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Human-inspired motion model of upper-limb with fast response and learning ability - A promising direction for robot system and control

  • Hong Qiao
  • , Chuan Li
  • , Peijie Yin
  • , Wei Wu
  • , Zhi Yong Liu
  • Chinese Academy of Sciences
  • CAS - Institute of Applied Mathematics

科研成果: 期刊稿件文章同行评审

35 引用 (Scopus)

摘要

Purpose - Human movement system is a Multi-DOF, redundant, complex and nonlinear system formed by coordinating combination of neural system, bones, muscles and joints, which is robust and has fast response and learning ability. Imitating human movement system can improve robustness, fast response and learning ability of the robots. Design/methodology/approach - In this paper, we propose a new motion model based on the human motion pathway, especially the information propagation mechanism between the cerebellum and spinal cord. Findings - The proposed motion model proves to have fast response and learning ability through experiments, which matches the features of human motion. Originality/value - The proposed model in this paper introduces the habitual theory in kinesiology and neuroscience into robot control, and improves robustness, fast response and learning ability of the robots. This paper proves that introduction of neuroscience has an important guiding significance for precise and adaptive robot control, such as assembly automation.

源语言英语
页(从-至)97-107
页数11
期刊Assembly Automation
36
1
DOI
出版状态已出版 - 1 2月 2016
已对外发布

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