Uncertainty-aware Non-linear Model Predictive Control for Human-following Companion Robot

Shunichi Sekiguchi, Ayanori Yorozu, Kazuhiro Kuno, Masaki Okada, Yutaka Watanabe, Masaki Takahashi

研究成果: Conference contribution

抄録

For a companion robot that follows a person as an assistant, predicting human walking is important to produce a proactive movement that is helpful to maintain an appropriate area decided by the human personal space. However, fully trusting the prediction may result in obstructing human walking because it is not always accurate. Hence, we consider the estimation of uncertainty (i.e., entropy) of the prediction to enable the robot to move without causing overconfident motion and without being late for the person it follows. To consider this uncertainty of the prediction to the controller, we introduce a reliability value that changes based on the entropy of the prediction. This value expresses the extent the controller should trust the prediction result, and it affects the cost function of our controller. We propose an uncertainty-aware robot controller based on nonlinear model predictive control to realize natural human-followings. We found that our uncertainty-aware control system can produce an appropriate robot movement, such as not obstructing the human walking and avoiding delay, in both simulations using actual human walking data and real-robot experiments.

本文言語English
ホスト出版物のタイトル2021 IEEE International Conference on Robotics and Automation, ICRA 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ページ8316-8322
ページ数7
ISBN(電子版)9781728190778
DOI
出版ステータスPublished - 2021
イベント2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China
継続期間: 2021 5月 302021 6月 5

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
2021-May
ISSN(印刷版)1050-4729

Conference

Conference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
国/地域China
CityXi'an
Period21/5/3021/6/5

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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