Learning arm motion strategies for balance recovery of humanoid robots

Masaki Nakada*, Brian Allen, Shigeo Morishima, Demetri Terzopoulos

*この研究の対応する著者

研究成果: Conference contribution

10 被引用数 (Scopus)

抄録

Humans are able to robustly maintain balance in the presence of disturbances by combining a variety of control strategies using posture adjustments and limb motions. Such responses can be applied to balance control in two-armed bipedal robots. We present an upper-body control strategy for improving balance in a humanoid robot. Our method improves on lowerbody balance techniques by introducing an arm rotation strategy (ARS). The ARS uses Q-learning to map sensed state to the appropriate arm control torques. We demonstrate successful balance in a physically-simulated humanoid robot, in response to perturbations that overwhelm lower-body balance strategies alone.

本文言語English
ホスト出版物のタイトルProceedings - EST 2010 - 2010 International Conference on Emerging Security Technologies, ROBOSEC 2010 - Robots and Security, LAB-RS 2010 - Learning and Adaptive Behavior in Robotic Systems
ページ165-170
ページ数6
DOI
出版ステータスPublished - 2010 12月 1
イベント2010 International Conference on Emerging Security Technologies, EST 2010, Robots and Security, ROBOSEC 2010, Learning and Adaptive Behavior in Robotic Systems, LAB-RS 2010 - Canterbury, United Kingdom
継続期間: 2010 9月 62010 9月 8

出版物シリーズ

名前Proceedings - EST 2010 - 2010 International Conference on Emerging Security Technologies, ROBOSEC 2010 - Robots and Security, LAB-RS 2010 - Learning and Adaptive Behavior in Robotic Systems

Conference

Conference2010 International Conference on Emerging Security Technologies, EST 2010, Robots and Security, ROBOSEC 2010, Learning and Adaptive Behavior in Robotic Systems, LAB-RS 2010
国/地域United Kingdom
CityCanterbury
Period10/9/610/9/8

ASJC Scopus subject areas

  • 人工知能
  • 人間とコンピュータの相互作用
  • 制御およびシステム工学

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