A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse

doi:10.1109/TCYB.2024.3358739

	A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse
	Qin, Shijie 1,2; Li, Houcheng1,2 ; Cheng, Long1,2
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
ISSN	2168-2267
	2024-02-14
页码	12
通讯作者	Cheng, Long(long.cheng@ia.ac.cn)
摘要	In manufacturing, musculoskeletal robots have gained more attention with the potential advantages of flexibility, robustness, and adaptability over conventional serial-link rigid robots. Focusing on the fundamental lifting tasks, a hybrid controller is proposed to overcome control challenges of such robots for widely applications in industry. The metaverse technology offers an available simulated-reality-based platform to verify the proposed method. The hybrid controller contains two main parts. A muscle-synergy-based radial basis function (RBF) network is proposed as the feedforward controller, which is able to characterize the phasic and the tonic muscle synergies simultaneously. The adaptive dynamic programming (ADP) is applied as the feedback controller to address the optimal control problem. The actor-critic structure is applied in the ADP-based controller, where the critic network is trained to approximate the optimal performance index and the actor network is trained to compute the optimal muscle excitations. Furthermore, the convergence and stability of the ADP algorithm are also analyzed. Finally, experiments have been designed to verify the effectiveness of this hybrid controller on an upper limb musculoskeletal system, and the comparisons with other controllers are also illustrated. The results show that the proposed controller can obtain a satisfactory performance for lifting tasks.
关键词	Adaptive dynamic programming (ADP) brain-inspired method muscle synergy musculoskeletal system reinforcement learning (RL) tracking control
DOI	10.1109/TCYB.2024.3358739
关键词[WOS]	MUSCLE SYNERGIES ; LEARNING CONTROL ; TIME ; ARM ; COMBINATIONS ; SYSTEM
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China
项目资助者	National Key Research and Development Program of China
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:001164066000001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：1[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/173211/55662
专题	多模态人工智能系统全国重点实验室
通讯作者	Cheng, Long
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
第一作者单位	中国科学院自动化研究所
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	Qin, Shijie,Li, Houcheng,Cheng, Long. A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse[J]. IEEE TRANSACTIONS ON CYBERNETICS,2024:12.
APA	Qin, Shijie,Li, Houcheng,&Cheng, Long.(2024).A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse.IEEE TRANSACTIONS ON CYBERNETICS,12.
MLA	Qin, Shijie,et al."A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse".IEEE TRANSACTIONS ON CYBERNETICS (2024):12.