A Graph Robot Network for Force Observer of Teleoperation Systems

doi:10.1109/TMECH.2024.3402995

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 智能机器人系统研究

	A Graph Robot Network for Force Observer of Teleoperation Systems
	Pan, Ming-Zhang 1; Li, Jing-Ao 1; Li, Zhen2,3 ; Liang, Kun 1; Su, Tie-Cheng 1; Liang, Ke 1; Bian, Gui-Bin4
发表期刊	IEEE-ASME TRANSACTIONS ON MECHATRONICS
ISSN	1083-4435
	2024-06-05
页码	11
通讯作者	Bian, Gui-Bin(guibin.bian@ia.ac.cn)
摘要	Force information is crucial to teleoperation systems, which allows experts to perform tasks safely and reduces potential risks. However, due to the limitations of robot size and working environment, it is difficult to obtain contact force information through traditional force sensors. Therefore, this article proposes a graph robot network force observer, which can achieve sensorless force estimation without solving the robot dynamics. First, different association graphs are constructed according to the relative spatial position of the robot joints, establishing information transmission channels between each joint. Second, a neural reinforcement factor is introduced from robot joint motion information to enhance the feature information of different association subgraphs. Finally, a spatial and temporal feature fusion module is developed to extract and fuse both temporal and spatial information, which outputs the force information on the robot end effector along axes X, Y, and Z. Experiments in different environments and ablation experiments are carried out to verify the stability and generalization ability of the model. The experimental results show that the proposed force observer can accurately achieve the contact force between the robot and the object, and the proposed force observer achieves state-of-the-art performance compared with other algorithms.
关键词	Deep learning force observer master-slave robot teleoperation system
DOI	10.1109/TMECH.2024.3402995
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China
项目资助者	National Natural Science Foundation of China
WOS研究方向	Automation & Control Systems ; Engineering
WOS类目	Automation & Control Systems ; Engineering, Manufacturing ; Engineering, Electrical & Electronic ; Engineering, Mechanical
WOS记录号	WOS:001242965600001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/58749
专题	多模态人工智能系统全国重点实验室_智能机器人系统研究
通讯作者	Bian, Gui-Bin
作者单位	1.Guangxi Univ, Sch Mech Engn, Nanning 530004, Peoples R China 2.Tongji Univ, Sch Elect & Informat Engn, Shanghai 200092, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing 100190, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Pan, Ming-Zhang,Li, Jing-Ao,Li, Zhen,et al. A Graph Robot Network for Force Observer of Teleoperation Systems[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2024:11.
APA	Pan, Ming-Zhang.,Li, Jing-Ao.,Li, Zhen.,Liang, Kun.,Su, Tie-Cheng.,...&Bian, Gui-Bin.(2024).A Graph Robot Network for Force Observer of Teleoperation Systems.IEEE-ASME TRANSACTIONS ON MECHATRONICS,11.
MLA	Pan, Ming-Zhang,et al."A Graph Robot Network for Force Observer of Teleoperation Systems".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2024):11.