Generalizable and precise control based on equilibrium-point hypothesis for musculoskeletal robotic system

doi:10.1108/RIA-01-2024-0022

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

	Generalizable and precise control based on equilibrium-point hypothesis for musculoskeletal robotic system
	Wu, Yaxiong 3; Chen, Jiahao 2; Qiao, Hong 1,2
刊名	ROBOTIC INTELLIGENCE AND AUTOMATION
	2024-06-11
页码	9
关键词	Musculoskeletal system Humanoid motion control Equilibrium-point hypothesis Muscle model
ISSN号	2754-6969
DOI	10.1108/RIA-01-2024-0022
通讯作者	Qiao, Hong(hong.qiao@ia.ac.cn)
英文摘要	PurposeThe purpose of this study is realizing human-like motions and performance through musculoskeletal robots and brain-inspired controllers. Human-inspired robotic systems, owing to their potential advantages in terms of flexibility, robustness and generality, have been widely recognized as a promising direction of next-generation robots.Design/methodology/approachIn this paper, a deep forward neural network (DFNN) controller was proposed inspired by the neural mechanisms of equilibrium-point hypothesis (EPH) and musculoskeletal dynamics.FindingsFirst, the neural mechanism of EPH in human was analyzed, providing the basis for the control scheme of the proposed method. Second, the effectiveness of proposed method was verified by demonstrating that equilibrium states can be reached under the constant activation signals. Finally, the performance was quantified according to the experimental results.Originality/valueBased on the neural mechanism of EPH, a DFNN was crafted to simulate the process of activation signal generation in human motion control. Subsequently, a bio-inspired musculoskeletal robotic system was designed, and the high-precision target-reaching tasks were realized in human manner. The proposed methods provide a direction to realize the human-like motion in musculoskeletal robots.
资助项目	Major Project of Science and Technology Innovation[2030-Brain] ; Major Project of Science and Technology Innovation[2021ZD0200408] ; National Natural Science Foundation of China (NSFC)[91948303] ; National Natural Science Foundation of China (NSFC)[62203439] ; National Natural Science Foundation of China (NSFC)[62203443]
WOS关键词	CROSS-BRIDGE MODEL ; DYNAMIC SIMULATIONS ; REACHING MOVEMENTS ; MUSCLE ; FORCE ; ARM ; CONTRACTION ; PARAMETERS ; SYNERGIES ; HEAT
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	EMERALD GROUP PUBLISHING LTD
WOS记录号	WOS:001240943400001
资助机构	Major Project of Science and Technology Innovation ; National Natural Science Foundation of China (NSFC)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/58685]
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	Qiao, Hong
作者单位	1.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing, Peoples R China 3.Univ Sci & Technol Beijing, Sch Mech Engn, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wu, Yaxiong,Chen, Jiahao,Qiao, Hong. Generalizable and precise control based on equilibrium-point hypothesis for musculoskeletal robotic system[J]. ROBOTIC INTELLIGENCE AND AUTOMATION,2024:9.
APA	Wu, Yaxiong,Chen, Jiahao,&Qiao, Hong.(2024).Generalizable and precise control based on equilibrium-point hypothesis for musculoskeletal robotic system.ROBOTIC INTELLIGENCE AND AUTOMATION,9.
MLA	Wu, Yaxiong,et al."Generalizable and precise control based on equilibrium-point hypothesis for musculoskeletal robotic system".ROBOTIC INTELLIGENCE AND AUTOMATION (2024):9.