Self-organised synchronisation is a common phenomenon observed in many natural and artificial systems: simple coupling rules at the level of the individual components of the system result in an overall coherent behaviour. Owing to these properties, synchronisation appears particularly interesting for swarm robotic systems, as it allows to robustly coordinate through time the activities of the group while keeping a minimal complexity of the individual controllers. The goal of the experiments presented in this paper is the study of self-organising synchronisation for robots that present an individual periodic behaviour. In order to design the robot controllers, we make use artificial evolution, which proves capable of synthesising minimal synchronisation strategies based on the dynamical coupling between robots and environment. The obtained results are analysed under a dynamical systems perspective, which allows us to uncover the evolved mechanisms and to predict the scalability properties of the self-organising synchronisation with respect to varying group size.
Self-Organising Sync in a Robotic Swarm. A Dynamical System View
Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America
IEEE transactions on evolutionary computation 13 (2009): 722–741. doi:10.1109/TEVC.2009.2015577
info:cnr-pdr/source/autori:Trianni, V. and Nolfi, S./titolo:Self-Organising Sync in a Robotic Swarm. A Dynamical System View/doi:10.1109/TEVC.2009.2015577/rivista:IEEE transactions on evolutionary computation/anno:2009/pagina_da:722/pagina_a:741/intervall