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Conventional distributed approaches to coverage control may suffer from lackof convergence and poor performance, due to the fact that agents have limitedinformation, especially in non-convex discrete environments. To address thisissue, we extend the approach of [Marden 2016] which demonstrates how a limiteddegree of inter-agent communication can be exploited to overcome such pitfallsin one-dimensional discrete environments. The focus of this paper is onextending such results to general dimensional settings. We show that theextension is convergent and keeps the approximation ratio of 2, meaning thatany stable solution is guaranteed to have a performance within 50% of theoptimal one. We also show that the computational complexity and communicationcomplexity are both polynomial in the size of the problem. The experimentalresults exhibit that our algorithm outperforms several state-of-the-artalgorithms, and also that the runtime is scalable as per theory.

Is Limited Information Enough? An Approximate Multi-agent Coverage Control in Non-Convex Discrete Environments