Force control of a robot gripper featuring shape memory alloy actuators

In this paper, we present design of a gripper for a robot arm. Our research brings out a new driven mechanism with shape memory alloy instead of servo motor as our actuator, and also the gripper is equipped with a force sensor inside. The fuzzy sliding-mode method is our control rule, and furthermore there is an anti-slipping control rule to avoid grabbing unknown object with insufficient force. The whole control strategies are integrated into a Microchip dsPIC MCU with DSP core inside which is good at dealing with complicated float-point calculation. Gripper can change grabbing force in real-time based on fuzzy sliding-mode control due to different weight objects. Finally, we grab five different objects with our gripper to verify our control strategy in the experiment.

[1]  S. Nahavandi,et al.  Intuitive Haptic Control Surface for Mobile Robot Motion Control , 2008, 2008 IEEE International Workshop on Safety, Security and Rescue Robotics.

[2]  Shiuh Jer Huang,et al.  Intelligent Robotic Gripper Control Strategy , 2013 .

[3]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..

[4]  Ben Horan,et al.  Multi-point multi-hand haptic teleoperation of a mobile robot , 2009, RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication.

[5]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Shiuh Jer Huang,et al.  Distributed Control Intelligent Robotic Gripper , 2013 .

[7]  Kazuo Tanaka,et al.  Stability analysis and design of fuzzy control systems , 1992 .

[8]  J. Andrew Bagnell,et al.  Robust Object Grasping using Force Compliant Motion Primitives , 2012, Robotics: Science and Systems.

[9]  Szu-Chi Tien,et al.  Precision Positioning with Shape-Memory-Alloy Actuators , 2013 .

[10]  Wen Hsien Kao,et al.  Development of Active Rehabilitation Device of Hand Joint , 2012 .

[11]  Victor Etxebarria,et al.  Neural network-based micropositioning control of smart shape memory alloy actuators , 2008, Eng. Appl. Artif. Intell..

[12]  I. Mizumoto,et al.  Shape Memory Alloy Actuator with Simple Adaptive Control , 2007, Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007).

[13]  Martial Hebert,et al.  An integrated system for autonomous robotics manipulation , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Toshiaki Tsuji,et al.  Command recognition based on haptic information for a robot arm , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Kyoung Kwan Ahn,et al.  Modeling and control of shape memory alloy actuators using Preisach model, genetic algorithm and fuzzy logic , 2008 .

[16]  Shiuh Jer Huang,et al.  Embedded Force Control Gripper for Frangible Fruit Robotic Manipulation , 2013 .