Impedance Identification Using Tactile Sensing and Its Adaptation for an Underactuated Gripper Manipulation
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Underactuated gripper has a broad application in the field of space robot and industrial robot because of its better shape-adaptation. However, because of the underactuated characteristics, it is a great challenge to accurately obtain the displacement of the contact point between the finger and grasped object, which makes it difficult to control the gripper grasp stably, especially the environmental parameters are unknown. This paper develops the identification of the unknown environmental parameters using a tactile array sensor based on the recursive leastsquares (RLS) method. The unknown environments are described as linear systems with unknown dynamics, and the environmental parameters are identified using the measured contact force and the derived displacement of the contact point which is obtained through the underactuated gripper dynamics. Meanwhile, an impedance adaptive control is presented to match the variability of the environment parameters, and the desired impedance model is imposed to the underactuated gripper to achieve stable grasp. A cost function that measures the contact force, velocity and displacement error is defined, and the critical impedance parameters are found to minimize it. At last, a co-simulation of ADAMS and MATLAB for an underactuated gripper grasp is implemented to show the feasibility of environmental parameters identification and its adaptive method.
KeywordsEnvironmental parameters identification impedance adaptation stable grasp underactuated gripper
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- L. Birglen and C. M. Gosselin, “On the force capability of underactuated fingers,” Proc. of IEEE Int. Conf. on Robotics and Automation, 2003.Google Scholar
- L. Odhner and A. Dollar, “Dexterous manipulation with underactuated elastic hands,” Proc. IEEE Int. Conf. Robot. Autom., Karlsruhe, Germany, pp. 5254–5260, May 2011.Google Scholar
- R. Ma, H. P. Liu, F. C. Sun, Q. F. Yang, and M. Gao, “Linear dynamic system method for tactile object classification,” Science in China. Series F: Information Sciences, vol. 57, no. 12, pp. 1–11, December 2014.Google Scholar
- M. Salehi and G. Vossoughi, “Impedance control of flexible base mobile manipulator using singular perturbation method and sliding mode control law,” International Journal of Control, Automation, and Systems, vol. 6, no. 5, pp. 677–688, October 2008.Google Scholar
- L. Biagiotti, H. Liu, G. Hirzinger, and C. Melchiorri, “Cartesian impedance control for dexterous manipulation,” Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Las Vegas, Nevada, October 2003.Google Scholar
- Z. Y. Chu, J. Hu, and Y. A. Lei, An Adaptive Gripper of Space Robot for Space On-orbit Services, CN 201310326633.7, 2013, China patent.Google Scholar
- M. Zhou and Z. Y. Chu, “Impedance joint torque control of an active-passive composited driving self-adaptive end effector for space manipulator,” Proc. of the 11th World Congress on Intelligent Control and Automation, Shenyang, China, June 29-July 4 2014.Google Scholar