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Self-organising swarms of firefighting drones: Harnessing the power of collective intelligence in decentralised multi-robot systems

机译:自我组织的消防无人机:利用分散的多机器人系统中集体智能的力量

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Swarm intelligence (SI) is concerned with the collective behaviour that emerges from decentralised self-organising systems, whilst swarm robotics (SR) is an approach to the self-coordination of large numbers of simple robots which emerged as the application of SI to multi-robot systems. Given the increasing severity and frequency of occurrence of wildfires and the hazardous nature of fighting their propagation, the use of disposable inexpensive robots in place of humans is of special interest. This paper demonstrates the feasibility and potential of employing SR to fight fires autonomously, with a focus on the self-coordination mechanisms for the desired firefighting behaviour to emerge. Thus, an efficient physics-based model of fire propagation and a self-organisation algorithm for swarms of firefighting drones are developed and coupled, with the collaborative behaviour based on a particle swarm algorithm adapted to individuals operating within physical dynamic environments of high severity and frequency of change. Numerical experiments demonstrate that the proposed self-organising system is effective, scalable and fault-tolerant, comprising a promising approach to dealing with the suppression of wildfires - one of the world's most pressing challenges of our time. (C) 2019 Elsevier B.V. All rights reserved.
机译:群体智能(SI)涉及从分散的自组织系统出现的集体行为,而群体机器人学(SR)是一种自我协调的方法,这是大量简单机器人的态度,它被出现为SI对多种机器人系统。鉴于野火发生的严重程度和频率越来越大,抗击其传播的危险性,使用一次性廉价机器人代替人类是特殊的兴趣。本文展示了雇用SR自主战斗火灾的可行性和潜力,重点关注所需的消防行为的自我协调机制。因此,开发和耦合了一种有效的基于物理的火力传播模型和用于消防无人机的群体的自组织算法,其基于粒子群算法的协作行为适用于在高度严重性和频率的物理动态环境中运行的个体变化。数值实验表明,所提出的自组织系统是有效的,可扩展性和容错的容易耐受性,包括处理野火的抑制的有希望的方法 - 这是世界上最紧迫的挑战之一。 (c)2019 Elsevier B.v.保留所有权利。

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