Constructing Constraint Force Field in Musculoskeletal Robot by Co-optimizing Muscle Arrangements and Constant Activations
Zhong SL(钟汕林)1,2; Zhou JJ(周俊杰)1,2; Wu W(吴伟)1,2
2022-07-18
会议名称International Joint Conference on Neural Networks
会议日期2022-7-18
会议地点PADUA,Italy
摘要

  Robots with high-precision motion and operation ability are of great application significance. By referring to the biomechanical structure and neural control mechanism of human motion system, the research of musculoskeletal robot system with rigid-flexible coupling characteristics is one of the important ways to improve the operation flexibility and control robustness of robot. Inspired by the equilibrium point hypothesis proposed in neuroscience, this paper proposes a co-optimization algorithm of muscle arrangement and activation to construct constraint force field in the workspace of musculoskeletal robot. When the muscle arrangement is rough due to the insufficient precision of the mechanical structure, the musculoskeletal robot can maintain accurate motion with the help of constraint force field by adopting the optimized constant activation. Experiments are carried out on a musculoskeletal robot model with human-mimetic muscle to demonstrate the effectiveness of the proposed algorithm in movement accuracy, noise robustness and generalization. This work may be of great significance for the further introduction of constraint force field into hardware system of musculoskeletal robot.

关键词Musculoskeletal robot Constraint Force Field High precision Control Schemes of robot
收录类别EI
资助项目Strategic Priority Research Program of Chinese Academy of Science[XDB32050100]
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/48644
专题多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者Wu W(吴伟)
作者单位1.State Key Laboratory of Management and Control for Complex System, Institute of Automation, Chinese Academy of Science, Beijing 100190, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
推荐引用方式
GB/T 7714
Zhong SL,Zhou JJ,Wu W. Constructing Constraint Force Field in Musculoskeletal Robot by Co-optimizing Muscle Arrangements and Constant Activations[C],2022.
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