A model predictive control approach for the Partner Ballroom Dance Robot

Gabriele Buondonno, Federico Patota, Hongbo Wang, Alessandro De Luca, Kazuhiro Kosuge

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

A model predictive controller is developed for following the position of a human dancer in robot ballroom dancing. The control design uses a dynamic model of a dancer, based on a variant of the so-called 3D Linear Inverted Pendulum Mode that includes also the swing foot. This model serves as a basis for a Kalman predictor of the human motion during the single-support phase, while a simpler kinematic technique is used during the double-support phase. The output of the prediction filter enables to design a Model Predictive Control (MPC) law, by recursively solving on line and within a preview window a convex linear-quadratic optimization problem, constrained by differential kinematic bounds on robot commands. Two different control strategies, either at the velocity or at the acceleration level, are proposed and compared in simulations and in actual experiments. Accurate and reactive behaviors are obtained by the ballroom robot follower, confirming the benefit of the predictive/filtering nature of a MPC approach to handle uncertainty of human intentions and noisy signals.

本文言語English
ホスト出版物のタイトル2015 IEEE International Conference on Robotics and Automation, ICRA 2015
出版社Institute of Electrical and Electronics Engineers Inc.
ページ774-780
ページ数7
June
ISBN(電子版)9781479969234
DOI
出版ステータスPublished - 2015 6月 29
外部発表はい
イベント2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
継続期間: 2015 5月 262015 5月 30

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
番号June
2015-June
ISSN(印刷版)1050-4729

Other

Other2015 IEEE International Conference on Robotics and Automation, ICRA 2015
国/地域United States
CitySeattle
Period15/5/2615/5/30

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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