A Multimodal Path Planning Approach to Human Robot Interaction Based on Integrating Action Modeling

Yosuke Kawasaki, Ayanori Yorozu, Masaki Takahashi, Enrico Pagello

研究成果: Article査読

3 被引用数 (Scopus)


To complete a task consisting of a series of actions that involve human-robot interaction, it is necessary to plan a motion that considers each action individually as well as in relation to the following action. We then focus on the specific action of “approaching a group of people” in order to accurately obtain human data that is used to make the performance of tasks involving interactions with multiple people more smooth. The movement depends on the characteristics of the important sensors used for the task and on the placement of people at and around the destination. Considering the multiple tasks and placement of people, the pre-calculation of the destinations and paths is difficult. This paper thus presents a system of navigation that can accurately obtain human data based on sensor characteristics, task content, and real-time sensor data for processes involving human-robot interaction (HRI); this method does not navigate specifically toward a previously determined static point. Our goal was achieved by using a multimodal path planning based on integration of action modeling by considering both voice and image sensing of interacting people as well as obstacle avoidance. We experimentally verified our method by using a robot in a coffee shop environment.

ジャーナルJournal of Intelligent and Robotic Systems: Theory and Applications
出版ステータスPublished - 2020 12月

ASJC Scopus subject areas

  • ソフトウェア
  • 制御およびシステム工学
  • 機械工学
  • 産業および生産工学
  • 人工知能
  • 電子工学および電気工学


「A Multimodal Path Planning Approach to Human Robot Interaction Based on Integrating Action Modeling」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。