制約環境における確率的軌道最適化を用いたエルゴディックカバレッジ
Ergodic Coverage In Constrained Environments Using Stochastic Trajectory Optimization
障害物や立入禁止領域のある環境で、目標発見確率に応じてロボットの滞在時間を配分するエルゴディックカバレッジを、確率的軌道最適化で実現し、異なるセンサを持つ複数ロボットの協調にも拡張した。
著者: Elif Ayvali, Hadi Salman, Howie Choset
分類: cs.RO
原文アブストラクト
In search and surveillance applications in robotics, it is intuitive to spatially distribute robot trajectories with respect to the probability of locating targets in the domain. Ergodic coverage is one such approach to trajectory planning in which a robot is directed such that the percentage of time spent in a region is in proportion to the probability of locating targets in that region. In this work, we extend the ergodic coverage algorithm to robots operating in constrained environments and present a formulation that can capture sensor footprint and avoid obstacles and restricted areas in the domain. We demonstrate that our formulation easily extends to coordination of multiple robots equipped with different sensing capabilities to perform ergodic coverage of a domain.
