分散モデル予測制御によるマルチエージェント点間遷移の軌道生成
Trajectory Generation for Multiagent Point-To-Point Transitions via Distributed Model Predictive Control
分散モデル予測制御に基づき、オンデマンド衝突回避を用いて複数エージェントの軌道を分散生成する手法を提案し、計算時間を85%以上削減、最大25機のクアッドロータで実証した。
著者: Carlos E. Luis, Angela P. Schoellig
分類: cs.RO, cs.MA
原文アブストラクト
This paper introduces a novel algorithm for multiagent offline trajectory generation based on distributed model predictive control. Central to the algorithm's scalability and success is the development of an on-demand collision avoidance strategy. By predicting future states and sharing this information with their neighbors, the agents are able to detect and avoid collisions while moving toward their goals. The proposed algorithm can be implemented in a distributed fashion and reduces the computation time by more than 85% compared to previous optimization approaches based on sequential convex programming, while only having a small impact on the optimality of the plans. The approach was validated both through extensive simulations and experimentally with teams of up to 25 quadrotors flying in confined indoor spaces.
