多層マップ構築による3D環境での効率的な軌道生成
Efficient Trajectory Generation in 3D Environments with Multi-Level Map Construction
点群入力から三角形パッチベースの多層マップを構築し、運動プリミティブ探索と曲率・平滑性・障害物項を含む最適化により、ノイズに強く高速な地上ロボットの大域軌道を生成するフレームワークを提案。
著者: Chengkun Tian, Xiaohui Gao, Yongguang Liu
分類: cs.RO
原文アブストラクト
We propose a robust and efficient framework to generate global trajectories for ground robots in complex 3D environments. The proposed method takes point cloud as input and efficiently constructs a multi-level map using triangular patches as the basic elements. A kinematic path search is adopted on the patches, where motion primitives on different patches combine to form the global min-time cost initial trajectory. We use a same-level expansion method to locate the nearest obstacle for each trajectory waypoint and construct an objective function with curvature, smoothness and obstacle terms for optimization. We evaluate the method on several complex 3D point cloud maps. Compared to existing methods, our method demonstrates higher robustness to point cloud noise, enabling the generation of high quality trajectory while maintaining high computational efficiency. Our code will be publicly available at https://github.com/ck-tian/MLMC-planner.