Learning to Assemble Noncylindrical Parts Using Trajectory Learning and Force Tracking

doi:10.1109/TMECH.2021.3110825

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 机器人应用与理论组

	Learning to Assemble Noncylindrical Parts Using Trajectory Learning and Force Tracking
	Su, Jianhua 2,3; Meng, Yan 1; Wang, Lili 1; Yang, Xu 2,3
刊名	IEEE-ASME TRANSACTIONS ON MECHATRONICS
	2021-09-20
页码	12
关键词	Force Trajectory Robots Task analysis Hidden Markov models Impedance Training Assembly skill impedance control learning from demonstration movement primitives (MPs)
ISSN号	1083-4435
DOI	10.1109/TMECH.2021.3110825
通讯作者	Su, Jianhua(jianhua.su@ia.ac.cn)
英文摘要	The purpose of this article is to teach a robot assembly skills from demonstrations, and we attempt to train both the trajectory and the insertion force simultaneously. We encode human demonstrations data via motion primitives and, then, generate a reference trajectory and a prescribed force profile for a new assembly task using the combination of the motion primitives. We then propose an adaptive impedance controller to track the prescribed force with unknown environment stiffness, where the impedance parameters are estimated by the optimal solution of an equivalent linearization model. Our approach combines adaptive impedance control techniques with learning from demonstration on the same that makes it tractable and applicable to a real robot. Experiments on several typical noncylindrical parts illustrate the efficiency of the proposed method.
资助项目	Beijing Natural Science Foundation[L201019] ; National Natural Science Foundation of China[91848109] ; Major Scientific and Technological Innovation Projects in Shandong Province[2019JZZY010430] ; Technology on Space Intelligent Control Laboratory[HTKJ2019KL502013]
WOS关键词	IMPEDANCE CONTROL ; TASKS
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000731658700001
资助机构	Beijing Natural Science Foundation ; National Natural Science Foundation of China ; Major Scientific and Technological Innovation Projects in Shandong Province ; Technology on Space Intelligent Control Laboratory
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/46773]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
通讯作者	Su, Jianhua
作者单位	1.Univ Chinese Acad Sci, Beijing 100864, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Su, Jianhua,Meng, Yan,Wang, Lili,et al. Learning to Assemble Noncylindrical Parts Using Trajectory Learning and Force Tracking[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2021:12.
APA	Su, Jianhua,Meng, Yan,Wang, Lili,&Yang, Xu.(2021).Learning to Assemble Noncylindrical Parts Using Trajectory Learning and Force Tracking.IEEE-ASME TRANSACTIONS ON MECHATRONICS,12.
MLA	Su, Jianhua,et al."Learning to Assemble Noncylindrical Parts Using Trajectory Learning and Force Tracking".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2021):12.