Understanding collective aggregation mechanisms: From probabilistic modelling to experiments with real robots

This paper presents an experiment of clustering implemented at three differ ent levels: in a hardware implementation, in a sensor-based simulation and in a probabilistic model. The experiment consists of small reactive autonom ous robots gathering and clustering randomly distributed objects. It is sho wn that, while the behaviour of the real robots can be faithfully reproduce d in a sensor-based simulation, the evolution of the cluster sizes is perfe ctly described, both qualitatively and quantitatively, by a simple probabil istic model. Rather than simulating robots moving within an environment, th e probabilistic model represents the clustering activity as a sequence of p robabilistic events during which cluster sizes can be modified depending on simple geometrical considerations. (C) 1999 Elsevier Science B.V. All righ ts reserved.