グラフニューラルネットワークによるマルチロボットシステムの被覆制御
Coverage Control in Multi-Robot Systems via Graph Neural Networks
限られたセンシング範囲のロボット群が重要度の異なる領域を効率的に監視するため、ロボット間通信を活用したグラフニューラルネットワークベースの分散制御ポリシーを開発した。
著者: Walker Gosrich, Siddharth Mayya, Rebecca Li, James Paulos, Mark Yim, Alejandro Ribeiro, Vijay Kumar
分類: cs.RO
原文アブストラクト
This paper develops a decentralized approach to mobile sensor coverage by a multi-robot system. We consider a scenario where a team of robots with limited sensing range must position itself to effectively detect events of interest in a region characterized by areas of varying importance. Towards this end, we develop a decentralized control policy for the robots -- realized via a Graph Neural Network -- which uses inter-robot communication to leverage non-local information for control decisions. By explicitly sharing information between multi-hop neighbors, the decentralized controller achieves a higher quality of coverage when compared to classical approaches that do not communicate and leverage only local information available to each robot. Simulated experiments demonstrate the efficacy of multi-hop communication for multi-robot coverage and evaluate the scalability and transferability of the learning-based controllers.
