自己反省型地形認識適応による不整地オフロード走行の一貫性向上
Self-Reflective Terrain-Aware Robot Adaptation for Consistent Off-Road Ground Navigation
ロボットが自分の走行結果を振り返って地形や機体の変化に適応し、不整地でも計画通りの安定した走行制御を生成する手法を提案した。
著者: Sriram Siva, Maggie Wigness, John G. Rogers, Long Quang, Hao Zhang
分類: cs.RO, cs.LG
原文アブストラクト
Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response. When a robot operates in off-road field environments such as forests, the robot's actual behaviors often do not match its expected or planned behaviors, due to changes in the characteristics of terrains and the robot itself. Therefore, the capability of robot adaptation for consistent behavior generation is essential for maneuverability on unstructured off-road terrains. In order to address the challenge, we propose a novel method of self-reflective terrain-aware adaptation for ground robots to generate consistent controls to navigate over unstructured off-road terrains, which enables robots to more accurately execute the expected behaviors through robot self-reflection while adapting to varying unstructured terrains. To evaluate our method's performance, we conduct extensive experiments using real ground robots with various functionality changes over diverse unstructured off-road terrains. The comprehensive experimental results have shown that our self-reflective terrain-aware adaptation method enables ground robots to generate consistent navigational behaviors and outperforms the compared previous and baseline techniques.
