2012 12th International Conference on Control, Automation and SystemsOct. 17-21, 2012 in ICC, Jeju Island, Korea

Human Anthropomorphic Gripper as an Automation Tool

Alvaro Uribe1, Edgar Diaz2 and Hernando Leon3

1Multimedia Engineering, Mil. Nueva Granada University, Bogota, Colombia2Mechatroncis Engineering, Mil. Nueva Granada University, Bogota, Colombia

3Industrial Engineering, Mil. Nueva Granada University, Bogota, Colombia(Tel : +57 6500000; E-mail: (alvaro.uribe, hernando.leon)@unimilitar.edu.co)

Abstract: This paper presents the design, development and implementation of a 14 DOF human anthropomorphic pneu-matic gripper as a tool for teaching automation basics using pneumatics and PLCs. The dexterity of the human handallows several types of power and precision grasps for interacting with various scenarios, these features have inspired thedevelopment of robotics mimicking the human hand in applications such as collaborative robotics workcells, where eachfinger is an actuated mechanism with a specific task. Collaborative actions through pneumatic and PLC programmingbasics using this hand allows enhancing the user’s knowledge based on concepts and familiarity with the device. Thepneumatic hand can be used on site, with the user directly operating it, and offline with a virtual reality tool for offeringsimultaneous accessible devices when multiple users need the hand. Robotics currently assists training surgical proce-dures, manipulation of elements in hazardous environments for us, kinematics, dynamics and path planning simulationsfor various industrial processes, or as didactic tools for inspiring school students for working with robotics. The pneumatichand system is composed of an actuation, control and teleoperation subsystems, these interact for simulating the muscles,and the user’s inputs for executing the chosen tasks.

Keywords: Anthropomorphic, Gripper, Pneumatics, Virtual Reality.

1. INTRODUCTIONAs a result of features found in various species, sev-

eral researchers and developers have found inspiration inthese natural models (dams, submarines, airplanes andhumanoid, quadruped and insect-like robots)[1][2][3][4].The human body is no exception, the dexterity obtainedfrom the Degrees of Freedom (DOF), make our hands re-markable tools [5]. The relevance of tool for achievinggoals depends on how fit that tool is, similarly to the hu-man hand, in robotics, the equivalent is the gripper. Somegripper configurations resembling the human hand are se-rial mechanisms like jaws and three fingered grippes usedin several industrial applications for easing and improv-ing robot teleoperation[6][7][8][9][10][11]. Robots andgrippers are used for improving tasks in: welding, as-sembling, painting, assisting surgery and manipulationof delicate or hazardous materials [12]. With the con-tinuous development of robots, currently they are usedin many applications such as, teleoperation [13], offlineprogramming [14], hazardous environments or prehensiletasks [15], [16], as well as grasp planning [17], designvalidation [18] and assisting rehabilitation [19]. High-lighted developments in robotic hands have resulted inthe design and construction of experimental prototypessuch as the Stanford/JPL [20], the Utah/MIT [21], theTUAT/Karlsruhe [22], the DLR [23], and the Nasa Robo-naut [24] among several others [25]. Training of pneu-matic, hydraulic, mechanical or electric actuators, pro-grammable logic controllers (PLC) are benefiting fromeducational tools as these, allow optimizing the skills de-velopment time [26]. The training tools are constantlyevolving, a main feature of simulators is the availability

The authors would like to acknowledge the support of the Mil. NuevaGranada University under the research project ING724.

of a virtual device without needing the real one. Certainsolutions allow simulating offline queues for training andlearning where hardware limitations occur or, when val-idating processes is a requirement for avoiding damagesduring any practice. In this case, Virtual Reality (VR)increases robotics applications providing teaching aids inmedicine [27], virtual architecture representations [28],robotics engineering training [29], and educational gam-ing [30], among others.

This work proposes the design and implementation ofa pneumatic anthropomorphic robotic human-based handas an automation tool for practicing online and offlinepneumatics programming concepts using PLCs. The pa-per is organized as follows; in section II the human handkinematics is studied; in section III the mechanical andpneumatic design is presented. In section IV the offline-programming tool is described and implemented; in sec-tion V the results, and finally in section VI the discussionand future works are presented.

2. HAND ANALYSIS

The human hand is composed of twenty DOF that al-low us to perform several grasps for interacting with ourenvironment [26]. These DOF are the result of havingthe flexion/extension and adduction/abduction rotationsin each finger. In [31], Cutosky studied various grasp-ing techniques and classified them in precision and powergrasps. Most common grasped objects are based on pris-matic and circular shapes as shown in Figure 1, and themain differences between these are the number of fingersin contact that is applied on the object.

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Fig. 1 Common graspsTable 1 Finger Denavit-Hartenberg parameters

Phalanx alpha a theta dProximal 0 ap θp 0Medial 0 am θm 0Distal 0 ad θd 0

3. KINEMATICS ANALYSISThrough kinematics positions and orientations for

each finger can be calculated. Similarly to how we reachobjects from known shapes, where we rotate our fingersfor making an specific grasp, the forward kinematics sup-plies sufficient information for executing both power andprecision grasp tasks with the pneumatic hand. Each fin-ger can be analyzed as an open kinematic chain repre-sented by a serial mechanism modeled by three serialconnecting bars. The rotational and translational infor-mation for each link can be calculated through the ho-mogenous transform matrix analysis presented in Table 1,were ap, am, ad are the proximal, medial and distal pha-lanxes distances, and θp, θm, θd their corresponding ori-entations.

The homogeneous matrix (1) is obtained using theDenavit-Hartenberg notation [32], where i and j are thecoefficients for the current and next joint, so the matrix al-lows calculating each joint kinematics or the overall fromthe base of the pal to the tip of the finger. This methodwas preferred over the geometric analysis, as it allowsincreasing the number of DOF without recalculating thekinematics models, and as the maximum number of DOFare 19, when solving the equations the amount of multi-plied zeros does not affect the computing speed and pro-cessing, thus making it a suitable method.

j−1Tj =

Cθj −Cαj · Sθj Sαj · Sθj aj · CθjSθj Cαj · Cθj −Sαj · Cθj aj · Sθj0 Sαj Cαj dj0 0 0 1

,(1)

For validating the solution, the DH method imple-mented in [33] for use with hand-like grippers was ap-plied to the pneumatic hand, obtaining the model pre-sented in Figure 2, where the rotation of each phalanxis calculated by choosing the desired orientation for eachfinger accordingly to the object.

4. ANTHROPOMORPHIC ANDPNEUMATIC DESIGN

The pneumatic hand was designed mechanically con-sidering the human support or skeletal system, and pneu-

Fig. 2 Kinematics solution of a random grasp

matically based on the muscular system.

4.1 Support SystemThe design process started by modeling each of the

fingers phalanxes, this allowed us to focus on each of thejoints motion and actuation system. For mimicking thetendons, nylon strings attached to the pneumatic actua-tors located at the forearm of the robotics hand the mech-anism were configured for performing the extension andflexion rotations. The finger prototype and assembly ispresented in Figure 3. Given that the most significantmotions in grasping are the flexion and extension rota-tions, each finger abduction/adduction movements werenot considered. The CAD models not only serve for de-veloping the offline and VR module for the hand, but alsoas base for the rapid prototyping of the pieces.

Base joint

Phalanx joint

Flexion tendon

Extension tendon

Fig. 3 Finger prototype

In Figure 4 the designed device and its human counterpart are presented for highlighting their similarities. TheDOF of the pneumatic hand were reduced for only con-sidering the flexion/extension rotations, this simplifiedthe mechanism and allowed validating the suitability ofpneumatic muscles. These DOF simplifications improveand allow the development and implementation of a sim-ple mechanics and actuation system that complies withthe most common grasped shapes.

4.2 Pneumatic SystemPneumatic actuators were chose as suitable muscles

given their resemblance with how our muscles workthrough contraction and expansion for performing flex-ion/extension rotations of our limbs. The system was de-signed using Festo’s FC660PLC, which were preferredover direct current (DC) motors because of the con-venience for programming basic automation interactionwith PLCs for pneumatics training and familiarization.These actuators allow performing and controlling each

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Pneumatic Muscles

Support Hand

Pneumatic Connectors

3DOF Thumb

Finger

3 DOF Fingers

Flat Palm of Aluminum

Fig. 4 Designed pneumatic hand

of the finger’s flexion and extension rotations through itscontraction and expansion, thus reassembling the humanmotion when grasping different objects. The actuatormain components are presented in Figure 5.

fitting

aluminum

coupling

pneumatic

fiber

Fig. 5 Pneumatic Muscle and coupling

Each muscle is connected using nylon strings, com-posed of two sets of valves in communication with thecorresponding PLC outputs. The activation and controlof every single muscle is accomplished by controlling alogic sequence of instructions from the PLC. The handis powered with 24V and it can be controlled manuallyor by a continuous sequences via Ethernet protocols, thusallowing its online and offline programming. The sys-tem setup for the muscles and control (PLC) subsystemis presented in Figure 6.

Computer

PLC-660

Pneuma�c valves

Designed finger

with muscles

Pneuma�c

muscles

Fig. 6 Control and actuation squematics

5. OFFLINE PROGRAMMING -TELEOPERATION

A Java3D API implemented in [33] was chosen for us-ing with the designed pneumatic hand. In Java3D the vir-tual assembly is organized following a hierarchical order,then by defining the common base of all the components,the relations between each finger can be defined so theirpivots match the joints of the mechanical assembly. Thepalm of the anthropomorphic device is chosen as the basefor all fingers, from it each finger is a branch, and eachphalanx is located relatively to the branch’s origin pointon the palm. This guarantees that the virtual movementmatches the real motion of the pneumatic hand. Figure 7shows a representation on of such relations in the humanhand.

Fig. 7 Pivot hierarchy

5.1 Offline ProgrammingThe offline/online programming flowchart is presented

in Figure 8. The program follows an initial configurationstep where the 3D model is set up accordingly to its an-thropometric measurements and the Virtual Reality Mod-eling Language (VRML) model imported from the CADsoftware, this process guarantees that the virtual repre-sentation is visually and functionally the same as the realpneumatic hand. Then, the kinematics module reads theanthropometric data so its ready for calculating the po-sitions of each finger during the grasp execution. Oncethe user chooses wether is going to execute the offlineor online programming, each process if followed as pre-sented in Figure 8, where he identifies the shape, movethe fingers, execute and adjust the grasp and save the in-formation for posterior analysis or later execution.

6. EXPERIMENTAL RESULTSThe pneumatic anthropomorphic hand was assembled

and connected following the mechanic and pneumatic de-sign. The modularity of the parts allows its fast and sim-

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Fig. 8 Application flowchart

ple assembly along with easy maintenance when neces-sary. Each joint supports continuous motion so the deviceis physically adequate for training and teaching automa-tion basics. The mechanism and its pneumatics musclesare suitable for reproducing several types of grasps, fortesting it various shapes where programmed using differ-ent valve configurations, thus resulting in the finger posi-tions presented in Figure 9.

When choosing the Offline programming, the testsproved to be realistic as the virtual model moved as thereal pneumatic hand. Although the fingers were movedto several positions, the focus remained on the executionof the three most common grasps, planar, spherical andcylindrical. The navigation and button location gives theuser a comfortable environment for using the application.Figure 10 shows a screen capture of the application, pre-senting from left to right the predefined shape buttons,the 3D canvas and finally the single finger movement but-tons. Figure 10 also shows the pneumatic hand executingthe three main grasps with and without objects.

7. CONCLUSION AND FUTURE WORKS

The designed pneumatic hand proved to behave andmove similarly to its human counterpart. The pneumaticmuscles acted just as expected fulfilling their roll as suit-able actuator for performing extension and flexion rota-tions for generating several types of grasps for each fin-ger when grabbing an object. The use of simple program-ming allows newcomers to easily configure and manipu-late the devices applying basic automation concepts foronline and offline programming the hand. Another fea-ture to highlight is the low cost of this device, it madeit affordable as a laboratory tool that students can build,adjust, improve and customize by their own according totheir needs or imagination. The similarity with the hu-man hand was achieved thanks to the selected mechanism

Fig. 9 Executed grasps

as allowed us to concentrate the actuators in the forearmrather than with motors in the hand, that would have re-sulted in a bigger and less anthropomorphic device.

Along with the offline programming tool, the physicaldevice was successfully assembled proving its scalabilityand easy maintenance. Its programming allowed movingeach finger as an isolated mechanism or as a workcellwhen various fingers are needed according to the task athand. At this point, the device is suitable for teaching andexecuting several grasp types and for grabbing differentobjects using visual feedback for estimating how to grabthe targets without extreme force. The anthropomorphicmodel was successfully exported through VRML and thefiles successfully edited for working properly in Java 3Dfor programming the device. This allowed the successfulexecution and grasp of cylindrical, spherical and planarobjects, along with data for actuating the PLC.

Finally, the integration of the hardware with the of-fline tool allow users to practice CLP programming firstin a virtual environment without comprising the real de-vice while a larger number of users can practice with thevirtual hand while the real is being used. With this tool,users can relate to kinematics, biomechanics and CLPprogramming basics with tasks easily compare with thoseperformed with our hands. This integration allows havingan open platform for implementing further developmentsin areas such as control, computer vision, artificial intel-ligence and others.

Substantial work needs to be done in other to improveits control and grasping performance, so other DOF suchas the abduction/adduction rotations can be considered.

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Fig. 10 Virtual executed grasps

Further developments can be made by using 3D user in-terfaces such as the Wiimote, Kinect or haptic gloves forincreasing user immersion and interaction. Adding moreobjects for simulating interactions between the hand canenhance the virtual environment effectiveness.

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