マルチ解像度3Dグリッド上での効率的な階層的任意角度経路計画
Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids
マルチ解像度の3Dボリュームマップを活用し、任意角度経路計画の最適性と完全性を保ちつつ計算効率を大幅に改善する手法を提案。実環境と合成環境での実験でサンプリングベース手法を上回る性能を示し、オープンソース化した。
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著者: Victor Reijgwart, Cesar Cadena, Roland Siegwart, Lionel Ott
分類: cs.RO, cs.AI
原文アブストラクト
Hierarchical, multi-resolution volumetric mapping approaches are widely used to represent large and complex environments as they can efficiently capture their occupancy and connectivity information. Yet widely used path planning methods such as sampling and trajectory optimization do not exploit this explicit connectivity information, and search-based methods such as A* suffer from scalability issues in large-scale high-resolution maps. In many applications, Euclidean shortest paths form the underpinning of the navigation system. For such applications, any-angle planning methods, which find optimal paths by connecting corners of obstacles with straight-line segments, provide a simple and efficient solution. In this paper, we present a method that has the optimality and completeness properties of any-angle planners while overcoming computational tractability issues common to search-based methods by exploiting multi-resolution representations. Extensive experiments on real and synthetic environments demonstrate the proposed approach's solution quality and speed, outperforming even sampling-based methods. The framework is open-sourced to allow the robotics and planning community to build on our research.
