Effectiveness Evaluation of Arm Usage for Human Quiet Standing Balance Recovery through Nonlinear Model Predictive Control

Keli Shen, Ahmed Chemori, Mitsuhiro Hayashibe

研究成果: Conference contribution

抄録

The computational study of human balance recovery strategy is crucial for revealing effective strategy in human balance rehabilitation and humanoid robot balance control. In this context, many efforts have been made to improve the ability of quiet standing human balance. There are three main strategies for human balance including (i) ankle, (ii) hip, and (iii) stepping strategies. Besides, arm usage was considered for balance control of human walking. However, there exist few works about effectiveness assessment of arm strategy for quiet standing balance recovery. In this paper, we proposed a nonlinear model predictive control (NMPC) for human balance control on a simplified model with sagittal arm rotation. Three case studies including (i) active arms, (ii) passive arms, and (iii) fixed arms were considered to discuss the effectiveness of arm usage for human balance recovery during quiet standing. Besides, the total root mean square (RMS) deviation of joint angles was computed as an index of human motion intensity quantification. The proposed solution has been implemented for a human-like balance recovery with arm usages during quiet standing under perturbation and shows the effectiveness of arm strategy.

本文言語English
ホスト出版物のタイトル2020 3rd International Conference on Control and Robots, ICCR 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ150-153
ページ数4
ISBN(電子版)9781728175621
DOI
出版ステータスPublished - 2020 12 26
イベント3rd International Conference on Control and Robots, ICCR 2020 - Tokyo, Japan
継続期間: 2020 12 262020 12 29

出版物シリーズ

名前2020 3rd International Conference on Control and Robots, ICCR 2020

Conference

Conference3rd International Conference on Control and Robots, ICCR 2020
CountryJapan
CityTokyo
Period20/12/2620/12/29

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Optimization

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