Dynamic Waypoint Navigation: Model-Based Adaptive Trajectory Planner for Human-Symbiotic Mobile Robots

Mitsuhiro Kamezaki*, Ayano Kobayashi, Ryosuke Kono, Michiaki Hirayama, Shigeki Sugano

*この研究の対応する著者

研究成果: Article査読

抄録

Path planning in dynamic environments is still a challenging issue with autonomous mobile robots. Current methods lack adaptability to various passing scenarios, a variety of passing trajectories including an acceleration path, or immediacy in planning time, which require human-aware navigation. In this study, we propose Dynamic Waypoint Navigation (DWN), which is a model-based adaptive real-time trajectory planning method. DWN first predicts human-robot path interference and the time and position of the interference on the basis of the measured velocity of humans. It then dynamically designates several waypoints considering the time delay of both calculation time and robot travel time. Then, DWN generates several trajectories by combining different speeds (default, acceleration, and deceleration) and paths (default, right, and left) and selects the best trajectory in terms of an interference-avoidance energy cost based on the degree of velocity-vector change. DWN can also output a trajectory within 0.5 s to immediately adapt to changes in human behavior and adopt a simple mathematical model and algorithm to enable easy expansion. Simulation and experimental results reveal that the DWN can adequately select a time-efficient trajectory in real-time and adaptively change a trajectory depending on human movement.

本文言語English
ページ(範囲)81546-81555
ページ数10
ジャーナルIEEE Access
10
DOI
出版ステータスPublished - 2022

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 材料科学(全般)
  • 工学(全般)
  • 電子工学および電気工学

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