Multi-hierarchy interaction control of a redundant robot using impedance learning

被引:14
|
作者
Jiang, Yiming [1 ,3 ]
Yang, Chenguang [2 ]
Wang, Yaonan [1 ]
Ju, Zhaojie [3 ]
Li, Yanan [4 ]
Su, Chun-Yi [5 ]
机构
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China
[2] Univ West England, Bristol Robot Lab, Bristol, Avon, England
[3] Univ Portsmouth, Sch Comp, Portsmouth PO1 3HE, Hants, England
[4] Univ Sussex, Sch Engn & Informat, Brighton BN1 9RH, E Sussex, England
[5] Concordia Univ, Gina Cody Sch Engn & Comp Sci, Montreal, PQ H3G 1M8, Canada
基金
英国工程与自然科学研究理事会;
关键词
Robot interaction control; Impedance control; Impedance parameters learning; Null space; Disturbance observer; SLIDING MODE CONTROL; PARALLEL MANIPULATOR; SPACE CONTROL; NULL-SPACE; FORCE; ACTUATION; DYNAMICS;
D O I
10.1016/j.mechatronics.2020.102348
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The control of robots with a compliant joint motion is important for reducing collision forces and improving safety during human robot interactions. In this paper, a multi-hierarchy control framework is proposed for the redundant robot to enable the robot end-effector to physically interact with the unknown environment, while providing compliance to the joint space motion. To this end, an impedance learning method is designed to iteratively update the stiffness and damping parameters of the end-effector with desired performance. In addition, based on a null space projection technique, an extra low stiffness impedance controller is included to improve compliant joint motion behaviour when interaction forces are acted on the robot body. With an adaptive disturbance observer, the proposed controller can achieve satisfactory performance of the end-effector control even with the external disturbances in the joint space. Experimental studies on a 7 DOF Sawyer robot show that the learning framework can not only update the target impedance model according to a given cost function, but also enhance the task performance when interaction forces are applied on the robot body.
引用
收藏
页数:14
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