オフロード地形における走行可能性を考慮した長距離ナビゲーションのためのトポロジカルマッピング
Topological mapping for traversability-aware long-range navigation in off-road terrain
森林のようなオフロード環境で、視覚とGPSのみを用いて未知の地形を長距離計画・探索・制御する手法を提案。トポロジカルマップと走行可能性解析、目標条件付き行動クローニングを組み合わせ、未学習の森林400m²を自律探索した。
著者: Jean-François Tremblay, Julie Alhosh, Louis Petit, Faraz Lotfi, Lara Landauro, David Meger
分類: cs.RO
原文アブストラクト
Autonomous robots navigating in off-road terrain like forests open new opportunities for automation. While off-road navigation has been studied, existing work often relies on clearly delineated pathways. We present a method allowing for long-range planning, exploration and low-level control in unknown off-trail forest terrain, using vision and GPS only. We represent outdoor terrain with a topological map, which is a set of panoramic snapshots connected with edges containing traversability information. A novel traversability analysis method is demonstrated, predicting the existence of a safe path towards a target in an image. Navigating between nodes is done using goal-conditioned behavior cloning, leveraging the power of a pretrained vision transformer. An exploration planner is presented, efficiently covering an unknown off-road area with unknown traversability using a frontiers-based approach. The approach is successfully deployed to autonomously explore two 400 meters squared forest sites unseen during training, in difficult conditions for navigation.
