  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.
