最適輸送理論を用いた未知環境における経路計画
Path Planning in Unknown Environments Using Optimal Transport Theory
最適輸送理論に着想を得て、未知障害物環境でグラフと経路を反復更新しながら完全な経路計画を行う手法を提案し、高次元問題でも有効性を示した。
著者: Haoyan Zhai, Magnus Egerstedt, Haomin Zhou
分類: math.OC, cs.RO
原文アブストラクト
This paper introduces a graph-based, potential-guided method for path planning problems in unknown environments, where obstacles are unknown until the robots are in close proximity to the obstacle locations. Inspired by optimal transport theory, the proposed method generates a graph connecting the initial and target configurations, and then finds a path over the graph using the available environmental information. The graph and path are updated iteratively when newly encountered obstacle information becomes available. The resulting method is a deterministic procedure proven to be complete, i.e., it is guaranteed to find a feasible path, when one exists, in a finite number of iterations. The method is scalable to high-dimensional problems. In addition, our method does not search the entire domain for the path, instead, the algorithm only explores a sub-region that can be described by the evolution of the Fokker-Planck equation. We demonstrate the performance of our algorithm via several numerical examples with different environments and dimensions, including high-dimensional cases.
