Post on 26-Apr-2020
Reconfigurable CPGs for an Adaptive Locomotion
Reconfigurable CPGs for the Implementation of
Adaptive Rhythmic Patterns of Locomotion.
José Hugo Barrón Zambrano.
Advisor: César Torres Huitzil.September, 2013.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 1
Reconfigurable CPGs for an Adaptive Locomotion
Outline
1 Motivation
2 Problem Description
3 Objectives and Hypothesis
4 Related Work
5 Methodology
6 Conclusions
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 2
Reconfigurable CPGs for an Adaptive Locomotion
Motivation
Motivation
A mobile robot depends on a locomotion mechanisms thatenable it to move throughout its environment.
Robot locomotion must perform in a controlled and reliablemanner through an unknown environment without the aid of ahuman operator.
To achieve an autonomous robot locomotion there are a largevariety of possible mechanisms to move.
Experiments and research work have addressed the feasibilityof the design of locomotion control systems based onlocomotion mechanisms present in humans and animals .
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 3
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
Problem Description
Legged locomotion concerns in how to determine the bestsequence, locomotion pattern, for lifting off and placing thefeet.
Legged locomotion requires multi-dimensional coordinatedrhythmic patterns that need to be correctly tuned to satisfymultiple constraints.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 4
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
Locomotion Approaches
Approach Mathematical model-
based
Biologically inspired ap-
proach
Main featu-
re
Joint angles are calculatedin advance
Central Pattern Generator
Design met-
hodology
Trial-and-error or recordingdata
Trial-and-error
Robot
knowledge
Exact robot model It does not need a robotmodel
Perturbation
problems
Require an additional mo-dule
Robust against perturba-tions
Control
scheme
Centralized Distributed
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 5
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
Central Pattern Generator (CPG)
The CPG is a neural circuit capable of producing coordinatedpatterns of rhythmic activity in open loop.
CPG can adapt to various environments by changing theperiodic rhythmic patterns through simple input signals.
The biological mechanisms underlying locomotion havetherefore been extensively studied by neurobiologists.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 6
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
CPG model
CPGs are often modeled as nonlinearoscillators through second order differentialequations that have mutually coupledexcitatory and inhibitory connections.
Oscillator model
xi = F (xi , xi , pxi , xai , Sfeed )(1)
Coupling contribution
xai = xi +Σwij ∗ xj (2)
For i =1, 2, 3, . . . , n , where xi is the output signal from oscillator i , n isthe number of oscillators in the CPG, pxi = [p0, p1, ..., pn] is the oscillatorparameters, Sfeed is the feedback signal,and wij is the coupling weight.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 7
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
CPG: Open Topics
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 8
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
CPG Design
To build a CPG able togenerate different basiclocomotion patterns.
Oscillator tuning.CPG structure.Transition between differentpatterns.
Given an oscillatorxi = F (xi , xi , pxi , xai), to find the valuesof vector pxi , feedback signal Sfeed , andthe coupling weights wij to generate aspecific locomotion pattern.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 9
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
Environment Feedback Integration
CPGs need environmentinformation to modulate andreact according to a sensedsituation.
The integration of feedbackinformation in the CPGmodulation process is notdirect.
To find the function, F , that mapsinformation sensors , Si , tolocomotion control parameters, Lc .
SiF→ Lc . (3)José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 10
Reconfigurable CPGs for an Adaptive Locomotion
Problem Description
Hardware Implementation
General purpose processor
Providing high accuracy andflexibility.Good performance onaverage.Tasks share the processortime.Real-time response cannot beguaranteed.
Analog implementation:
Computation and powerefficient.Lack flexibility to be reused.Large design cycles.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 11
Reconfigurable CPGs for an Adaptive Locomotion
Objectives and Hypothesis
Objectives
Main Objective
To design and implement an adaptive locomotion control, based onCPG principles and visual information integration, embedded in ahardware platform capable of reacting under real-time constraints.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 12
Reconfigurable CPGs for an Adaptive Locomotion
Objectives and Hypothesis
Objectives
Specific Objectives
To design a CPG-based locomotion able to generate multiplepatterns of locomotion for quadruped and hexapod robots andthe transitions between them.
To propose and implement an integration mechanism tomodulate the locomotion pattern generation based on visualinformation.
To design and implement efficiently a locomotion controlbased on biological organization embedded in a hardwareplatform under real-time constraints.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 13
Reconfigurable CPGs for an Adaptive Locomotion
Objectives and Hypothesis
Hypothesis
Hypothesis
It is possible to design a locomotion control scheme based on CPGprinciples able to generate adaptable locomotion patterns throughintegration of visual feedback information embedded in a customparallel hardware platform under real-time constraints.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 14
Reconfigurable CPGs for an Adaptive Locomotion
Objectives and Hypothesis
Contributions
Contributions
CPG able to generate three different locomotion patterns
for quadruped and hexapod morphologies.
CPG capable of switching between gaits, and controllingthe locomotion speed.
Scalable hardware architecture of CPG-based locomotion
for a quadruped and a hexapod morphologies, so as thephysical implementation in a hexapod robot.
Integration mechanism based on fuzzy logic and finite statemachine to modulate the CPG-base locomotion usingvisual perception information.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 15
Reconfigurable CPGs for an Adaptive Locomotion
Related Work
CPG-Based Locomotion: Quadruped Robots
Work Imple-mentation
Feedback IntegrationMechanism
Behavior
Billard andIjspeert(2000)
Software Internal (legpositions)
Linear equa-tion
Three gaits
Fukuoka etal. (2005)
Software external (ob-ject distances)
Linear equa-tion
Walk and con-trol direction
Feng andWang(2008)
Software Internal (legpositions)
PD-controller Walk and con-trol direction
Santosand Matos(2012)
Software External (ob-jects and dis-tances)
Mathematicalmodel
Pursuit andavoiding
Nakada etal. (2003)
Hardware(CMOS)
None None Three gaits
Nakada etal. (2005)
Hardware(VLSI)
None P-controller Three gaits
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 16
Reconfigurable CPGs for an Adaptive Locomotion
Related Work
CPG-Based Locomotion: Hexapod Robots
Work Imple-mentation
Feedback IntegrationMechanism
Behavior
Inagaki etal. (2006)
Software(parallel)
None Hamiltonianfunction
Three differentgaits with ve-locity control
Arena etal. (2004)
Software Internal(legspeeds)
Neural Net-worsk (SOM)
Three differentgaits
Arena etal. (2005)
Hardware(VLSI)
Internal (legspeeds andhorizontalpositions)
Neural net-works (CNN)and PID-controllers
Climbing gait
Arena etal. (2006)
Software(microcon-troller)
None Neural net-works (CNN)
Climbing gaitand directioncontrol
Manoonponget al.(2008)
Software External(Obstacledistance)
Neural net-works (FFNN)
Avoiding obs-tacles
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 17
Reconfigurable CPGs for an Adaptive Locomotion
Methodology
Methodology
It was divided into three phases:
CPG-based locomotion.
Visual perception and integration mechanism.
Embedded hardware implementation.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 18
Reconfigurable CPGs for an Adaptive Locomotion
Methodology
Phase 1: CPG-Based Locomotion
Phase 1: CPG-Based Locomotion
Oscillator modelselection.
Oscillator network(CPG) design.
CPG simulations.
Result analysis.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 19
Reconfigurable CPGs for an Adaptive Locomotion
Methodology
Phase 1: CPG-Based Locomotion
Phase 2: Visual Perception and Integration mechanism
Visual perception design.
Integration mechanism design.
Locomotion control assembly.
Locomotion control tests.
Result analysis.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 20
Reconfigurable CPGs for an Adaptive Locomotion
Methodology
Phase 1: CPG-Based Locomotion
Phase 3: Embedded Hardware Implementation
Hardware module designs.
Oscillator model.CPG-based locomotion.Integration mechanism.
Hardware module simulations.
Physical implementation.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 21
Reconfigurable CPGs for an Adaptive Locomotion
Methodology
Phase 1: CPG-Based Locomotion
Timeline of activities
year 2010 2011 2012 2013Activity Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3 Q1 Q2 Q3Selection, implementation,testing of oscillator model.
X X X
Design, implementationand testing of CPG (1).
X X X
Review of visual perception(PV) models
X X X
Implementation of PV mo-del (2)
X X X X
Design and implementa-tion of integration mecha-nism (3).
X X X X X
Design and hardware im-plementation of the modu-les.
1 1 1 3 3-3
2-3
2-3
Module integration in therobot platform based onFPGA.
X X X
Testing and result analysis. X X XCourses. SMR IDP RCPredoctoral and thesis dis-sertation.
P T
Publications. C J C C CH J/C J J
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 22
Reconfigurable CPGs for an Adaptive Locomotion
Conclusions
Conclusions
CPG is neural circuit capable to generate locomotion patternsfeasible to be used in robot locomotion.
CPGs are able to generate complex and adaptive locomotionbehaviors from manipulation of simple periodic signals.
The presented CPG-based controller will provide flexibility togenerate different rhythmic patterns, at runtime, suitable foradaptable locomotion for quadruped and hexapod robots.
The proposed embedded locomotion architecture will exploitthe distributed processing able to carry out in FPGA throughunits working in parallel and ensuring a real time response.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 23
Reconfigurable CPGs for an Adaptive Locomotion
Referencias
References I
P. Arena, L. Fortuna, Frasca, G. Sicurella. An adaptive, self-organizing dynamical system for hierarchical
control of bio-inspired locomotion. IEEE Transactions on Systems, Man and Cybernetics, Part B, 34(4),1823–1837 (2004)
Y.J. Lee, J. Lee, K. K. Kim, and J. Kim, Y.and Ayers. Low power cmos electronic central pattern generatordesign for a biomimetic underwater robot. Neurocomputing, 71:284–296, December 2007
A. J. Ijspeert and A. Crespi. Online trajectory generation in an amphibious snake robot using a lamprey-likecentral pattern generator model. In Proceedings of the 2007 IEEE International Conference on Robotics andAutomation (ICRA 2007), pages 262–268, 2007
P. Manoonpong. Neural Preprocessing and Control of Reactive Walking Machines: Towards Versatile
Artificial Perception-Action Systems (Cognitive Technologies). Springer-Verlag New York, Inc., Secaucus,NJ, USA, 2007.
C. P. Santos and V. Matos. CPG modulation for navigation and omnidirectional quadruped locomotion.
Robotics and Autonomous Systems, 60(6):912 – 927, 2012.
X. Li and L. Li. Efficient implementation of FPGA based central pattern generator using distributed
arithmetic. IEICE Electronics Express. 8 (21): 1848–1854, 2011.
M. A. Lewis. Perception Driven Robot Locomotion. Journal Robot Society of Japan, 20(3):51–56, 2002.
K. Nakada, T. Asai, and T. Amemiya. Analog cmos implementation of a neuromorphic oscillator withcurrent-mode low-pass filters. ISCAS 2005, pages 1923–1926, 2005.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 24
Reconfigurable CPGs for an Adaptive Locomotion
Referencias
References II
S. Inagaki, H. Yuasa, T. Suzuki, and T. Arai. Wave CPG model for autonomous decentralized multi-legged
robot: Gait generation and walking speed control. Robotics and Autonomous Systems, 54(2):118–126,2006. Intelligent Autonomous Systems.
H. Feng and R. Wang. Construction of central pattern generator for quadruped locomotion control. 2008
IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pages 979–984, 2008.
P. Arena, L. Fortuna, M. Frasca, and L. Patane. A cnn-based chip for robot locomotion control. Circuits
and Systems I: Regular Papers, IEEE Transactions on, 52(9):1862–1871, sept. 2005.
K. Matsuoka. Sustained oscillations generated by mutually inhibiting neurons with adaptation. Biological
Cybernetics, 52(6):367–376, October 1985
S. Amari. Characteristics of random nets of analog neuron-like elements. pages 55–69, 1988.
B. Van Der Pol and J. Van Der Mark. The heartbeat considered as a relaxation oscillation, and an electrical
model of the heart. 6:763Ű775, 1928.
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 25
Reconfigurable CPGs for an Adaptive Locomotion
Thanks
José Hugo Barrón Zambrano. Reconfigurable CPGs for an Adaptive Locomotion 26