Adaptive-Constrained Impedance Control for Human-Robot Co-Transportation
文献类型:期刊论文
作者 | Yu, Xinbo1; Li, Bin1,6![]() ![]() |
刊名 | IEEE TRANSACTIONS ON CYBERNETICS
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出版日期 | 2021-09-24 |
页码 | 13 |
关键词 | Robots Robot sensing systems Task analysis Force Impedance Sensors Collaboration Error constraint human-robot co-transportation input constraint neural networks (NNs) vision and force sensing |
ISSN号 | 2168-2267 |
DOI | 10.1109/TCYB.2021.3107357 |
通讯作者 | He, Wei(weihe@ieee.org) |
英文摘要 | Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of applications raises a great number of theoretical and practical challenges arising mainly from the unknown human-robot interaction model as well as from the difficulty of accurately model the robot dynamics. In this article, an adaptive impedance controller for human-robot co-transportation is put forward in task space. Vision and force sensing are employed to obtain the human hand position, and to measure the interaction force between the human and the robot. Using the latest developments in nonlinear control theory, we propose a robot end-effector controller to track the motion of the human partner under actuators' input constraints, unknown initial conditions, and unknown robot dynamics. The proposed adaptive impedance control algorithm offers a safe interaction between the human and the robot and achieves a smooth control behavior along the different phases of the co-transportation task. Simulations and experiments are conducted to illustrate the performance of the proposed techniques in a co-transportation task. |
WOS关键词 | NONLINEAR-SYSTEMS ; TRACKING CONTROL ; NEURAL-CONTROL ; COLLABORATION ; MANIPULATION ; ADAPTATION ; DESIGN ; DELAY ; GAIT |
资助项目 | National Natural Science Foundation of China[62061160371] ; National Natural Science Foundation of China[U1913209] ; National Natural Science Foundation of China[62025307] ; National Natural Science Foundation of China[62073031] ; National Natural Science Foundation of China[62003032] ; China Postdoctoral Science Foundation[2020TQ0031] ; China Postdoctoral Science Foundation[2021M690358] ; Guangdong Basic and Applied Basic Research Foundation[2020B1515120071] ; Macao Science and Technology, Development Fund[FDCT/0031/2020/AFJ] ; University of Macau, Macau, China[MYRG2018-00198-FST] ; Fundacao para a Ciencia e a Tecnologia (FCT) through ISR LARSyS-FCT Project[UIDB/50009/2020] |
WOS研究方向 | Automation & Control Systems ; Computer Science |
语种 | 英语 |
WOS记录号 | WOS:000733560600001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
资助机构 | National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Guangdong Basic and Applied Basic Research Foundation ; Macao Science and Technology, Development Fund ; University of Macau, Macau, China ; Fundacao para a Ciencia e a Tecnologia (FCT) through ISR LARSyS-FCT Project |
源URL | [http://ir.ia.ac.cn/handle/173211/47142] ![]() |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
通讯作者 | He, Wei |
作者单位 | 1.Univ Sci & Technol Beijing, Inst Artificial Intelligence, Beijing 100083, Peoples R China 2.Univ Macau, Fac Sci & Technol, Dept Elect & Comp Engn, Taipa, Macau, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Peoples R China 6.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China |
推荐引用方式 GB/T 7714 | Yu, Xinbo,Li, Bin,He, Wei,et al. Adaptive-Constrained Impedance Control for Human-Robot Co-Transportation[J]. IEEE TRANSACTIONS ON CYBERNETICS,2021:13. |
APA | Yu, Xinbo,Li, Bin,He, Wei,Feng, Yanghe,Cheng, Long,&Silvestre, Carlos.(2021).Adaptive-Constrained Impedance Control for Human-Robot Co-Transportation.IEEE TRANSACTIONS ON CYBERNETICS,13. |
MLA | Yu, Xinbo,et al."Adaptive-Constrained Impedance Control for Human-Robot Co-Transportation".IEEE TRANSACTIONS ON CYBERNETICS (2021):13. |
入库方式: OAI收割
来源:自动化研究所
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