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Multi-Agent Collaborative Path Planning Based on Staying Alive Policy
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-8235-2728
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-7631-002x
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-0126-1897
2020 (English)In: Robotics, E-ISSN 2218-6581, Vol. 9, no 4, article id 101Article in journal (Refereed) Published
Abstract [en]

Modern mobile robots tend to be used in numerous exploration and search and rescue applications. Essentially they are coordinated by human operators and collaborate with inspection or rescue teams. Over the time, robots became more advanced and capable for various autonomous collaborative scenarios. Recent advances in the field of collaborative exploration and coverage provide different approaches to solve this objective. Thus scope of this article is to present a novel collaborative approach for multi-agent coordination in exploration and coverage of unknown complex indoor environments. Fundamentally, the task of collaborative exploration can be divided into two core components. The principal one is a sensor based exploration scheme that aims to guarantee complete area exploration and coverage. The second core component proposed is a staying alive policy that takes under consideration the battery charge level limitation of the agents. From this perspective the path planner assigns feasible tasks to each of the agents, including the capability of providing reachable, collision free paths. The overall efficacy of the proposed approach was extensively evaluated by multiple simulation results in a complex unknown environments.

Place, publisher, year, edition, pages
MDPI, 2020. Vol. 9, no 4, article id 101
Keywords [en]
area coverage, boustrophedon motion, collaborative exploration, multi-agent, algorithmic robotics
National Category
Robotics and automation
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-81702DOI: 10.3390/robotics9040101ISI: 000601764600001Scopus ID: 2-s2.0-85097270481OAI: oai:DiVA.org:ltu-81702DiVA, id: diva2:1504656
Note

Validerad;2020;Nivå 2;2020-12-03 (marisr)

Available from: 2020-11-30 Created: 2020-11-30 Last updated: 2025-02-09Bibliographically approved

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Koval, AntonMansouri, Sina SharifNikolakopoulos, George

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