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

文献类型：期刊论文

作者Wu, Yaxiong1; Chen, Jiahao2; Qiao, Hong2,3
刊名ROBOTIC INTELLIGENCE AND AUTOMATION
出版日期2024-06-11
页码9
关键词Musculoskeletal system Humanoid motion control Equilibrium-point hypothesis Muscle model
ISSN号2754-6969
DOI10.1108/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.
WOS关键词CROSS-BRIDGE MODEL ; DYNAMIC SIMULATIONS ; REACHING MOVEMENTS ; MUSCLE ; FORCE ; ARM ; CONTRACTION ; PARAMETERS ; SYNERGIES ; HEAT
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研究方向Automation & Control Systems ; Engineering
语种英语
WOS记录号WOS:001240943400001
出版者EMERALD GROUP PUBLISHING LTD
资助机构Major Project of Science and Technology Innovation ; National Natural Science Foundation of China (NSFC)
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.Univ Sci & Technol Beijing, Sch Mech Engn, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing, Peoples R China
3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, 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.

入库方式： OAI收割

来源：自动化研究所

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