feedback for studying and controlling the movements

of the robot fish.

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5.5.1. Issues to Be Solved

Several problems in designing the haptic robot fish system are

considered.

(1) Haptic interfaces are used to provide touch feedback to a user

from a virtual (or remote) environment. The haptic device

needs to be driven in real-time to let the user feel the force the

robot fish gets in water. Applying force sensors to the robot

fish is definitely the most direct method to reach this aim.

However, any force sensors are not used in current haptic

robot fish system. The haptic framework of the robot fish will

be set up using a preset database. It even will calculate the

force in real-time instead of force data from sensors. These

will help the setting up of the virtual force feedback quickly

and easily for the haptic robot fish system in the initially

period of this research project. It will also guide on designing

the real force sensors applied on the robot fish.

(2) How to get the position of the robot fish and display it on the

PC display port? A good choice is to employ a camera and use

the digital image processing to get the position and posture of

the robot fish. Another choice is using the pre-calculated

results from simulations to estimate the position which will

also help on controlling the robot fish.

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(3) How to use the haptic controller (Omni phantom) to send

control commands to the robot fish? One method is using

pre-designed commands. Another method is to use the haptic

device to measure the intention of the operator, driving the

robot fish to go forward, turn or dive at some level speed, then

translate it into commands and send to the robot fish.

5.5.2. Haptic Robot Fish System Framework

The proposed haptic robot fish system includes two main steps:

First, the position and posture of the robot fish is achieved for the

virtual display, and the force the robot fish gets in water has been

obtained for the haptic device force feedback; Second, the control

commands of the operator can be defined according to the real-time

status of the current task implementation and transferred to the robot

fish.

The haptic robot fish system employs three parts to achieve the

two procedures: First is a display used to show 3D virtual robot fish;

the second is a computer to fetch the information from the robot fish

from pre-set database or calculate it in real time and communicate with

both the robot fish and the haptic device; thirdly is a haptic interface

transferring the information of the control commands and force

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feedback.

Figure 5:14: The Framework of Haptic Robot Fish System

As shown in Figure 5:14, the haptic robot fish system integrates

visual and haptic information to give assistive force feedback through a

haptic controller (Omni Phantom) to the user. A pre-set database

provides force feedback to help the user feel the force that the robot

fish gets in water and the estimated position and posture information of

the robot fish to help display the robot fish in the 3D virtual vision. A

camera is mounted to monitor the whole pool to provide information of

the position. With on-line visual feedback, the fishes’ position and

orientation, the speed of straight swimming and turning performance

can be measured, posture of the robot fish for the 3D virtual display

can be shown, and also help the user to decide the intended path to the

selected target. Furthermore, this real-time system is versatile. The

haptic component can be used for rehabilitation purposes in cases

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where hydrodynamic property analysis can be shown to give the

operator professional information about the robot fish, for example,

pressure distribution at specified cross sections. It can also be used for

teleoperation with force feedback in either the supervisory or automatic

modes. The former one provides a very indirect method of interaction

with the preset hydrodynamic analysis database.

Figure 5:15: Virtual Display and Haptic Operating

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Figure 5:16: Command in Virtual Interface

The proposed haptic robot fish system (refer to Figure 5:15 &

Figure 5:16, the fish model used for the virtual interface is a fungible

one) employed Omni Phantom haptic device as the hardware platform.

The system was coded by Visual C++ in Windows XP. The display

design was developed by OpenGL. Force interaction was designed by

calling the Omega 3DOF own modules to communicate with the haptic

robot fish and upper console.

5.5.3. 3D Virtual Display Design

A 3D virtual graphic user interface used in the haptic robot fish

system brings the following advantages:

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(1) The interface enables the user to create the special virtual

robot fish world. For example, the user can decorate the

aquatic environment with static objects and seaweeds, and can

specify the number, type, size, initial positions as well as

individual habits (i.e. innate behavioral characteristics) of the

robot fish.

(2) It allows the user to do experiments with the physical

properties of the robot fish, the hydrodynamic medium and the

mental parameters of the robot fish.

(3) It controls the display of a binocular fish-view from the “eyes”

of the robot fish.

In this thesis, the simulation was made in a simple “environment”,

quiet water area without any obstacle in order to simplify the current

study.

5.5.4. Haptic Robot Fish System Force Feedback Method

The simulation results were used to build up the database for the

haptic robot fish system. The upper console obtains the real-time

movement status of the robot fish and looks up the database to fetch

the information about the simulation results for the haptic interaction

with the operator.

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5.5.4.1. Preset Database Based on Computational Fluid

Dynamics (CFD) Simulation Results

The preset database of the haptic robot fish system includes two

kinds of data:

(1) Composite and component forces along different axes or

based on different effects can be provided according to the

initial conditions, swimming speed, direction and swinging

frequency of the robot fish. They were mapped to the haptic

space using direct force mapping. These force data can be set

up according to the haptic display rendering requirement and

can be rendered stably.

(2) The velocity, pressure field distribution and any other further

information of the robot fish’s hydrodynamic properties can be

provided by CFD simulation.

5.5.4.2. Possibility of Real-time Calculation Based on

Kinematic Modeling

The force rendering frequency of haptic display is required to be

over 1 KHz. Kinematic modeling is performed for different swimming

postures of the robot fish and analytic solutions were calculated by

software Mathematics®, which has strong ability in symbolic

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computation. As soon as the robot fish’s movement parameters are set,

the calculated force feedback for haptic interacting is satisfies the

haptic rendering requirement.

5.5.4.3. Further Haptic Robot Fish System Design

Further improvement is to apply force sensors into this haptic

robot fish system to implement multi-dimensional force measurement

and hopefully provide a more precise sensation of reality, a step

forward toward the development of a haptic virtual environment. The

force sensors can be applied on the robot fish surface to provide the

force feedback to the haptic robot fish system to let the operator feel

the force of the robot fish directly.

5.6. Underwater Experiments

Experiments are conducted in a pool of 4.0m×3.0m×0.75m.

Figure 5:17 describes a turning process implemented by adding a

deflection to the tail in the experiment pool. This shows the feasibility

of the biomimetic robot fish designed in the present work.

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(a) (b)

(c) (d)

Figure 5:17: The Image Sequence of the Robot Fish Turning

Table 5.2: Oscillating frequency (Hz) versus Speed (m/s) of straight swimming Frequency 0.5 0.67 0.8 1 1.43 2

Speed 0.09 0.12 0.13 0.15 0.18 0.26

Table 5.2 contains the test results of the oscillating frequency and

the straight swimming speed. It shows a general tendency that the

swimming speed increases with the oscillating frequency. The speed

cannot be infinitely expanded since the servomotors can hardly follow

sufficiently high speeds under high oscillating frequency condition.

It should be noticed, when the robot fish’s tail swinging frequency

is 10/7 Hz (1.43 Hz), its swimming forward velocity was about 0.18

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m/s. This experimental result is consistent with the simulation results:

• The Kinematic Modeling indicates that the simulation

scalar velocity was stabilized on 0.179531 m/s (similar to

0.18 m/s ) when the robot fish is in forward motion with

Amp =π / 4, Aturn =0, f = 10/7 Hz, (refer to sections 4.6).

• In the CFD simulation, the robot fish oscillates its tail and

caudal fin at T = 0.7s (swinging period). After ten swinging

periods, the inlet velocity becomes stable and is about

0.18m/s too, which illustrates the simulation is valid (refer

to section 5.4.4).

5.7. Conclusion

In this chapter, a computational fluid dynamic model was built for

a biomimetic robot fish. The hydrodynamic properties, such as the

exerted pressure and the force on the fish, have been obtained. They

explained how the fish oscillated the tail and the caudal fin to push

water away behind it and get the thrust pushing it forward.

The CFD simulations provided the information of the flow of

water around the robot fish and the pressure distribution. This will be

used for the optimization and improvement of the design and

fabrication of robot fish. It also provided more complex fluid flow

characteristics for the research and development of robot fish used in

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different external situations.

A new interactive haptic robot fish system with force feedback for

3D hydrodynamic analysis of the robot fish was also proposed in this

chapter. The haptic robot fish system supports users to understand the

hydrodynamic properties around the robot fish more deeply than other

common visualization systems based only on the graphic visualization

of hydrodynamic analysis. By attaching a haptic interface to the system,

a fully interactive haptic robot fish system in 3D space was developed

for interactive visualization of moving objects inside the display

domain. Hence, one cannot only observe the field distribution maps,

such as velocity and pressure field distributions, but also interactively

perceive the forces at the same time, interactively, in real time. This

system would be applicable for educational and design purposes in

robot fish research.

Some experiments were carried out upon the biomimetic robot

fish, and the results demonstrated the performance of the mechanical

structure and control system of the biomimetic robot fish. The

experiments also verified the simulation results.

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6. Analysis and Discussion on Kinematic Modeling and Computational Fluid Dynamics (CFD) Hydrodynamic Simulation

6.1. Introduction

Kinematic modeling and computational fluid dynamics analysis

have their own significant features. This section will compare their

features and identify their contribution to the haptic robot fish systems.

6.2. Distinguishing Features of Kinematic Modeling

The kinematic modeling used a typical series structure for the

robot fish simulation. On one hand, the Lagrangian energy function for

simplified multi-links structures in free movement was written

according to the robot fish functional principle and the geometry. On

the other hand, the fluid forces on the robot fish were calculated

according to the principles of hydromechanics. Then, the kinematic

equations, combined with mechanics for the robot fish, were obtained

by uniting the generalized forces and fluid forces according their

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relationship in the Lagrange equation. The components of the resultant

forces in X-axis and Y-axis and the resultant moment of the robot fish

can be calculated according Eq. 4.10. When the boundary conditions at

initial time are set, instantaneous robot fish motion data can be

obtained by solving the equations using numerical method.

This is a quite easy and direct method to look for the movement

data of the whole robot fish, from which the first-hand data can be

gained in order to control robot fish locomotion. It will help the

operators to control robot fish movement on line or make a route

planning off line. The energy consumption for performing the task can

also be estimated via this simulation, so the operators can get guidance

about the implementation strategy.

In summary, the kinematic modeling is a good macroscopic tool

to help the researchers study and control robot fish.

6.3. Distinguishing Feature of Computational Fluid

Dynamics (CFD) Analysis

Compared to the macroscopic kinematic modeling, CFD analysis

can give researchers more detailed information of the robot fish on

both macroscopic and microscopic aspects.

In the macroscopic aspect:

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(1) The forces on the whole robot fish can be calculated.

(2) The forces acting on any special parts of the robot fish can be

calculated.

(3) Different fluid forces can be calculated separately, such as

thrust, lift and drag.

(4) The pressure and velocity distribution on or around the robot

fish can be analysed.

In the microscopic aspect:

(1) The pressure and velocity on or around every point of the

robot fish can be analysed.

(2) The forces acing on every point of the robot fish can be

calculated.

6.4. Comparison between Kinematic Modeling and

Computational Fluid Dynamics (CFD) Hydrodynamic

Analysis

The kinematic modeling and CFD analysis have their own

significant advantages and disadvantages in the simulation of robot fish

swimming as listed in Table 6.1. Some special properties are compared

in Table 6.2

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Table 6.1: Comparison between the kinematic modeling and CFD analysis

kinematic

modeling

CFD

analysis

Note

Software Mathematics® Fluent®, Gambit®

Modeling build up

Simplified the robot fish structure, then united the generalized forces and fluid forces according their relationship in the Lagrange equation

Generated 3D meshes for the robot fish; mimic the robot fish locomotion using UDF, then performed the simulation with Fluent®

Calculation accuracy

General accuracy Greater accuracy and fidelity

Duration Simulation period

After the modeling being built up, results for new parameter simulation can be produced quickly, generally within several minutes or hours.

Long period for modeling built up and debugging many parameters. The calculation is time-consuming, several days, even several weeks.

Simulation data

Provides macroscopic data of the swimming robot fish

Provide both macroscopic and microscopic data of the swimming robot fish

Refer to section 7.2 & 7.3

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Table 6.2: Comparison in special properties between the kinematic modeling and CFD analysis

Kinematic modeling CFD analysis

Body shape analysis

No, it cannot provide body shape analysis.

Yes, kinds of parameters can bring some ideas about the Quarlity of the robot fish shape.

Force the fish gets in water

Similar to CFD simulation results, but at low accuracy.

2 4 6 8 10tHsL

-0.8

-0.6

-0.4

-0.2

0.2

0.4

0.6FxHNL

2 4 6 8 10tHsL

-2.0

-1.5

-1.0

-0.5

0.5

1.0

Fy HNL

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Velocity Can be calculated for the whole fish and a specific section, but cannot directly displayed in graphic detail

The velocity at any surface of the robot fish can be calculated and displayed easily.

Pressure Can be calculated for the whole or and a specific section, but no directly graphic display

The pressure of every point at any surface of the robot fish can be calculated and displayed easily.

6.5. Conclusion

Both kinematic modeling and CFD analysis were used for the

haptic robot fish system in different ways to exert their respective

advantages.

The kinematic modeling results were used for the whole fish

status analysis, for example, the composite forces and moments, the

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components of forces and moments on the swimming robot fish will

help researchers study the efficiency of the robot fish locomotion, the

relationship among velocity and amplitude, and frequency of the robot

fish swinging. All of them will provide abundant data for assigning

robot fish tasks. Another usage of this simulation is attributed to its

quick solution. It will be applied for on line calculation; this will

contribute to the real time control of robot fish in the future.

CFD analysis results were used to build up the database of the

haptic robot fish system for force feedback. It can provide abundant

information and give the operators direct tactile experience to study the

swimming robot fish. CFD hydrodynamic analysis can also help

researchers study the robot fish in detail, for example, pressure and

velocity distribution on or around the robot fish, which cannot be

obtained through physical experiences. This is quite important in the

design and improvement of the robot fish.

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7. Conclusions and Future Works

7.1. Conclusions

This thesis demonstrated a medium size (62 centimetres in length)

biomimetic robot fish design based on the carangiform prototype

(shown in Figure 3:1). It had the most functions in this dimension of

robot fish and was made up of a sensing unit, a control unit, a

communication unit, an actuation unit, a support frame and other

accessories. A biomimetic motion library conception was brought

forward to help researchers easily control robot fish to realize 3D

controllable free swimming in water. The robot fish can detect

obstacles through the sensing unit and can swim autonomously. It also

can communicate with an upper console, send out the visual and other

information and receive operation commands. These functions make it

possible to the robot fish system complete special tasks with, or

without, real-time commands from the upper console.

Two kinds of modeling, the kinematic modeling and CFD

simulation were carried out to study the robot fish characteristics, the

foundation of the haptic robot fish system. On one side, the kinematic

modeling was built according to the relationship between the

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generalized force in Lagrange's equation of the second kind and the

fluid force based on a simplified geometric model of the robot fish. It

provided a simple and time-efficient way to calculate the force on the

swimming robot fish. The swimming forward motion of the robot fish

was simulated, which has been verified by experiment. On the other

side, the 3D CFD simulation of the biomimetic robot fish was

investigated using Fluent® version 6.3.26. The UDF was used to define

the movement of the robot fish and the Dynamic Mesh contributed to

the simulation too. The hydrodynamic analysis produced detail

information not only the forces exerted on the robot fish, but also the

flow pattern, velocity and pressure fields, providing researchers with

an insightful view into the hydrodynamic properties of the robot fish.

This also can assist in improving the design, remote control and

flexibility of the underwater robot fish. The results of the two kinds of

simulation were respectively used for the analysis of the whole fish

status and the buildup of the haptic robot fish system database

according to their different simulation features.

A haptic robot fish system was innovated with a new interactive

force feedback using direct force mapping. It supports users in

understanding the hydrodynamic properties around the robot fish more

deeply than in other common visualization systems based only on

graphical visualization of hydrodynamic analysis. One can feel the

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force imposed on the robot fish in water and also can observe the field

distribution maps, such as velocity and pressure on need for

hydrodynamic analysis. This system would be applicable for

educational and design purposes in robot fish research.

7.2. Future Works

The haptic robot fish system is innovative in robot fish

development and many things still need to be done. Future activities

will aim to improve and enhance its performance and also to make the

haptic feedback directly come from test results by adding force sensors.

Here are some:

(1) In the present system, the robot fish communicates with the

upper console on shore via a cable that is connected to a

Buoyage Information Relay. The relay generates drag force

which greatly reduces the efficiency of the robot fish

movement. Under water communication is difficult due to the

factors such as multi-path propagation, time variations of the

channel, small available bandwidth and strong signal

attenuation, especially over long range. In underwater

communication there are low data rates compared to terrestrial

communication, since underwater communication uses

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acoustic waves instead of electromagnetic waves. In future,

underwater acoustic communication will be a good choice for

the robot fish communicating with the outside.

(2) The diving ability of the robot fish is limited by its diving

method and the materials of its outer shell. The robot fish must

currently dive when it is swimming. It was realized using a

barycenter-adjustor to change the robot fish posture to get a

pitch swim route. The shape of the robot fish changes in a way

when it swims in water at different depths, which brings many

difficulties in controlling its locomotion. In future, some

special mechanical structures will be added to help the robot

fish obtain an easier diving method. New materials will be

applied to the robot fish outer shell, which should be soft but

still be able to resist the unwanted deformation coming from

water pressure.

(3) To build a true haptic robot fish system, some force sensors

will be applied on the robot fish body surface in the future.

Then the force information can be obtained from the real-time

measurement of the force sensors. This will help researchers

build more intellectualized robot fish like real fish, for example,

autonomously keeping away from underwater vortexes

measured and judged by its own sensors.

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(4) Both the kinematic modeling and CFD hydrodynamic

analysis should be improved to enhance the simulation

accuracy. More accurate and realistic numerical simulations

should be investigated for the robot fish when it is swimming

in different kinds of modes, such as turning and diving, and in

different water flows, such as downstream, in adverse currents,

turbulence or other complex stream currents. Those may

contribute to a better understanding and modeling of all the

sophisticated solutions in a near future.

(5) The simulation force data were mapped to the haptic space via

direct force mapping method. This will be improved later to

get better haptic interaction results.

There is a long way to go in building a real-fish robot and which

give operators good tactile interaction with the robot fish. But nature

gives researchers some revelation which will help them keep going

with it.

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References

1. How much water is there on, in, and above the Earth?

08-Feb-2011; Available from:

http://ga.water.usgs.gov/edu/earthhowmuch.html.

2. Kirby, G. Navies in Transition: A History of the Torpedo; The

Early Days. Originally published in the Journal of the Royal Navy

Scientific Service [cited 27 1]; Available from:

http://www.btinternet.com/~philipr/torps.htm.

3. uboat.net. Torpedo personnel.

http://www.uboat.net/men/crew/torpedo.htm [JPG] [cited 450 ×

302 - 20k; Available from:

www.uboat.net/men/crew/images/torpedo_3.jpg.

4. Alt, C.v., Autonomous Underwater Vehicles. 2003: p. 5.

5. Ewart, T.E., Observations from Straight Line Isobaric Runs of

SPURV, in Joint Oceanography Assembly. 1976.

6. Endicott, D.L., Khul, G. R., The Fast Area Search System. 1992.

7. J. Bellingham, C.G., T. R. Consi, C. Chryssostomidis, A Small

Long Range Vehicle for Deep Ocean Exploration, in Proceedings

of the International Offshore and Polar Engineering Conference.

1992: San Francisco. p. 151–159.

Page 147: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

144

8. Curtin, T.B., Bellingham, J. G., Catapovic, J., and Webb, D.,

Autonomous oceanographic sampling networks. Oceanographics,

1993. 6(3): p. 86-93.

9. Autonomous Benthic Explorer (ABE). Available from:

http://oceanexplorer.noaa.gov/technology/subs/abe/abe.html.

10. Ferguson, J.S., The Theseus autonomous underwater vehicle. Two

successful missions, in Underwater Technology, 1998. Proceedings

of the 1998 International Symposium on. 1998. p. 109-114.

11. von Alt, C., et al., Remote environmental measuring units, in

Autonomous Underwater Vehicle Technology, 1994. AUV '94.,

Proceedings of the 1994 Symposium on. 1994. p. 13-19.

12. Curv III CABLE-CONTROLLED UNDERWATER RECOVERY

VEHICLE. Available from:

http://www.ssedmundfitzgerald.com/casualtyreport.html.

13. A Royal Navy ROV (Cutlet) first used in the 50s to retrieve practice

torpedoes and mines. [image/jpeg]; Available from:

http://commons.wikimedia.org/wiki/File:Cutletrov.jpg.

14. Bowen, A.D., et al., Field trials of the Nereus hybrid underwater

robotic vehicle in the challenger deep of the Mariana Trench, in

OCEANS 2009, MTS/IEEE Biloxi - Marine Technology for Our

Future: Global and Local Challenges. 2009. p. 1-10.

Page 148: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

145

15. Robot sub reaches deepest ocean. 3,Jun, 2009; Available from:

http://www.ok4me2.net/2009/06/03/robot-sub-reaches-deepest-oce

an/.

16. Colgate, J.E. and K.M. Lynch, Mechanics and control of

swimming: a review. Oceanic Engineering, IEEE Journal of, 2004.

29(3): p. 660-673.

17. Sfakiotakis, M., D.M. Lane, and J.B.C. Davies, Review of fish

swimming modes for aquatic locomotion. Oceanic Engineering,

IEEE Journal of, 1999. 24(2): p. 237-252.

18. Triantafyllou, M.S., Triantafyllou, George S. , An efficient

swimming machine. Scientific American, 1995. 272(3): p. 64-70

19. Iijima, D., et al., Obstacle avoidance learning for a multi-agent

linked robot in the real world, in Robotics and Automation, 2001.

Proceedings 2001 ICRA. IEEE International Conference on. 2001.

p. 523-528 vol.1.

20. Barrett, D.S.T., M.S.; Yue, D.K.P.; Grosenbaugh, M.A.; Wolfgang,

M.J., Drag reduction in fish-like locomotion. Fluid Mechanics,

1999. 392: p. 183-212.

21. RoboTuna. Available from:

http://web.mit.edu/towtank/www/Tuna/tuna.html.

22. Tank, M.T. RoboPike Photos. Available from:

http://web.mit.edu/towtank/www/Pike/photos.html.

Page 149: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

146

23. Guo, S., et al., A fish microrobot using ICPF actuator, in Advanced

Motion Control, 1998. AMC '98-Coimbra., 1998 5th International

Workshop on. 1998. p. 592-597.

24. Shuxiang, G., et al., Development of underwater microrobot using

ICPF actuator, in Robotics and Automation, 1998. Proceedings.

1998 IEEE International Conference on. 1998. p. 1829-1834.

25. RobotBooks. Available from:

http://www.robotbooks.com/coelecanth-robot.htm.

26. Ayers, J., C. Wilbur, and C. Olcott, Lamprey Robots, in

International Symposium on Aqua Biomechanisms, T. Wu and N.

Kato, Editors. 2000.

27. Crespi, A., et al., Swimming and Crawling with an Amphibious

Snake Robot, in Robotics and Automation, 2005. ICRA 2005.

Proceedings of the 2005 IEEE International Conference on. 2005.

p. 3024-3028.

28. Crespi, A., et al., AmphiBot I: an amphibious snake-like robot.

Robotics and Autonomous Systems, 2005. 50(4): p. 163-175.

29. Willy, A. and K.H. Low, Development and initial experiment of

modular undulating fin for untethered biorobotic AUVs, in

Robotics and Biomimetics (ROBIO). 2005 IEEE International

Conference on. 2005. p. 45-50.

Page 150: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

147

30. Low, K.H. and A. Willy, Biomimetic motion planning of an

undulating robotic fish fin. Journal of Vibration and Control, 2006.

12(12): p. 1337(23).

31. Low, K.H., Locomotion Consideration and Implementation of

Robotic Fish with Modular Undulating Fins: Analysis and

Experimental Study, in Intelligent Robots and Systems, 2006

IEEE/RSJ International Conference on. 2006. p. 2424-2429.

32. Liu J., C.Z., Chen W., Wang L., A new type of under water turbine

imitating fish-fin for under water robot. Robot, 2000. 22(5): p.

427-432.

33. Xie H., Z.D., Shen L., Control System Design and Realization of

Bionic Underwater Vehicle Propelled by the Long Flexible Fin

Undulation. Journal of Control & Automation, 2006. 22(8-2): p.

218-221.

34. Beijing Information Net. Available from:

http://www.ctibj.com.cn/assembly/action/browsePage.do?channelI

D=1112148652630&contentID=1116421493073.

35. Yu, J., S. Wang, and M. Tan, A simplified propulsive model of

bio-mimetic robot fish and its realization. Robotica, 2005. 23(01):

p. 101-107.

36. Erkui, C., Research on control problems of biotic robot fish. 2003,

China University of Mining and technology. p. 104.

Page 151: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

148

37. Junzhi Yu , E.C., Shuo Wang, Min Tan, Research evolution and

analysis of biomimetic robot fish. CONTROL THEORY &

APPLICATIONS, 2003. 20(4).

38. shang, H., Research on Sensor-based Intelligent Control of

Biomimetic Robot Fish, in Institute of Automation, Chinese

Academy of Sciences. 2005: Beijing. p. 102.

39. Zhizhong Shen , Z.C., Min Tan, Shuo Wang Control of obstacle

avoidance of biomimetic robot fish based on reinforcement

learning. CHINESE HIGH TECHNOLOGY LETTERS, 2006.

16(12).

40. LIU Jun kao, C.Z.l., CHEN Wei shan, WANG Li gang, A new type

of underwater turbine imitating fish-fin for underwater robot.

Robot, 2000. 22(5): p. 427-432.

41. Biomimetic dolphin, Peking University. [JPG]; Available from:

http://www.zjgkj.gov.cn/Article/ShowArticle.asp?ArticleID=14706

.

42. Intelligent robot. [JPG]; Available from:

http://www.ia.ac.cn/kxcb/kxtp/200908/t20090811_2364468.html.

43. Srinivasan, M.A. and C. Basdogan, Haptics in virtual

environments: Taxonomy, research status, and challenges.

Computers & Graphics, 1997. 21(4): p. 393-404.

Page 152: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

149

44. Oakley, I., et al., Putting the feel in \’look and feel\&lsquo,

in Proceedings of the SIGCHI conference on Human factors in

computing systems. 2000, ACM: The Hague, The Netherlands. p.

415-422.

45. Merriam-Webster Online Dictionary. Available from:

http://www.merriam-webster.com/dictionary/.

46. ISO, in TC159/SC4/WG9.

47. Salisbury, K., F. Conti, and F. Barbagli, Haptic rendering:

introductory concepts. Computer Graphics and Applications, IEEE,

2004. 24(2): p. 24-32.

48. Goertz, R.C., FUNDAMENTALS OF GENERAL-PURPOSE

REMOTE MANIPULATORS. Journal Name: Nucleonics (U.S.)

Ceased publication; Journal Volume: Vol: 10, No. 11; Other

Information: Orig. Receipt Date: 31-DEC-53, 1952: p. Medium: X;

Size: Pages: 36-42.

49. Stone, R., Haptic feedback: a brief history from telepresence to

virtual reality, in Haptic Human-Computer Interaction, S.

Brewster and R. Murray-Smith, Editors. 2001, Springer Berlin /

Heidelberg. p. 1-16.

50. T.B., S., Telerobotics, in Plenary Presentation for 10th IFAC

World Congress on Automatic Control. 1987: Munich.

51. Sheridan, T.B., Telerobotics. Automatica, 1989. 25(4): p. 487-507.

Page 153: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

150

52. History Of Glove Input Devices. Interface Design 6 Jan 2011;

Available from:

http://interface-design-10.wikis.bgc.bard.edu/history-of-glove-inpu

t-devices.

53. Bergamasco, M., The GLAD-IN-ART Project, in In Proceedings of

Imagina '92 (Edited by Le Centre National de la

Cinematographie). 1992: Monte Carlo, France. p. II-7 to II-14.

54. Stone, R.J., IERAPSI - A Human-Centred Definition of Surgical

Procedures, in Work Package 2, Deliverable D2 (Part 1), Revision

1.0. May, 2000, Framework V Contract No.: IST-1999-12175.

55. Breder, C.M., The locomotion of fishes. Zoologica, 1926. 4: p.

159–256.

56. Webb, P.W., Form and function in fish swimming. Scientific

American, 1984. 251(1): p. 58-68.

57. Webb, P.W., The biology of fish swimming, in Mechanics and

Physiology of Animal Swimming, B.Q. Maddock L, Rayner J M V,

Editor. 1994, Cambridge University. p. 45-62.

58. Webb, P.W., 3 Hydrodynamics: Nonscombroid Fish, in Fish

Physiology, W.S. Hoar and D.J. Randall, Editors. 1979, Academic

Press. p. 189-237.

Page 154: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

151

59. Triantafyllou, M.S., G.S. Triantafyllou, and D.K.P. Yue,

Hydrodynamics of Fishlike Swimming. Annual Review of Fluid

Mechanics, 2000. 32(1): p. 33-53.

60. Drucker, E.G. and G.V. Lauder, Locomotor function of the dorsal

fin in teleost fishes: experimental analysis of wake forces in

sunfish. Journal of Experimental Biology, 2001. 204(17): p. 2943.

61. Tokumaru, P.T. and P.E. Dimotakis, Rotary oscillation control of a

cylinder wake. Journal of Fluid Mechanics, 1991. 224: p. 77-90.

62. Streitlien, K., Extracting energy from unsteady flows through

vortex control. 1994, Massachusetts Institue of Technology. p. 139.

63. Triantafyllou, G.S., M.S. Triantafyllou, and M.A. Grosenbaugh,

Optimal Thrust Development in Oscillating Foils with Application

to Fish Propulsion. Journal of Fluids and Structures, 1993. 7(2): p.

205-224.

64. Anderson, J.M., Vorticity Control for Efficient Propulsion, in

Massachusetts Institute of Technology. Dept. of Ocean

Engineering. 1996, Massachusetts Institute of Technology. p. 197.

65. Muller, U.K., et al., Fish foot prints: morphology and energetics of

the wake behind a continuously swimming mullet (Chelon labrosus

Risso). J Exp Biol, 1997. 200(22): p. 2893-2906.

66. Wolfgang, M., et al., Near-body flow dynamics in swimming fish. J

Exp Biol, 1999. 202(17): p. 2303-2327.

Page 155: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

152

67. Domenici, P. and R. Blake, The kinematics and performance of fish

fast-start swimming. J Exp Biol, 1997. 200(8): p. 1165-1178.

68. Weihs, D., A Hydrodynamical Analysis of Fish Turning

Manoeuvres. Proceedings of the Royal Society of London. Series

B, Biological Sciences, 1972. 182(1066): p. 59-72.

69. Taylor, G., Analysis of the Swimming of Long and Narrow

Animals. Proceedings of the Royal Society of London. Series A,

Mathematical and Physical Sciences, 1952. 214(1117): p. 158-183.

70. Lighthill, M.J., Note on the swimming of slender fish. Journal of

Fluid Mechanics, 1960. 9(02): p. 305-317.

71. Wu, T.Y.-T., Swimming of a waving plate. Journal of Fluid

Mechanics, 1961. 10(03): p. 321-344.

72. Lighthill, M.J., Aquatic animal propulsion of high

hydromechanical efficiency. Journal of Fluid Mechanics, 1970.

44(02): p. 265-301.

73. Lighthill, M.J., Large-Amplitude Elongated-Body Theory of Fish

Locomotion. Proceedings of the Royal Society of London. Series

B, Biological Sciences, 1971. 179(1055): p. 125-138.

74. Chopra, M.G., Hydromechanics of lunate-tail swimming

propulsion. Journal of Fluid Mechanics, 1974. 64(02): p. 375-392.

75. VIDELER, J.J. and F. HESS, Fast Continuous Swimming of Two

Pelagic Predators, Saithe (Pollachius Virens) and Mackerel

Page 156: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

153

(Scomber Scombrus): a Kinematic Analysis. J Exp Biol, 1984.

109(1): p. 209-228.

76. Cheng, J. and R. Blickhan, NOTE ON THE CALCULATION OF

PROPELLER EFFICIENCY USING ELONGATED BODY

THEORY. J Exp Biol, 1994. 192(1): p. 169-177.

77. TRIANTAFYLLOU, et al., A new paradigm of propulsion and

maneuvering for marine vehicles. Discussion. Authors' closure.

Vol. 104. 1996, New York, NY, ETATS-UNIS: Society of Naval

Architects and Marine Engineers.

78. Tong, B., Propulsive mechanism of fish's undulatory motion.

Mechanics In Engineering, 2000. 22: p. 69-74.

79. Melsaac, K.A. and J.P. Ostrowski, A geometric approach to

anguilliform locomotion: modelling of an underwater eel robot, in

Robotics and Automation, 1999. Proceedings. 1999 IEEE

International Conference on. 1999. p. 2843-2848.

80. T., K. Designing an underwater eel-like robot and developing

anguilliform locomotion control. Available from:

http://www.ese.upenn.edu/~sunfest/pastProjects/Papers00/Knutsen

Tamara.pdf.

81. Koichi Hirata, S.K. Prototype Fish Robot, UPF-2001. 9 Nov

2001; Available from:

Page 157: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

154

http://www.nmri.go.jp/eng/khirata/fish/experiment/upf2001/index_

e.html.

82. Quan, X., K. Feng, and T. Jin, Research on point-to-point of

Biomimetic Robot-fish based on fuzzy control, in Electric

Information and Control Engineering (ICEICE), 2011

International Conference on. 2011. p. 1652-1655.

83. Dandan, Z., et al., Coordinated Transport by Multiple Biomimetic

Robotic Fish in Underwater Environment. Control Systems

Technology, IEEE Transactions on, 2007. 15(4): p. 658-671.

84. Barrett, D., M. Grosenbaugh, and M. Triantafyllou, The optimal

control of a flexible hull robotic undersea vehicle propelled by an

oscillating foil, in Autonomous Underwater Vehicle Technology,

1996. AUV '96., Proceedings of the 1996 Symposium on. 1996. p.

1-9.

85. Kato, N. and M. Furushima, Pectoral fin model for maneuver of

underwater vehicles, in Autonomous Underwater Vehicle

Technology, 1996. AUV '96., Proceedings of the 1996 Symposium

on. 1996. p. 49-56.

86. Harper, K.A., M.D. Berkemeier, and S. Grace, Modeling the

dynamics of spring-driven oscillating-foil propulsion. Oceanic

Engineering, IEEE Journal of, 1998. 23(3): p. 285-296.

Page 158: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

155

87. Kelly, S.D. and R.M. Murray, Modelling efficient pisciform

swimming for control. International Journal of Robust and

Nonlinear Control, 2000. 10(4): p. 217-241.

88. Hirata, K., Development of Experimental Fish Robot, in Sixth

International. Symposium On Marine Engineering. 2000. p.

711-714.

89. Morgansen, K.A., et al., Nonlinear control methods for planar

carangiform robot fish locomotion, in Robotics and Automation,

2001. Proceedings 2001 ICRA. IEEE International Conference on.

2001. p. 427-434.

90. Saimek, S. and P.Y. Li, Motion planning and control of a

swimming machine, in American Control Conference, 2001.

Proceedings of the 2001. 2001. p. 125-130.

91. Bhatta, P. and N.E. Leonard, Stabilization and coordination of

underwater gliders, in Decision and Control, 2002, Proceedings of

the 41st IEEE Conference on. 2002. p. 2081-2086.

92. Leonard, N.E. and E. Fiorelli, Virtual leaders, artificial potentials

and coordinated control of groups, in Decision and Control, 2001.

Proceedings of the 40th IEEE Conference on. 2001. p. 2968-2973.

93. Joshua G. Graver and Ralf Bachmayer, N.E.L., David M.

Fratantoni, Underwater Glider Model Parameter Identification, in

Page 159: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

156

Proc. 13th Int. Symp. on Unmanned Untethered Submersible

Technology (UUST). 2003.

94. Ogren, P., F. Edward, and L. Naomi Ehrich, Formations with a

mission: stable coordination of vehicle group maneuvers, in Proc.

15th International Symposium on Mathematical Theory of

Networks and Systems. 2002.

95. Coordinated Control of Multiple Autonomous Vehicles at

Princeton University. http://dcsl.princeton.edu/?page_id=38].

Available from: http://graham.princeton.edu/~auvlab.

96. McIsaac, K.A. and J.P. Ostrowski, Experimental Verification of

Open-loop Control for an Underwater Eel-like Robot. International

Journal of Robotics Research, 2002. 21(10/11): p. 849.

97. Boyer, F., M. Porez, and W. Khalil, Macro-Continuous Computed

Torque Algorithm for a Three-Dimensional Eel-Like Robot. IEEE

Transactions on Robotics, 2006. 22(4): p. 763-775.

98. Fin Actuated Autonomous Underwater Vehicle. Available from:

http://vger.aa.washington.edu/fish_project.html.

99. Morgansen, K.A., P.A. Vela, and J.W. Burdick, Trajectory

stabilization for a planar carangiform robot fish, in Robotics and

Automation, 2002. Proceedings. ICRA '02. IEEE International

Conference on. 2002. p. 756-762.

Page 160: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

157

100. Junzhi, Y., et al., Development of a biomimetic robotic fish and its

control algorithm. Systems, Man, and Cybernetics, Part B:

Cybernetics, IEEE Transactions on, 2004. 34(4): p. 1798-1810.

101. Mittal, R., Computational modeling in biohydrodynamics: trends,

challenges, and recent advances. Oceanic Engineering, IEEE

Journal of, 2004. 29(3): p. 595-604.

102. Zhang, Y.-H., et al., A Computational Fluid Dynamics (CFD)

analysis of an undulatory mechanical fin driven by shape memory

alloy. International Journal of Automation and Computing, 2006.

3(4): p. 374-381.

103. Tangorra, J.L., et al., The Development of a Biologically Inspired

Propulsor for Unmanned Underwater Vehicles. Oceanic

Engineering, IEEE Journal of, 2007. 32(3): p. 533-550.

104. Mohammadshahi, D., et al., Design, fabrication and hydrodynamic

analysis of a biomimetic robot fish, in Proceedings of the 10th

WSEAS International Conference on Automatic Control, Modelling

\& Simulation. 2008, World Scientific and Engineering Academy

and Society (WSEAS): Istanbul, Turkey. p. 249-254.

105. Anton, M., et al., Analytical and computational modeling of

robotic fish propelled by soft actuation material-based active

joints, in Intelligent Robots and Systems, 2009. IROS 2009.

IEEE/RSJ International Conference on. 2009. p. 2126-2131.

Page 161: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

158

106. Listak, M., D. Pugal, and M. Kruusmaa, CFD simulations and real

world measurements of drag of biologically inspired underwater

robot, in US/EU-Baltic International Symposium, 2008 IEEE/OES.

2008. p. 1-4.

107. Guan, Z., et al., A 3-D Locomotion Biomimetic Robot Fish with

Information Relay, in Intelligent Robotics and Applications, C.

Xiong, et al., Editors. 2008, Springer Berlin / Heidelberg. p.

1135-1144.

108. Craig, J.C. and G.B. Rollman, SOMESTHESIS. Annual Review of

Psychology, 1999. 50(1): p. 305-331.

109. Sherrick, C.E., Touch as a communicative sense: Introduction. The

Journal of the Acoustical Society of America, 1985. 77(1): p.

218-219.

110. Vincent Hayward, O.R.A., Manuel Cruz-Hernandez, Danny Grant,

Gabriel Robles-De-La-Torre, Haptic interfaces and devices. Sensor

Review, 2004. 24(1): p. 16-29.

111. Finch, M., et al., Surface modification tools in a virtual

environment interface to a scanning probe microscope, in

Proceedings of the 1995 symposium on Interactive 3D graphics.

1995, ACM: Monterey, California, United States. p. 13-ff.

112. Mark, W.R., et al., Adding force feedback to graphics systems:

issues and solutions, in Proceedings of the 23rd annual conference

Page 162: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

159

on Computer graphics and interactive techniques. 1996, ACM. p.

447-452.

113. Ouh-Young, M., Force display in molecular docking. 1990, The

University of North Carolina at Chapel Hill p. 379.

114. Hirabayashi, T., et al., Teleoperation of construction machines with

haptic information for underwater applications. Automation in

Construction, 2006. 15(5): p. 563-570.

115. Dobashi, Y., et al., A fluid resistance map method for real-time

haptic interaction with fluids, in Proceedings of the ACM

symposium on Virtual reality software and technology. 2006,

ACM: Limassol, Cyprus. p. 91-99.

116. Sanwa RS-995 Servo. [cited 2011; Available from:

http://www.rc-book.com/en/node/3777/sanwa-rs-995-servo.

117. Hirata, K. Up-down Motion for a Fish Robot. 3rd Feb. 2001;

Available from:

http://www.nmri.go.jp/eng/khirata/fish/general/updown/index_e.ht

ml.

118. BARRETT, et al., Drag reduction in fish-like locomotion. Vol.

392. 1999, Cambridge, ROYAUME-UNI: Cambridge University

Press.

Page 163: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

160

119. Yu, J., Research on Control and Coordination of Multiple

Bio-mimetic Robot Fishes, in Institute of Automation, Chinese

Academy of Sciences. 2003: Beijing.

120. Zhou, C., Research on Modeling, Control and Cooperation of a

Marsupial Biomimetic Robotic Fish, in Institute of Automation,

Chinese Academy of Sciences. 2008: Beijing.

121. Zhang, Z., S. Wang, and M. Tan, 3-D locomotion control for a

biomimetic robot fish. Journal of Control Theory and Applications,

2004. 2(2): p. 169-174.

122. Chao, Z., et al., The Posture Control and 3-D Locomotion

Implementation of Biomimetic Robot Fish, in Intelligent Robots

and Systems, 2006 IEEE/RSJ International Conference on. 2006. p.

5406-5411.

123. McIsaac, K.A. and J.P. Ostrowski, Motion planning for

anguilliform locomotion. Robotics and Automation, IEEE

Transactions on, 2003. 19(4): p. 637-652.

124. Shape Effects on Drag. Available from:

http://wright.nasa.gov/airplane/shaped.html.

125. Epstein, M., J.E. Colgate, and M.A. MacIver, Generating Thrust

with a Biologically-Inspired Robotic Ribbon Fin, in Intelligent

Robots and Systems, 2006 IEEE/RSJ International Conference on.

2006. p. 2412-2417.

Page 164: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

161

126. DEFINE_GRID_MOTION. Available from:

http://my.fit.edu/itresources/manuals/fluent6.3/help/html/udf/node7

8.htm.

Page 165: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

162

Appendix

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A 3-D LOCOMOTION BIOMIMETIC ROBOT FISH WITH INFORMAITON RELAY

Zhenying Guan*, Chao Zhou**, Zhiqiang Cao**, Nong Gu*,

Min Tan**, Saeid Nahavandi*

* Intelligent Systems Research Lab., Deakin University, Geelong, VIC 3217, Australia ** Laboratory of Complex Systems and Intelligence Science, Institute of Automation,

Chinese Academy of Sciences, Beijing, 100190, China *{zgua, ng, nahavand}@deakin.edu.au

**{zhouchao, zqcao, tan}@compsys.ia.ac.cn

Abstract: In this paper, a biomimetic robot fish is designed. It has a biomimetic tail to simulate the carangiform tail, a barycenter-adjustor for descending/ascending motions, multiple sensors, and it may communicate with the outside by an information relay system on water. Combining the movements of the tail and the structure for descending and ascending, the robot fish can simulate the swimming of real fish in water and a biomimetic motion library is established. Finally, the prototype and experiments are given.

Keywords: biomimetic robot fish, 3-D locomotion, information relay, biomimetic motion library

1 INTRODUCTION

In nature, the fish adjusts itself to hydrodynamics environment and becomes a perfect swimming expert during years of evolution. Many researchers study its body structure and swimming characteristics and many propulsive theories are given. Lighthill built a model based on elongated-body theory to analyze the carangiform propulsive mechanism [1][2]. The large-amplitude elongated-body theory [3] was propounded to analyze the irregular amplitude of the tail. Wu developed a two-dimensional (2-D) waving plate theory, treating fish as elastic plates to analyze the hydrodynamic feature of the carangiform fish [4]. Triantfyllou [5][6] found that the jet formed behind the fish body played an important part of propulsion. Tong developed the 3-D waving plate theory (3DWDP) based on the 2-D waving plate theory and a semi-analytic semi-numeric method was adopted to obtain the 3-D nonstationary linear solutions [7].

With the development of propulsive theories and robotic technologies, the research on a biomimetic robot fish with high velocity, high efficiency and high maneuverability has been a hotspot. MIT successfully developed an eight-link, fish-

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like machine-RoboTuna. RoboTuna and subsequent RoboPike [5][8] projects attempted to create AUVs with increased energy savings and longer mission duration by utilizing a flexible posterior body and a flapping foil (tail fin). In Nagoya University, Guo developed a kind of underwater microrobot by using ICPF actuator [9][10]. Mitsubishi Heavy Industries (MHI) created a robotic replica of the rarely-seen coelacanth, which died out millions of years ago and was known only from fossils [11]. Scientists in Harvard University developed an underwater eel robot [12][13] and analyzed its kinematics and kinetics. K H Low designed a robot fish with undulating fins [14]-[16]. The Harbin Institute of Technology conducted the underwater robot research on imitating the propulsion mechanical structure of the fish fins and constructed an experiment platform using elastic module [17]. National University of Defense Technology investigated on the Long Flexible Fin Undulation equipment, which was based on the undulatory Calisthenics of Gymnarchus niloticus’s long flexible dorsal fin [18]. Peking University developed the biomimetic dolphin and built a series of experiments and a test platform [19]. Institute of Automation Chinese Academy of Sciences studied on the coordination and control of robot fishes [20].

As a new idea for developing a robot fish system under the water, we construct a biomimetic robot fish with a simulating-carangiform tail, a barycenter-adjustor and several kinds of sensors, which performs 3-D locomotion and may avoid obstacles with the help of infrared sensors. The robot fish can communicate with the upper console via a buoyage information relay, which makes it possible for the upper console to get more information under water and send instructions to the robot fish to execute complicated tasks.

In the rest of the paper, section 2 describes the design of the mechanical structure and the control system. The biomimetic motion library is given in Section 3. The robot fish prototype and experiments are introduced in Section 4 and Section 5 concludes the paper.

2 DESIGN OF THE ROBOT FISH

2.1 Design of the Mechanical Structure

The biomimetic robot fish is designed based on the Carangiform prototype as it has a good balance of velocity, acceleration and controllable properties. As shown in Fig. 1, the biomimetic robot fish is made up of the following parts:

• sensing unit (infrared sensors + press sensor + CCD camera); • control unit (MCU + peripherals); • communication unit (optical transmitter + optical receiver + wireless modules +

optical fiber cable + cable); • actuation unit (pitch motor + 4 tail motors); • support frame (aluminium exoskeleton + head); • accessories (Li-polymer batteries + waterproofed skin + caudal fin, etc.).

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A 3-D LOCOMOTION BIOMIMETIC ROBOT FISH WITH INFORMAITON RELAY 3

The robot fish has a clipper-built head, flexible body and a caudal fin. The rigid head made of FRP (Fiberglass-Reinforced Plastics) has a big room inside, where MCU, batteries, sensors, peripherals etc. are installed. The flexible body is built by four links, which are jointed together by an aluminium exoskeleton, driven by four tail motors and airproofed by a waterproofed skin. The flexiblle body cooperates with the caudal fin on simulating the movement of the carangiform fish tail, which impulses the robot fish to swim forward. At the same time, in order to maintain the balance when the robot fish is swimming in water, some weights are fitted into the robot fish’s body.

Fig. 1. Biomimetic robot fish system

There are several methods to descend or ascend, such as Changing Gravitation (Buoyancy), Pectoral fins, Changing body shape, Changing the barycenter and so on[21]. Considering these methods’ features and limitations in the realization, changing the gravity center is chosen to realize the robot fish’s 3-D movement. A barycenter-adjustor mechanical structure is designed and implemented. It is driven by a motor and can swing to different angles to change the gravity center of the whole robot fish. With shifting of the gravity center, the robot fish can pitch to swim upwards or downwards.

Moreover, several kinds of sensors equip the robot fish for autonomic control and environmental monitoring. Firstly, three infrared sensors mounted on the left, middle and right side of the robot fish head are used to detect obstacles, which are processed by MCU directly and keep the fish swimming safely. Secondly, the water depth information can be gained by a pressure sensor set on the body, by which the robot fish can get feedback of depth data using for diving depth control. Thirdly, a camera is installed on the fish head to provide abundant information in front of the fish.

Limited by the information processing capability of the robot fish, it is necessary to design a communication system between the robot fish and the outside. There are several methods on the information transmission of the robot fish. One is to utilize

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wireless equipment, which only works above the water surface because of severe attenuation of the electromagnetic wave in water. The robot fish has to swim only on water or ascend to the water surface to exchange the data with the upper console. Another is to connect the robot fish with the upper console by a cable directly, which can assure the transfer speed and accuracy. However, this method will limit the robot fish. In this paper, a buoyage information relay is presented. It is used as a communication relay that connects the robot fish by cables on one hand and communicates with the upper console by wireless on the other hand.

2.2 The Control System

The robot fish’s control system is shown in Fig. 2. The MCU using uCOS-II real-time operating system based on the minimal system of Mega128 sends task-related PWM signals to tail motors to control its motions and to pitch the motor to change the fish’s gravity center. It exchanges the information with the outside via the buoyage information relay.

Fig. 2. The block diagram of the control system

Two kinds of data, the mass visual data from CCD camera, the digital signals including the information provided by other sensors and commands from the upper console should be transmitted separately. The digital signals are sent to the buoyage information relay via normal cable after being converted into RS232 Serial signal and then sent out by low frequency wireless module and received by the upper console later. And vice versa, as the digital signals may be sent to robot fish by the upper console via this information relay system. At the same time, the visual signals are converted into light signals and sent to the buoyage information relay via optical fiber cable, where the light signals are resumed into electronic signals and then sent out by high frequency wireless module. The upper console receives the information and extracts it to make decisions for remote control. The result of vision processing and the target identification reflects the information of environment and goals.

In one word, with the information from sensing units, the robot fish may make decisions independently or execute a task after combining them with the commands from the upper console.

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A 3-D LOCOMOTION BIOMIMETIC ROBOT FISH WITH INFORMAITON RELAY 5

3 THE BIOMIMETIC MOTION LIBRARY

According to the behaviors of real fish and the functions of biomimetic robot fish, a biomimetic motion library is designed based on the mechanical structure and the control system. The robot fish adjusts its poses in water by controlling the oscillatory frequency of the tail and the position of the gravity center. Accordingly, the motion library includes acceleration, deceleration, uniform motion, turn, dive, and even swimming backwards. Different combinations of these motions may be chosen according to the task required to be executed.

The tail’s movement is the basis of the biomimetic motion library. Researchers point out that there is an implied travelling wave in the body of swimming fish, which runs from its neck to tail. The wave whose amplitude increases gradually appears as the curvature of the fish’s spine and muscle. It travels faster than the fish’s forward movement. The robotic fish is devised according to carangiform propulsion model, whose propulsive wave curve starts from the fish’s inertia centre to its caudal link. It is assumed that this kind of curve can be described by Eq. (1) [1][22].

)])][sin([(),( 221 tkxxcxctxybody ω++= (1)

where bodyy is the transverse displacement of body, x is the displacement along

main axis, k is the body wave number, λπ2=k , λ is the body wave length, 1c is the linear wave amplitude envelope, 2c is the quadratic wave amplitude envelope, ω is the body wave frequency T/2πω = . A sample of the fish body wave curve is shown in Fig. 3.

Fig. 3. Links fitting fish’s body-wave

The parameters ( )ωλ,,, 21 cc are chosen to determine the proper body wave. We adopt four hinge links to simulate the locomotion of fish tails (see Fig. 1), the robot fish’s oscillatory part can be modeled as a planar serial chain of links at an interval of 0 to π2×R along the axial body displacement, where R is defined as the length ratio of the fish's oscillating part to the whole sine wave. Let the length of each link be )4,3,2,1( =jI j , the ratio of them be 4321 ::: llll , and the link angle between 1−jl

and jl be jϕ [23]. With the jϕ changing, the fish's oscillatory part undulate along

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the travelling wave as Eq. (1) expressed. Impetus is produced when the speed of body wave propagation exceeds the speed of fish swimming forward [24][25].

Propulsion: The acceleration, deceleration and uniform motion are realized by changing the swing frequency of the robot fish tail, which is realized by sending different signals to the motors of the tail. Increasing duty ratio of the PWM signal to the tail motors results in increasing the tail's swing frequency, which increases the fish swimming speed. On the contrary, reducing duty ratio of the PWM signal may result in the deceleration of the speed. If the tail motor rotates uniformly the robot fish will swim at uniform velocity [23].

In addition, the robot fish may be considered to realize swimming backwards according to the study on kinematics and kinetics of Europe eel [26].

Turn: The orientation control is realized by superimposing different link’s deflection. It is necessary to insure that the oscillating rule matches Eq. (1) when turning, so the arc is chosen as the oscillating axis of the links. Correcting Eq. (1), we have [27] [28]:

2 2 21 2( , ) [( )][sin( )]bodyy x t c x c x kx t R x Rω= + + + − − (2)

where R is the radius of the tail axis, which is connected with the turning radius. A sample of the corrected fish body wave curve is shown in Fig. 4.

1l

2l3l

4l

( )dm

( )dm

Fig. 4. The corrected fish body wave curve

Dive: As described above, the robot fish pitch uses the barycenter-adjustor to change its posture [26]. As shown in Fig. 5, O0, O1 are respectively the initial position of buoyancy (FB) centre and the gravity centre. m is the weight of the adjustor. M is the fish weight without m. r is the length of the turning arm. When the pitch motor turns θ (clockwise, assumed to be “+”), the barycenter-adjustor moves forward. As a result, the robot fish’s gravity centre moves forward to O1' and the robot fish gets a pitch angle α, together with the tail’s swinging movement, it will swim downwards.

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A 3-D LOCOMOTION BIOMIMETIC ROBOT FISH WITH INFORMAITON RELAY 7

Fig. 5. The moment analysis of barycenter-adjustor

4 EXPERIMENTS

Fig. 6 gives a functional prototype of the biomimetic robot fish with a tail for propulsion, barycenter-adjustor and information relay system.

Fig. 6. The functional prototype of the biomimetic robot fish

The experiments are conducted in a pool of 4.0m*3.0m*0.75m. Fig. 7 describes the process of turn by adding deflection on the tail in the experiment pool, which shows the feasibility of the biomimetic robot fish design.

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(a) (b)

(c) (d)

Fig. 7. The image sequence of the robot fish turning

Another experiment is related to goal recognition. The camera on the robot fish sends out the video to the upper console, which extracts the goal based on the given color decided by the operator. Fig. 8 gives the selected image from the camera of the robot fish, where the robot fish swims in the experiment pool with the goal A. B is the recognition result based on the color characteristic, which shows that the goal is successfully recognized in water, which is useful for future process.

Fig. 8. The selected image and the corresponding recognition result

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A 3-D LOCOMOTION BIOMIMETIC ROBOT FISH WITH INFORMAITON RELAY 9

5 CONCLUSION

In this paper, a novel biomimetic robot fish with a carangiform tail for propulsion and barycenter-adjustor for diving are designed based on the analysis of propulsion and maneuvering mechanisms for carangiform swimming. An information relay system on water is designed for information transmitting. The sensors information processing of the fish are studied. Some experiments are carried out upon the biomimetic robot fish, and the results have initially demonstrated the performance of the mechanical structure and control system of the biomimetic robot fish.

In the future, we will endeavour to improve the performance of the robot fish and make use of the reserved interfaces and big space in its head to extend new functions.

ACKNOWLEDGEMENT This work is funded by research grants from National Natural Science Foundation of China under Grants 60725309, 60635010. The authors would also like to thank Intelligent Systems Research Lab., Deakin University, Australia for the support to this work.

REFERENCES 1 Lighthill M. J.: Note on the swimming of slender fish. Journal of Fluid Mechanics, vol.9,

305-317 (1960) 2 Lighthill M. J.: Aquatic animal propulsion of high hydromechanical efficiency. Journal of

Fluid Mechanics, vol.44, 265-301 (1970) 3 Lighthill M. J.: Large-amplitude elongated-body theory of fish locomotion. Proceedings of

the Royal Society of London. Series B, Biological Sciences, vol. 179, Issue 1055, 125-138 (1971)

4 Wu T. Y.: Swimming of a waving plate. J. Fluid Mech, vol.10, 321-344 (1961) 5 Triantafyllou M. S., and Triantafyllou G. S.: An efficient swimming machine. Scientific

American, 272(3): 64-70 (1995) 6 Triantafyllou M. S., Barrett D. S., and Yue D. K. P.: A new paradigm of propulsion and

maneuvering for marine vehicles. Trans. Soc. Naval Architects Marine Eng, vol.104, 81-100 (1996)

7 Tong B.: Propulsive mechanism of fish's undulatory motion. Mechanics In Engineering, 22: 69-74 (2000) (in Chinese)

8 Barrett D. S., Triantafyllou M. S., Yue D. K. P., et al: Drag reduction in fish-like locomotion. J. Fluid Mech, vol.392, 183-212 (1999)

9 Guo S., Kato N., Fukuda T., Oguro K.: a Fish-microrobot Using ICPF Actuator. The 5th International Workshop on Advanced Motion Control (AMC19998). 592-597 (1998)

10 Guo S., Fukuda T., Kato N., Oguro K.: Development of Underwater Microrobot Using ICPF actuator. Proceedings of the 1998 IEEE International conference on Robotics & automation, Leoven Belgium (1998)

11 RobotBooks, http://www.robotbooks.com/coelecanth-robot.htm 12 McIsaac K., Ostrowski J., A Geometric Approach to Anguilliform Locomotion: Modelling

of an Underwater Eel Robot. In: Proceedings of the 1999 IEEE Conference of Robotics and Automation (ICRA1999). Detroit, Michigan: IEEE, 2843-2848 (1999)

13 Knusten T.: Designing an underwater eel-like robot and developing anguilliform locomotion control. http://www.ese.upenn.edu/~sunfest/pastProjects/Papers00/KnutsenTamara.pdf

Page 175: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

14 Willy A., Low K. H.: Development and Initial Experiment of Modular Undulating Fin for Untethered Biorobotic AUVs. IEEE International Conference on Robotics and Biomimetics (ROBIO2005). Hong Kong and Macau: IEEE, 45-50 (2005)

15 Low K. H., Willy A.: Biomimetic motion planning of an undulating robotic fish fin. Journal of Vibration and Control, 12(12):1337-1359 (2006)

16 Low K. H.: Locomotion Consideration and Implementation of Robotic Fish with Modular Undulating Fins: Analysis and Experimental Study. Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing, China: IEEE, 2424-2429 (2006)

17 Liu J., Chen Z., Chen W., Wang L.: A new type of under water turbine imitating fish-fin for under water robot. Robot, 22(5): 427-432 (2000) (in Chinese)

18 Xie H., Zhang D., Shen L.: Control System Design and Realization of Bionic Underwater Vehicle Propelled by the Long Flexible Fin Undulation. Journal of Control & Automation, 22 8-2: 218-221 (2006) (in Chinese)

19 Beijing Information Net, http://www.ctibj.com.cn/assembly/action/browsePage.do?channelID=1112148652630&contentID=1116421493073

20 Yu J., Wang S., and Tan M.: A Simplified Propulsive Model of Biomimetic Robot Fish and Its Realization. Robotica volume 23, 101-107 (2005)

21 National Maritime Research Institute, http://www.nmri.go.jp/eng/khirata/fish/index_e.html 22 Barrett D., Grosenbaugh M., Triantafyllow M.: The optimal control of a flexible hull robotic

undersea vehicle propelled by an oscillating foil. Proc. 1996 IEEE AUV Symp. New York: IEEE Press, 1-9 (1996)

23 Yu J.: Research on Control and Coordination of Multiple Bio-mimetic Robot Fishes. Dissertation for degree of Doctor of Engineering, Institute of Automation, Chinese Academy of Sciences (2003) (in Chinese)

24 Barrett D S, Triantafyllou M S, Yue D K P, et al.: Drag reduction infish-like locomotion. J. Fluid Mech. vol.392, 183-212 (1999)

25 Kato N., Furushima M.: Pectoral fin model for maneuver of underwater vehicles. Proceedings of 1996 IEEE AUV Symp. New York: IEEE Press, 49-56 (1996)

26 Zhou. C., Research on Modeling: Control and Cooperation of a Marsupial Biomimetic Robotic Fish. Dissertation for degree of Doctor of Engineering, Institute of Automation, Chinese Academy of Sciences (2008) (in Chinese)

27 Zhang Z., Wang S., and Tan M.: 3-D Locomotion control for a biomimetic robot fish. Journal of Control Theory and Applications, 2(2): 169-174 (2004)

28 Zhou. C., Cao Z., Wang S., and Tan M.: The Posture Control and 3-D Locomotion Implementation of Biomimetic Robot Fish. Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 5406-5411 (2006)

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978-1-4244-7815-6/10/$26.00 ©2010 IEEE ICARCV2010

3D Hydrodynamic Analysis of a Biomimetic Robot Fish

Zhenying Guan Centre for Intelligent Systems Research

Deakin University Geelong, Australia

[email protected]

Nong Gu Centre for Intelligent Systems Research

Deakin University Geelong, Australia

[email protected]

Weimin Gao Institute for Technology Research and Innovation

Deakin University Geelong, Australia

[email protected]

Saeid Nahavandi Centre for Intelligent Systems Research

Deakin University Geelong, Australia

[email protected]

Abstract— This paper presents a three-dimensional (3D) computational fluid dynamic simulation of a biomimetic robot fish. Fluent and user-defined function (UDF) is used to define the movement of the robot fish and the Dynamic Mesh is used to mimic the fish swimming in water. Hydrodynamic analysis is done in this paper too. The aim of this study is to get comparative data about hydrodynamic properties of those guidelines to improve the design, remote control and flexibility of the underwater robot fish.

Keywords—robot fish, computational fluid dynamics (CFD), user-defined function (UDF), Dynamic mesh, hydrodynamic analysis

I. INTRODUCTION Recently, there has been a growing interest in studying

biomimetic robot fish as it can provide significant insights into both theory and application of underwater robotics. Observations show that a fish in nature can achieve great propulsive efficiency and excellent maneuverability through coordinated motion of the body, fins, and tail. In 1994, RoboTuna, a first robotic fish in the world was successfully developed, which demonstrated that the power required to propel the swimming fish-like body was significantly smaller than that required to drag the body straight forward at the same speed [1][2]. McIsaac et al. developed an underwater eel robot [3][4] and analysed its kinematics and kinetics. Liu et al. conducted the underwater robot research to imitate the propulsion mechanical structure of the fish fins and constructed an experiment platform using an elastic module [5]. Xie et al. investigated the Long Flexible Fin Undulation equipment, which was based on the undulatory calisthenics of the long flexible dorsal fin of the gymnarchus niloticus[6]. Wang et al. developed a biomimetic dolphin, built a test platform and performed a series of experiments to explore a coordination method for multiply robot fishes to conduct an underwater

transport task [7]. Yu et al. studied the coordination and control of robot fishes [8].

It should be noted that most existing control algorithms of robot fishes are based on a simplified propulsive model that only provides a rough prediction of the effect of hydrodynamics on robot fishes. To obtain an accurate prediction to the hydrodynamic force on robotic fish, it is necessary to conduct dynamic analysis of the surrounding fluid by computational fluid dynamics (CFD) [9].

CFD analysis has been widely used in many areas, including vehicle design, aircraft design and ground robot development due to the following reasons [10].

• CFD simulations can be a useful tool for designers to understand the complex physics of the flow phenomena involved in the fluid dynamics.

• CFD simulations require less time than field test. Moreover, different models can be tested with CFD simulation before accrual prototype models are created for tests.

• CFD also provides detailed visualization of flow field, which is difficult to be obtained by experimental facilities.

CFD simulations and analyses for robot fishes have been carried out. Zhang et al. [11] investigated the fluid dynamics, pressure and velocity distribution, and the production of forces associated with an undulatory mechanical fin. Tangorra et al. [12] also employed CFD simulation, together with using stereo digital particle image velocimetry (DPIV) and proper orthogonal decomposition (POD), to estimate the hydrodynamic force generated by the complex component motions of their biorobotic pectoral fin and to analyse its hydrodynamics. The fins studied by Zhang et al. and Tangorra et al. are important factors towards developing propulsive

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devices that will make an underwater robot fish having the ability to produce and control thrust like highly maneuverable fish. Mohammadshahi et al. [13] evaluated hydrodynamic forces of a fish-like swimming robot by using a two-dimensional (2D) CFD model, which provided impactful results to optimize performance parameters in the process of design and fabrication, but 2D model of robt fish cannot offer abundant tridimensional information compared to 3D simulating. Anton et al. [14] adopted CFD modeling and examined the flow field, the produced thrust, and the bending moments at the joints of two-link tails of a robot fish, but the two-link tail fins were assumed to be rigid, thin and light. Actually, popular biomimetic robot fish bodies are soft and quite flexible. Listak et al. [15] created a 3D computer model for a biomimetic robot and simulated the ideal ellipsoid with Gerris, which helped them find an ideal robot fish body with low drag and improved the design, although without detail analysis on the simulation results. In this paper, to produce significant information on flow pattern, velocity and pressure fields and to prvide an insight into both the design and the application of robot fishes, a 3D CFD simulation was investigated for our robot fish propoto type [16] by using Fluent 6.3.26.

II. BIOMIMETIC ROBOT FISH We developed a biomimetic robot fish (Fig. 1) with 3D

locomotion capability. It consists of a simulating-carangiform tail, a barycenter-adjustor, a CCD camera and several infrared and pressure sensors. With these sensors, it is able to avoid running into obstacles automatically. Moreover, the robot fish can communicate with a remote computer via a buoyage information relay. The information relay enables operators to obtain the information of underwater situations in real time and send commands to the robot fish to execute complex tasks.

Figure 1. Biomimetic Robot Fish

The movement of the robotic fish is based on a carangiform propulsion model where the propulsive wave curve starts from the inertia centre to the caudal link of the fish (We call this part of the fish body as “fish tail”). The curve can be described by the following Equation.

21 2( , ) ( )sin( )bodyy x t c x c x kx tω= + + (1)

where bodyy is the transverse displacement of the fish body, x is the intergeted distance along the backbone of the fish from its inertia centre, k is the wave number, λπ2=k ,

λ is the body wave length, 1c is the linear wave amplitude envelope, 2c is the quadratic wave amplitude envelope, ω is the body wave frequency, T/2πω = .

III. 3D HYDRODYNAMIC SIMULATION MODEL

A. Biomimetic Robot Fish and The pool The 3D geometry and the mesh of the robot fish is

generated by Gambit (V2.3.16). To simplify the robot fish model, we ignore the effect of the connection cable between the robot fish and the buoyage information relay.

The dimension of the robot fish is 0.62m×0.16m×0.08m (length × max high × max width). To allocate enough space for dynamic current stretching, a pool is designed to be 9m×9m×4m. The pool walls are defined as moving walls and their local velocities depend on the fluid velocity. The main currents are backward flow generated by the locomotion of the fish tail so that the robot fish is located at the centre of the vertical cross section of the pool, while the distance between the fish head and the pool inlet is 1.53m.

B. Mesh Scheme To achieve a much quicker and more accurate calculation,

tetrahedronal mesh elements are only used for the cube area (0.91m×0.7m×0.4m) close to the robot fish, while Quant mesh elements as big as possible are used for other areas to reduce the number of elements. The distance between the small cube with tetrahedronal elements and the inlet is 1.42 m. This meshing scheme will give enough space to process meshing with high qualified tetrahedron around the robot fish and approach a lower number of meshes to reduce computational time. The key parameters for determining the mesh size are.

Reynolds number,

(2)

The thickness of the boundary,

(3)

where U=0.18 m/s (it is the experimental velocity of the robot fish)

L=0.62 m (the length of the robot fish)

v=1.01*10-6 (water viscosity)

To reach an accurate calculation of the forces acting on the fish surface and reduce the number of meshes, a boundary schema with a growing rate of 1.4 ratio and 4 layers is applied for the mashing the hydrodynamic boundary of the robot fish. According to Eq. (3), the size of the minimum grids adhered to the robot fish is 2 mm.

With the above settings, for the fluid domain, the total number of nodes is 189683 and the total number of elements is

5Re 1.1 10ULv

= = ×

14.64 0.00865( )Re

L mσ = × × =

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837773. Figs. 2 & 3 show the mesh distribution in the fluid regain and a close view around the fish.

Figure 2. Mesh of the Biomimetic Robot Fish

Figure 3. Robot Fish

C. Defination of the Locamotion of the Robot Fish User-defined function (UDF) is used to define the

movement of the robot fish and the dynamic mesh is used to simulate the fish swimming in water. As the oscillation of the fish tail (moving part-1, shown in fig. 4) and the caudal fin (moving part-2, shown in fig. 4) is complex and flexible, we choose the DEFINE macro DEFINE_GRID_MOTION to describe the movement of the fish tail and the caudal fin. DEFINE_GRID_MOTION is implemented according to Eq. (1) where c1=0.05, c2=0.09, k=0.5 and R=0.6

To couple the posture of the fish body accurately and timely, the performance of the dynamic mesh is quite important in the simulation. We used Smoothing and Remeshing mesh method here. The relative parameters used are listed in table I.

A commercial CFD code, Fluent 6.3.26 with a standard k–epsilon turbulent model and standard wall functions, are used in all simulations.

Figure 4. Mesh on Robot Fish body

TABLE I. PARAMETERS FOR DYNAMIC MESH

Mesh Methods

Parameters Setting Items setting

Smoothing

Spring Constant Factor 0.05

Boundary Node Relaxation 0.8

Convergence Tolerance 1e-05

Number of Iterations 100

Remeshing

Minimum Length Scale (m) 0.00072372

Maximum Length Scale (m) 0.0008

Maximum Cell Skewness 0.8

Maximum Face Skewness 0.79

Size Rmesh Interval 1

Size Function Resolution 1

Size Function Variation 48.94077

Size Function Rate 0.7

IV HYDRODYNAMIC ANALYSIS

A. Pressure distribution In the simulations, the robot fish oscillates its tail and

caudal fin at T = 0.7s (swinging period). The pressure distribution will be analysed on the horizontal cross section of the pool at the middle position (M-view), like Fig. 5.

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Figure 5. M-view

Figure 6. Pressure contours of the M-view at 4 locomotion times (N*m–2) ( a)

approaching the left maximal rotation position (t = 0.1 s); (b) intermedial position during oscillating motion (t = 0.25 s); (c) going on intermedial

position during oscillating motion (t = 0.4 s); (d) approaching right maximal rotation position (t =0.55 s). (It is supposed that a robot fish locomotion period

begin from the position t=0 according the Equation 1)

Fig. 6 shows the M-view of the pressure contours at four locomotion times (“The right” / “the left” means the side of the right / left hand when one stands on the point of the robot fish inertia centre and face to the fish head. ):

• At t = 0.1s (Fig. 6 (a)), the fish tail and the caudal fin are swinging from the right to the left and almost reach the maximal displacement. On the left side of the fish tail and the caudal fin, a bigger positive pressure is generated and a wider distribution than the right side can be found. Especially, the positive pressure focuses most on the rear of the tail, which generates forces pointing to the right-front of the fish. These positive pressures are generated as the water is extruded by the movement of the fish tail and the caudal fin. Also, they grow bigger along the direction from the fish tail to the caudal fin due to the growing up amplitudes of the fish tail and the caudal fin oscillating. This also implies that a tip vortex can be generated near the edge of the robot

fish caudal fin and considerable fluid is pushed into the downstream region on the left side of the caudal fin.

• At t = 0.25s (Fig. 6 (b)), the robot fish body and the caudal fin are already on the way of swinging back from the left to the right. This action pushes the water away, so a positive pressure is exerted and widely distributes on the right side of the fish tail and the caudal fin. Actually, immediately after the anticlockwise stroke began, which is a change of the fish tail swinging direction, one observes a small positive pressure distribution on the right side of the caudal fin and a negative pressure distribution on its left side. This shows the generation of the thrust. The direction of the thrust is left-front according the angle of the robot fish body posture.

• At t = 0.4s (Fig. 6 (c)), the fish tail and the caudal fin keep on swinging from the left to the right. The positive pressure grows up and turns to the left side of the robot fish. On the other side of the robot fish body, the negative pressure seems to be decreased. This demonstrates that the robot fish achieves a larger right-front direction thrust.

• At t = 0.55s (Fig. 6 (d)), the fish tail and the caudal fin keep on swinging from the left to the right and its body reach almost the most flexuous position. The positive pressure grows up quickly and distributes on both of the left side of the middle tail and the right side of the caudal fin. On the contrary, a negative pressure distributes on the right side of the tail. At this point, the robot fish achieves the largest forward direction thrust during the whole period.

• After the period described above, the fish tail and the caudal fin continue to swing for the next half period.

According to the above analysis, the resulting force that the robot fish acquires by periodically oscillating its tail and caudal fin can be divided into two types, the fluctuant thrust at forward direction and the drag at left-right direction.

B. velocity The velocity contours of the robot fish at critical instants

are shown in Figure 7 during the oscillation, the same instants and views with the ones for pressure contours analysis.

• At t = 0.1s (Fig. 7 (a)), a counter-rotating vortex is observed. This vortex is shed from the distal edge (especially the tip edge of the tail fin) on the robot fish. The shedding of vortex may be one of the main effects on the pressure distribution at the robot fish surface mentioned in the pressure analysis.

• At t = 0.25s (Fig. 7 (b)), a thin clockwise vortex sheds from the tip of the caudal fin at the beginning of the fish tail and the caudal fin reverse motion.

• At t = 0.4s (Fig. 7 (c)), one observes a clockwise vortex at the right middle side of the fish tail. The shedding of this vortex into the wake leads to a momentary increase in the thrust.

(a) 0.1s (b) 0.25s

(c) 0.4s (d) 0.55s

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• At t = 0.55s (Fig. 7 (d)), a large anticlockwise vortex sheds at the left middle side of the fish tail. Two clockwise vortexes shed at the right side of the upper tail and the caudal fin. The shedding of these vortexes into the wake leads to larger increase in the thrust than the one at t = 0.4s.

• After the period described above, the robot fish will endure the next similar half period.

Figure 7. Velocity distribution

C. Force After ten swinging periods, the inlet velocity becomes

stable and is about 0.18m/s, which is the same as our experiments. This says the simulation is valid. Figure 8 shows the forces exerted on the robot fish along with X and Z axes directions. In the X-axis direction, the fish suffers a much bigger force than in the Z-axis direction. The composite of the force in the X axis direction is almost zero, which is generated by the swing movement of the fish tail and the caudal fin. It will be counteracted by the force arisen from the movement of inside motors. The force in the Z-axis direction is always positive. This is caused by the movement of the fish tail and the tail fin. The robot fish will be driven by the force in the Z-axis direction.

Figure 8. Force in X and Z directions

IV. CONCLUSIONS In this paper, a computational fluid dynamic model was

built for a biomimetic robot fish. Lots of hydrodynamic properties, such as the exerted pressure and the force of the fish, have been obtained. This paper explained how the fish oscillated the tail and the caudal fin to push water away behind it and get the thrust pushing it forward.

The CFD simulations provided the information of the flow of water around the robot fish and the pressure distribution, which will be used for the optimization of robot fish and the improvement of the design and fabrication of the robot fish. It can also provide more complex fluid flow characteristics for the research and development of robot fishes used in different external situations.

For future work, we should investigate more accurate and realistic numerical simulations of the robot fish when it is swimming in kinds of modes, turning, diving or others, and in different water flow, downstream, adverse current, turbulence or other complex stream currents. Those may contribute to a better understanding and modeling of all the sophisticated solutions we need to develop in a near future.

ACKNOWLEDGMENT This research was funded by CISR, Deakin University. The

authors would also like to thank Mr. K. Khoshmanesh for his kind help on the CFD work presented in this paper.

REFERENCES [1] M. S. Triantafyllou, and G. S. Triantafyllou, “An efficient swimming

machine,” Scientific American, 272(3), pp. 64-70 , 1995 [2] D. S. Barrett, M. S. Triantafyllou, D. K. P. Yue, et al, “Drag reduction in

fish-like locomotion,” J. Fluid Mech, vol.392, pp. 183-212, 1999 [3] K. McIsaac, J. Ostrowski, “A Geometric Approach to Anguilliform

Locomotion: Modelling of an Underwater Eel Robot,” Proceedings of the 1999 IEEE Conference of Robotics and Automation (ICRA1999). Detroit, Michigan: IEEE, pp. 2843-2848, 1999

[4] T. Knusten, “Designing an underwater eel-like robot and developing anguilliform locomotion control,” http://www.ese.upenn.edu/~sunfest/pastProjects/Papers00/KnutsenTamara.pdf

[5] J. Liu, Z. Chen, W. Chen, L. Wang, “A new type of under water turbine imitating fish-fin for under water robot,” Robot, 22(5): pp. 427-432, 2000 (in Chinese)

[6] H. Xie, D. Zhang, L. Shen, “Control System Design and Realization of Bionic Underwater Vehicle Propelled by the Long Flexible Fin Undulation,” Journal of Control & Automation, 22 8-2, pp. 218-221, 2006 (in Chinese)

[7] D. Zhang; L. Wang; J. Yu; M. Tan, “Coordinated Transport by Multiple Biomimetic Robotic Fish in Underwater Environment,” IEEE Transactions on Control Systems Technology, Vol. 15 , Issue 4, pp. 658 – 671, 2007

[8] J. Yu, S. Wang, and M. Tan, “A Simplified Propulsive Model of Biomimetic Robot Fish and Its Realization,” Robotica vol. 23, pp. 101-107, 2005

[9] J. Yu; M. Tan; S. Wang; E. Chen, “Development of a biomimetic robotic fish and its control algorithm,” J. of Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 34 , Issue 4, pp. 1798 – 1810, 2004

[10] R. Mittal, “Computational modeling in bio-hydrodynamic-trends, challenges and recent advances,” In Proc. of the International Symposium on Unmanned Untethered Submersible Technology (UUST 2003), 2003.J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, pp.68–73, 1892

(a) 0.1S (b) 0.25S

(c) 0.4S (d) 0.55S

Page 181: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,

[11] Y. Zhang, J. He1, J. Yang1, S. Zhang and K. Low, "A Computational Fluid Dynamics (CFD) analysis of an undulatory mechanical fin driven by shape memory alloy " J. of Automation and Computing, Vol. 3, Number 4 / October, 2006

[12] J. Tangorra, S. Davidson, I. Hunter, P. Madden, G. Lauder, H. Dong, M. Bozkurttas and R. Mittal, “The Development of a Biologically Inspired Propulsor for Unmanned Underwater Vehicles”, J. of Oceanic Engineering, Vol. 32, No. 3, pp. 533 – 550, July 2007

[13] D. Mohammadshahi, A. Yousefi-koma, S. Bahmanyar, H. Ghassemi and H. Maleki, “Design, Fabrication and Hydrodynamic Analysis of a Biomimetic Robot Fish”, J. of Mechanics, Issue 4, Vol. 2, pp. 59 - 66, 2008

[14] M. Anton, Z. Chen, M. Kruusmaa and X. Tan, "Analytical and Computational Modeling of Robotic Fish Propelled by Soft Actuation Material-based Active Joints", The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems October 11-15, 2009 St. Louis, USA

[15] M. Listak, D. Pugal, M. Kruusmaa "CFD simulations and real world measurements of drag of biologically inspired underwater robot ", US/EU-Baltic International Symposium, 2008 IEEE/OES

[16] Z. Guan, C. Zhou, Z. Cao, N. Gu, M. Tan, S. Nahavandi, “A 3-D locomotion biomimetic robot fish with information relay,” Lecture Notes in Computer Science, Springer Berlin / Heidelberg, Vol. 5314/2008, pp.1135-1144.

Page 182: 3D Locomotion Biomimetic Robot Fish with Haptic Feedbackdro.deakin.edu.au/eserv/DU:30048718/guan-locomotion-2012.pdf · locomotion biomimetic robot fish with information relay”,