Estimation of human impedance and motion intention for constrained human-robot interaction

doi:10.1016/j.neucom.2019.07.104

	Estimation of human impedance and motion intention for constrained human-robot interaction
	Yu, Xinbo 1,2,3; Li, Yanan 4; Zhang, Shuang 1,2,3; Xue, Chengqian 1,2,3; Wang, Yu5
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
	2020-05-21
卷号	390 页码:268-279
通讯作者	Zhang, Shuang(zhangshuang.ac@gmail.com)
摘要	In this paper, a complete framework for safe and efficient physical human-robot interaction (pHRI) is developed for robot by considering both issues of adaptation to the human partner and ensuring the motion constraints during the interaction. We consider the robot's learning of not only human motion intention, but also the human impedance. We employ radial basis function neural networks (RBFNNs) to estimate human motion intention in real time, and least square method is utilized in robot learning of human impedance. When robot has learned the impedance information about human, it can adjust its desired impedance parameters by a simple tuning law for operative compliance. An adaptive impedance control integrated with RBFNNs and full-state constraints is also proposed in our work. We employ RBFNNs to compensate for uncertainties in the dynamics model of robot and barrier Lyapunov functions are chosen to ensure that full-state constraints are not violated in pHRI. Results in simulations and experiments show the better performance of our proposed framework compared with traditional methods. (C) 2019 Elsevier B.V. All rights reserved.
关键词	Human motion intention estimation Impedance learning Adaptive neural network control Full-state constraints Barrier Lyapunov functions
DOI	10.1016/j.neucom.2019.07.104
关键词[WOS]	NEURAL-NETWORK CONTROL ; NONLINEAR-SYSTEMS ; TRACKING CONTROL ; ARM IMPEDANCE ; DESIGN
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61873297] ; China Postdoctoral Science Foundation[2019T120048] ; China Postdoctoral Science Foundation[2018M630074] ; Fundamental Research Funds for the Central Universities[FRF-GF-18-027B] ; Beijing Science and Technology Project[Z181100003118006]
项目资助者	National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Fundamental Research Funds for the Central Universities ; Beijing Science and Technology Project
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000531728800007
出版者	ELSEVIER
引用统计	被引频次：27[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/173211/39465
专题	复杂系统认知与决策实验室_先进机器人复杂系统管理与控制国家重点实验室
通讯作者	Zhang, Shuang
作者单位	1.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 2.Univ Sci & Technol Beijing, Inst Artificial Intelligence, Beijing 100083, Peoples R China 3.Univ Sci & Technol Beijing, Key Lab Knowledge Automat Ind Proc, Minist Educ, Beijing 100083, Peoples R China 4.Univ Sussex, Dept Engn & Design, Brighton BN1 9RH, E Sussex, England 5.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Yu, Xinbo,Li, Yanan,Zhang, Shuang,et al. Estimation of human impedance and motion intention for constrained human-robot interaction[J]. NEUROCOMPUTING,2020,390:268-279.
APA	Yu, Xinbo,Li, Yanan,Zhang, Shuang,Xue, Chengqian,&Wang, Yu.(2020).Estimation of human impedance and motion intention for constrained human-robot interaction.NEUROCOMPUTING,390,268-279.
MLA	Yu, Xinbo,et al."Estimation of human impedance and motion intention for constrained human-robot interaction".NEUROCOMPUTING 390(2020):268-279.