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Learning Accurate and Stable Point-to-Point Motions: A Dynamic System Approach

文献类型：期刊论文

作者Zhang, Yu1,2; Cheng, Long1,2; Li, Houcheng1,2; Cao, Ran1,2
刊名IEEE ROBOTICS AND AUTOMATION LETTERS
出版日期2022-04-01
卷号7期号:2页码:1510-1517
关键词Point-to-point tasks neural network dynamic system generalization performance high dimensional data
ISSN号2377-3766
DOI10.1109/LRA.2022.3140677
通讯作者Cheng, Long(long.cheng@ia.ac.cn)
英文摘要This letter proposes a dynamic system approach to learn point-to-point motions while keeping the stability of the dynamic system. The proposed approach is grounded on a Learning from Demonstration (LfD) method based on a neural network, which gets a better reproduction performance while guaranteeing the generalization ability. The proposed approach has been experimentally validated on the LASA dataset and by the "pick-and-place" task of Franke Emika robot, and experimental results demonstrate that: (1) compared with the state-of-the-art results, the trajectory generated by the proposed approach achieves higher accuracy (approximately 24.79%) in terms of the similarity with respect to the demonstration; (2) the proposed approach can handle high dimensional data and learn from one or more demonstrations; (3) the proposed approach can guarantee the performance regardless of the variation of starting points even in the case of high dimensional complex motions.
WOS关键词MOVEMENT PRIMITIVES ; IMITATION ; TASK
资助项目National Natural Science Foundation of China[62025307] ; National Natural Science Foundation of China[U1913209] ; National Natural Science Foundation of China[61873013] ; Beijing Natural Science Foundation[JQ19020]
WOS研究方向Robotics
语种英语
WOS记录号WOS:000742721400003
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Beijing Natural Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/47051]  
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Cheng, Long
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Yu,Cheng, Long,Li, Houcheng,et al. Learning Accurate and Stable Point-to-Point Motions: A Dynamic System Approach[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2022,7(2):1510-1517.
APA Zhang, Yu,Cheng, Long,Li, Houcheng,&Cao, Ran.(2022).Learning Accurate and Stable Point-to-Point Motions: A Dynamic System Approach.IEEE ROBOTICS AND AUTOMATION LETTERS,7(2),1510-1517.
MLA Zhang, Yu,et al."Learning Accurate and Stable Point-to-Point Motions: A Dynamic System Approach".IEEE ROBOTICS AND AUTOMATION LETTERS 7.2(2022):1510-1517.

入库方式： OAI收割

来源：自动化研究所

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