走破不能領域を走破する：垂直に険しい地形における車輪移動のための走破性推定
Traverse the Non-Traversable: Estimating Traversability for Wheeled Mobility on Vertically Challenging Terrain
従来は走破不能とされた垂直に険しい地形を、過去の車両-地形間の動的相互作用データから走破可能と推定し、プランナを効率的に誘導する手法を提案。
著者: Chenhui Pan, Aniket Datar, Anuj Pokhrel, Matthew Choulas, Mohammad Nazeri, Xuesu Xiao
分類: cs.RO
原文アブストラクト
Most traversability estimation techniques divide off-road terrain into traversable (e.g., pavement, gravel, and grass) and non-traversable (e.g., boulders, vegetation, and ditches) regions and then inform subsequent planners to produce trajectories on the traversable part. However, recent research demonstrated that wheeled robots can traverse vertically challenging terrain (e.g., extremely rugged boulders comparable in size to the vehicles themselves), which unfortunately would be deemed as non-traversable by existing techniques. Motivated by such limitations, this work aims at identifying the traversable from the seemingly non-traversable, vertically challenging terrain based on past kinodynamic vehicle-terrain interactions in a data-driven manner. Our new Traverse the Non-Traversable(TNT) traversability estimator can efficiently guide a down-stream sampling-based planner containing a high-precision 6-DoF kinodynamic model, which becomes deployable onboard a small-scale vehicle. Additionally, the estimated traversability can also be used as a costmap to plan global and local paths without sampling. Our experiment results show that TNT can improve planning performance, efficiency, and stability by 50%, 26.7%, and 9.2% respectively on a physical robot platform.
