Swarms of autonomous drones self-organised to fight the spread of wildfires

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    Abstract

    Swarm robotics and drone technology have progressed at an increasingly fast pace for the past two decades, extending their capabilities and the kinds of problems they can help tackle. Drones can now be equipped with a range of advanced devices and sensors which enable them to navigate remote areas and to operate in dangerous environments. Given the hazardous nature of the activity, fighting fires by means of disposable and relatively inexpensive robots in place of humans is of special interest. In addition, the use of fleets of decentralised cooperative and self-organising robots results in a robust and resilient system with collective decision-making which can cope with uncertainty, errors, and the failure or loss of a few non-essential units without jeopardising the mission. This paper comprises an initial proof of concept to demonstrate the feasibility and potential of employing swarm robotics to fight fires autonomously. Thus, an efficient yet realistic model of the spread of wildfires is developed, which is then coupled with a model of a fleet of self-organising drones whose coordination mechanism is based on a forgetful particle swarm algorithm.
    Original languageEnglish
    Title of host publicationProceedings of the GEOSAFE Workshop on Robust Solutions for Fire Fighting
    EditorsA. Navarra, G. Di Stefano
    PublisherCEUR
    Pages30-39
    Volume2146
    Publication statusPublished - 24 Jul 2018
    EventRSFF 2018 Robust Solutions for Fire Fighting: GEOSAFE Workshop on Robust Solutions for Fire Fighting - L'Aquila, Italy
    Duration: 19 Jul 201820 Jul 2018
    http://ceur-ws.org/Vol-2146/

    Conference

    ConferenceRSFF 2018 Robust Solutions for Fire Fighting
    CountryItaly
    CityL'Aquila
    Period19/07/1820/07/18
    Internet address

    Bibliographical note

    CEUR Workshop Proceedings (CEUR-WS.org) is a free open-access publication service at Sun SITE Central Europe operated under the umbrella of RWTH Aachen University. CEUR-WS.org is a recognized ISSN publication series, ISSN 1613-0073.

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