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Deep and Decentralized Multi-Agent Coverage of a Target with Unknown Distribution

2023/07/10 by Hossein Rastgoftar, Rastgoftar, Hossein · 1 citation
Computer Science · #Distributed Control Multi-Agent Systems #FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2307.04407

openalex publication_date 2023/07/10 · openalex created_date 2023/07/12 · openalex updated_date 2026/07/28

Abstract

This paper proposes a new architecture for multi-agent systems to cover an unknowingly distributed fast, safely, and decentralizedly. The inter-agent communication is organized by a directed graph with fixed topology, and we model agent coordination as a decentralized leader-follower problem with time-varying communication weights. Given this problem setting, we first present a method for converting communication graph into a neural network, where an agent can be represented by a unique node of the communication graph but multiple neurons of the corresponding neural network. We then apply a mass-cetric strategy to train time-varying communication weights of the neural network in a decentralized fashion which in turn implies that the observation zone of every follower agent is independently assigned by the follower based on positions of in-neighbors. By training the neural network, we can ensure safe and decentralized multi-agent coordination of coverage control. Despite the target is unknown to the agent team, we provide a proof for convergence of the proposed multi-agent coverage method.

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