Generalizable and precise control based on equilibrium-point hypothesis for musculoskeletal robotic system | |
Wu, Yaxiong3; Chen, Jiahao2; Qiao, Hong1,2 | |
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. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论