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

Mauro Sebastián Innocente; Paolo Grasso

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

Mauro Sebastián Innocente, Paolo Grasso

Institute for Future Transport and Cities

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

307 Downloads (Pure)

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 language	English
Title of host publication	Proceedings of the GEOSAFE Workshop on Robust Solutions for Fire Fighting
Publisher	CEUR
Volume	2146
Publication status	Published - 24 Jul 2018
Event	RSFF 2018 Robust Solutions for Fire Fighting: GEOSAFE Workshop on Robust Solutions for Fire Fighting - L'Aquila, Italy Duration: 19 Jul 2018 → 20 Jul 2018 http://ceur-ws.org/Vol-2146/

Conference

Conference	RSFF 2018 Robust Solutions for Fire Fighting
Country	Italy
City	L'Aquila
Period	19/07/18 → 20/07/18
Internet address	http://ceur-ws.org/Vol-2146/

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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Innocente & Grasso (2018) - Swarm of autonomous drones self-organised to fight wildfiresFinal published version, 813 KBLicence: CC BY-NC
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Innocente & Grasso (2018) - Swarm of autonomous drones self-organised to fight wildfiresFinal published version, 816 KB

http://ceur-ws.org/Vol-2146/

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Cite this

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title = "Swarm of autonomous drones self-organised to fight the spread of wildfires",

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.",

author = "Innocente, {Mauro Sebasti{\'a}n} and Paolo Grasso",

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.; RSFF 2018 Robust Solutions for Fire Fighting : GEOSAFE Workshop on Robust Solutions for Fire Fighting ; Conference date: 19-07-2018 Through 20-07-2018",

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AU - Innocente, Mauro Sebastián

AU - Grasso, Paolo

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N2 - 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.

AB - 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.

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