Intuitive human skill reconstruction for compliance control

Samuel Okodi, Xin Jiang, Satoko Abiko, Atsushi Konno, Masaru Uchiyama

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

This paper presents a robust and efficient method of generating manipulation motion skill for non-force-feedback high speed constrained compliant robot motion. Using a non-structured teaching environment, the inherent task in the captured demonstration force and position data is estimated and reconstructed from three sets of complimentary models, including analytical mathematical modelling, empirical modelling and human skill demonstration modelling. The approach addresses task specification accuracy deficiencies, and involves outward interface simplifications, with embedded rigorous analytical methodologies that enable users to realise complex and robust constrained compliant robot motion without dealing with the low level motion generation aspects. Function based task representation supports an intuitive approach to generate robust constrained motion by skill superimposition, as exemplified by peg-in-hole with crank turning.

本文言語English
ホスト出版物のタイトル2010 IEEE International Conference on Robotics and Automation, ICRA 2010
ページ5576-5581
ページ数6
DOI
出版ステータスPublished - 2010
外部発表はい
イベント2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK, United States
継続期間: 2010 5月 32010 5月 7

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
ISSN(印刷版)1050-4729

Other

Other2010 IEEE International Conference on Robotics and Automation, ICRA 2010
国/地域United States
CityAnchorage, AK
Period10/5/310/5/7

ASJC Scopus subject areas

  • ソフトウェア
  • 制御およびシステム工学
  • 人工知能
  • 電子工学および電気工学

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