混雑度指標とボロノイ分割を用いた密環境マルチエージェント経路計画
Dense Multi-Agent Navigation Using Voronoi Cells and Congestion Metric-based Replanning
密集環境で複数の差動駆動ロボットを誘導する分散型経路計画を提案し、混雑度指標による再計画とボロノイセルで衝突を抑えつつ倉庫のような複雑な場面での成功率と効率を向上させた。
著者: Senthil Hariharan Arul, Dinesh Manocha
分類: cs.RO
原文アブストラクト
We present a decentralized path-planning algorithm for navigating multiple differential-drive robots in dense environments. In contrast to prior decentralized methods, we propose a novel congestion metric-based replanning that couples local and global planning techniques to efficiently navigate in scenarios with multiple corridors. To handle dense scenes with narrow passages, our approach computes the initial path for each agent to its assigned goal using a lattice planner. Based on neighbors' information, each agent performs online replanning using a congestion metric that tends to reduce the collisions and improves the navigation performance. Furthermore, we use the Voronoi cells of each agent to plan the local motion as well as a corridor selection strategy to limit the congestion in narrow passages. We evaluate the performance of our approach in complex warehouse-like scenes and demonstrate improved performance and efficiency over prior methods. In addition, our approach results in a higher success rate in terms of collision-free navigation to the goals.
