Is Limited Information Enough? An Approximate Multi-agent Coverage Control in Non-Convex Discrete Environments
CoRR(2024)
摘要
Conventional distributed approaches to coverage control may suffer from lack
of convergence and poor performance, due to the fact that agents have limited
information, especially in non-convex discrete environments. To address this
issue, we extend the approach of [Marden 2016] which demonstrates how a limited
degree of inter-agent communication can be exploited to overcome such pitfalls
in one-dimensional discrete environments. The focus of this paper is on
extending such results to general dimensional settings. We show that the
extension is convergent and keeps the approximation ratio of 2, meaning that
any stable solution is guaranteed to have a performance within 50
optimal one. We also show that the computational complexity and communication
complexity are both polynomial in the size of the problem. The experimental
results exhibit that our algorithm outperforms several state-of-the-art
algorithms, and also that the runtime is scalable as per theory.
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