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Distributed Multi-Coverage for Robot Swarms

This paper presents a distributed multi-coverage algorithm for drone swarms that ensures redundant coverage of critical assets using only local sensing and communication, without global coordination. It is accepted at ANTS 2026.

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Key points

  • Proposes a distributed multi-coverage algorithm that handles robot failures
  • Requires only local sensing and communication, no global planning
  • Accepted at the swarm intelligence conference ANTS 2026

Why it matters

This matters because proposes a distributed multi-coverage algorithm that handles robot failures.

Technical impact

May affect research directions, evaluation methods, open-source reproduction, and productization paths.

[2605.21686] Distributed Multi-Coverage for Robot Swarms

[Submitted on 20 May 2026]

Title:Distributed Multi-Coverage for Robot Swarms

View a PDF of the paper titled Distributed Multi-Coverage for Robot Swarms, by Mariem Guitouni and Aaron T. Becker

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Abstract:Autonomous drone swarms deployed for surveillance, environmental monitoring, and infrastructure inspection must maintain reliable coverage of critical assets despite robot failures. This requires multicoverage: each asset must be observed by multiple robots for redundancy, with coverage requirements varying by asset importance. While recent work has solved the centralized problem optimally using integer programming, practical deployments face constraints that demand distributed solutions: robots operate with limited communication ranges, onboard computation restricts global planning, and partial system failures must not cause mission abort. We present a distributed multicoverage algorithm for robot swarms operating with local sensing, local communication, and no global coordination.

Comments: Accepted at ANTS 2026 (International Conference on Swarm Intelligence), published by Springer Nature

Subjects:

Robotics (cs.RO)

Cite as: arXiv:2605.21686 [cs.RO]

(or arXiv:2605.21686v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2605.21686

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Mariem Guitouni [view email] [v1] Wed, 20 May 2026 19:43:41 UTC (347 KB)

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