転倒を考慮した不整地自律ナビゲーションのための軌道最適化
Capsizing-Guided Trajectory Optimization for Autonomous Navigation with Rough Terrain
不整地での転倒リスクを解析し、安全な姿勢範囲を制約として組み込んだ軌道計画手法CAPを提案し、シミュレーションと実機実験で有効性を示した。
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著者: Wei Zhang, Yinchuan Wang, Wangtao Lu, Pengyu Zhang, Xiang Zhang, Yue Wang, Chaoqun Wang
分類: cs.RO
原文アブストラクト
It is a challenging task for ground robots to autonomously navigate in harsh environments due to the presence of non-trivial obstacles and uneven terrain. This requires trajectory planning that balances safety and efficiency. The primary challenge is to generate a feasible trajectory that prevents robot from tip-over while ensuring effective navigation. In this paper, we propose a capsizing-aware trajectory planner (CAP) to achieve trajectory planning on the uneven terrain. The tip-over stability of the robot on rough terrain is analyzed. Based on the tip-over stability, we define the traversable orientation, which indicates the safe range of robot orientations. This orientation is then incorporated into a capsizing-safety constraint for trajectory optimization. We employ a graph-based solver to compute a robust and feasible trajectory while adhering to the capsizing-safety constraint. Extensive simulation and real-world experiments validate the effectiveness and robustness of the proposed method. The results demonstrate that CAP outperforms existing state-of-the-art approaches, providing enhanced navigation performance on uneven terrains.
