Minimal Communication Strategies for Self-Organising Synchronisation Behaviours

The ability to synchronise the individual actions within large groups is an adaptive response observed in many biological systems. Indeed, synchrony can increase the efficiency of a group by maximising the global outcome or by minimising the interference among individuals. In any case, synchronisation appears desirable for a robotic system as it allows to coordinate through time the activities of the group. The main goal of the experiments presented in this paper is the study of self-organising synchronisation behaviours for a group of robots. To do so, we do not postulate the need of internal dynamics. Instead, we stress the importance of the dynamical coupling between robots and environment, which can be exploited for synchronisation, allowing to keep a minimal complexity of both the behavioural and the communication level. We use artificial evolution to synthesise the robot controllers, and we show how very simple communication strategies can produce self-organising synchronisation behaviours that scale to very large groups and that can be transfered to physical robots.