Bio-inspired robotic impedance adaptation for human-robot collaborative tasks  

作　　者：Chao ZENG Chenguang YANG Zhaopeng CHEN 

机构地区：[1]School of Automation Science and Engineering,South China University of Technology,Guangzhou 510641,China [2]TAMS Group,Informatics,University of Hamburg,Hamburg D22527,Germany

出　　处：《Science China(Information Sciences)》2020年第7期65-74,共10页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China(Grant Nos.61861136009,61811530281)。

摘　　要：To improve the robotic flexibility and dexterity in a human-robot collaboration task,it is important to adapt the robot impedance in a real-time manner to its partner’s behavior.However,it is often quite challenging to achieve this goal and has not been well addressed yet.In this paper,we propose a bio-inspired approach as a possible solution,which enables the online adaptation of robotic impedance in the unknown and dynamic environment.Specifically,the bio-inspired mechanism is derived from the human motor learning,and it can automatically adapt the robotic impedance and feedforward torque along the motion trajectory.It can enable the learning of compliant robotic behaviors to meet the dynamic requirements of the interactions.In order to validate the proposed approach,an experiment containing an anti-disturbance test and a human-robot collaborative sawing task has been conducted.

关 键 词：impedance learning biomimetic control human-robot collaboration 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]