樹冠上空の航空LiDARマップを活用した森林下ナビゲーション
Under-Canopy Navigation using Aerial Lidar Maps
上空から取得したLiDARスキャンで不確かさを考慮した3D確率占有マップを作り、障害リスクを組み込んだコスト関数とD* Liteで地上ロボットの森林内経路計画・再計画を行う手法を提案した。
著者: Lucas Carvalho de Lima, Nicholas Lawrance, Kasra Khosoussi, Paulo Borges, Michael Bruenig
分類: cs.RO
原文アブストラクト
Autonomous navigation in unstructured natural environments poses a significant challenge. In goal navigation tasks without prior information, the limited look-ahead of onboard sensors utilised by robots compromises path efficiency. We propose a novel approach that leverages an above-the-canopy aerial map for improved ground robot navigation. Our system utilises aerial lidar scans to create a 3D probabilistic occupancy map, uniquely incorporating the uncertainty in the aerial vehicle's trajectory for improved accuracy. Novel path planning cost functions are introduced, combining path length with obstruction risk estimated from the probabilistic map. The D-Star Lite algorithm then calculates an optimal (minimum-cost) path to the goal. This system also allows for dynamic replanning upon encountering unforeseen obstacles on the ground. Extensive experiments and ablation studies in simulated and real forests demonstrate the effectiveness of our system.
