騒音制限下のハイブリッド燃料無人航空機のためのマルチエージェント経路探索
Multi Agent Pathfinding for Noise Restricted Hybrid Fuel Unmanned Aerial Vehicles
ハイブリッド燃料ドローン群が場所ごとの騒音規制を守りつつ衝突せずに目的地へ向かう経路を、制約木探索とラベリングアルゴリズムで求める手法を提案した。
著者: Drew Scott, Satyanarayana G. Manyam, David W. Casbeer, Manish Kumar, Isaac E. Weintraub
分類: math.OC, cs.RO
原文アブストラクト
Multi Agent Path Finding (MAPF) seeks the optimal set of paths for multiple agents from respective start to goal locations such that no paths conflict. We address the MAPF problem for a fleet of hybrid-fuel unmanned aerial vehicles which are subject to location-dependent noise restrictions. We solve this problem by searching a constraint tree for which the subproblem at each node is a set of shortest path problems subject to the noise and fuel constraints and conflict zone avoidance. A labeling algorithm is presented to solve this subproblem, including the conflict zones which are treated as dynamic obstacles. We present the experimental results of the algorithms for various graph sizes and number of agents.
