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Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization

Champagnie, Kale; Arvin, Farshad; Hu, Junyan

Authors

Kale Champagnie



Abstract

In this paper, we present GEM, a novel approach to online coverage path planning in which a swarm of homogeneous agents act to maximize the entropy of pheromone deposited within their environment. We show that entropy maximization (EM) coincides with many conventional goals in offline coverage path planning, while also generalizing to online settings. We first propose the concept of uniformity, which is a generalised metric that allows offline and online CPP approaches to be viewed through a unified lens. We then evaluate our approach by measuring the rate at which entropy is maximized within a variety of static and dynamic environments. Our experimental results demonstrate that GEM achieves state-of-the-art performance in online coverage, competitive with offline methods, despite requiring no direct communication among agents.

Citation

Champagnie, K., Arvin, F., & Hu, J. (in press). Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization. In 2024 IEEE International Conference on Industrial Technology (ICIT) (1-6)

Conference Name 2024 IEEE International Conference on Industrial Technology (ICIT)
Conference Location Bristol, UK
Start Date Mar 25, 2024
End Date Mar 27, 2024
Acceptance Date Jan 27, 2024
Deposit Date Apr 8, 2024
Pages 1-6
Book Title 2024 IEEE International Conference on Industrial Technology (ICIT)
Public URL https://durham-repository.worktribe.com/output/2379771
Publisher URL https://ieeexplore.ieee.org/xpl/conhome/1000355/all-proceedings