火星を踏破する：未知環境を効率的にナビゲートする協調的情報経路計画
Traversing Mars: Cooperative Informative Path Planning to Efficiently Navigate Unknown Scenes
偵察ロボット（例：ドローン）と追従ロボット（例：ローバー）が協力し、未知環境で追従ロボットの最小コスト経路を効率的に探索する情報経路計画フレームワークを提案。理論的保証と実験で既存手法より高速な経路発見と終了を実証。
著者: Friedrich M. Rockenbauer, Jaeyoung Lim, Marcus G. Müller, Roland Siegwart, Lukas Schmid
分類: cs.RO
原文アブストラクト
The ability to traverse an unknown environment is crucial for autonomous robot operations. However, due to the limited sensing capabilities and system constraints, approaching this problem with a single robot agent can be slow, costly, and unsafe. For example, in planetary exploration missions, the wear on the wheels of a rover from abrasive terrain should be minimized at all costs as reparations are infeasible. On the other hand, utilizing a scouting robot such as a micro aerial vehicle (MAV) has the potential to reduce wear and time costs and increasing safety of a follower robot. This work proposes a novel cooperative IPP framework that allows a scout (e.g., an MAV) to efficiently explore the minimum-cost-path for a follower (e.g., a rover) to reach the goal. We derive theoretic guarantees for our algorithm, and prove that the algorithm always terminates, always finds the optimal path if it exists, and terminates early when the found path is shown to be optimal or infeasible. We show in thorough experimental evaluation that the guarantees hold in practice, and that our algorithm is 22.5% quicker to find the optimal path and 15% quicker to terminate compared to existing methods.
