Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks

doi:10.1109/TSMC.2019.2920870

	Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks
	Yang, Chenguang 1; Peng, Guangzhu 2; Cheng, Long3,4 ; Na, Jing 5; Li, Zhijun 6
发表期刊	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
ISSN	2168-2216
	2021-05-01
卷号	51 期号:5 页码:3282-3292
通讯作者	Yang, Chenguang(cyang@ieee.org)
摘要	In this paper, a force sensorless control scheme based on neural networks (NNs) is developed for interaction between robot manipulators and human arms in physical collision. In this scheme, the trajectory is generated by using geometry vector method with Kinect sensor. To comply with the external torque from the environment, this paper presents a sensorless admittance control approach in joint space based on an observer approach, which is used to estimate external torques applied by the operator. To deal with the tracking problem of the uncertain manipulator, an adaptive controller combined with the radial basis function NN (RBFNN) is designed. The RBFNN is used to compensate for uncertainties in the system. In order to achieve the prescribed tracking precision, an error transformation algorithm is integrated into the controller. The Lyapunov functions are used to analyze the stability of the control system. The experiments on the Baxter robot are carried out to demonstrate the effectiveness and correctness of the proposed control scheme.
关键词	Robot sensing systems Force Robot kinematics Artificial neural networks Admittance Torque Admittance control error transformation force observer Kinect neural adaptive control neural networks (NNs) robot
DOI	10.1109/TSMC.2019.2920870
收录类别	SCI
语种	英语
资助项目	Engineering and Physical Sciences Research Council[EP/S001913] ; National Natural Science Foundation of China[61873268] ; National Natural Science Foundation of China[61633016] ; Beijing Municipal Natural Science Foundation[L182060]
项目资助者	Engineering and Physical Sciences Research Council ; National Natural Science Foundation of China ; Beijing Municipal Natural Science Foundation
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Cybernetics
WOS记录号	WOS:000640749000055
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：106[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44338
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Yang, Chenguang
作者单位	1.Univ West England, Bristol Robot Lab, Bristol BS16 1QY, Avon, England 2.Univ Macau, Fac Sci & Technol, Dept Comp & Informat Sci, Macau 999078, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 5.Kunming Univ Sci & Technol, Fac Mech & Elect Engn, Kunming 650500, Yunnan, Peoples R China 6.Univ Sci & Technol China, Dept Automat, Hefei 230026, Peoples R China
推荐引用方式 GB/T 7714	Yang, Chenguang,Peng, Guangzhu,Cheng, Long,et al. Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2021,51(5):3282-3292.
APA	Yang, Chenguang,Peng, Guangzhu,Cheng, Long,Na, Jing,&Li, Zhijun.(2021).Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,51(5),3282-3292.
MLA	Yang, Chenguang,et al."Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 51.5(2021):3282-3292.