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Article Dans Une Revue Adaptive Behavior Année : 2023

A unifying method-based classification of robot swarm spatial self-organisation behaviours

Résumé

Self-organisation in robot swarms can produce collective behaviours, particularly through spatial self-organisation. For example, it can be used to ensure that the robots in a swarm move collectively. However, from a designer’s point of view, understanding precisely what happens in a swarm that allows these behaviours to emerge at the macroscopic level remains a difficult task. The same behaviour can come from multiple different controllers (ie the control algorithm of a robot) and a single controller can give rise to multiple different behaviours, sometimes caused by slight changes in self-organisation. To grasp the causes of these differences, it is necessary to investigate the relationships between the many methods of self-organisation that exist and the various behaviours that can be obtained. The work presented here addresses self-organisation in robot swarms by focusing on the main behaviours that lead to spatial self-organisation of the robots. First, we propose a unified definition of the different behaviours and present an original classification system highlighting ten self-organisation methods that each allow one or more behaviours to be performed. An analysis, based on this classification system, links the identified mechanisms with behaviours that could be considered as obtainable or not. Finally, we discuss some perspectives on this work, notably from the point of view of an operator or designer.
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Dates et versions

hal-04044975 , version 1 (24-03-2023)

Identifiants

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Aymeric Hénard, Jérémy Rivière, Etienne Peillard, Sébastien Kubicki, Gilles Coppin. A unifying method-based classification of robot swarm spatial self-organisation behaviours. Adaptive Behavior, 2023, pp.105971232311639. ⟨10.1177/10597123231163948⟩. ⟨hal-04044975⟩
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