Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization

Champagnie, Kale; Arvin, Farshad; Hu, Junyan

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. (2024, March). Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization. Presented at 2024 IEEE International Conference on Industrial Technology (ICIT), Bristol, UK

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 IEEE International Conference on Industrial Technology (ICIT)
• Start Date: Mar 25, 2024
• End Date: Mar 27, 2024
• Acceptance Date: Jan 27, 2024
• Online Publication Date: Jun 5, 2024
• Publication Date: Jun 5, 2024
• Deposit Date: Apr 8, 2024
• Publicly Available Date: Jun 5, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Series ISSN: 2641-0184
• Book Title: 2024 IEEE International Conference on Industrial Technology (ICIT)
• ISBN: 9798350340273
• DOI: https://doi.org/10.1109/ICIT58233.2024.10540869
• Public URL: https://durham-repository.worktribe.com/output/2379771