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

This paper presents an experiment of clustering implemented at three different levels: in a hardware implementation, in a sensor-based simulation and in a probabilistic model. The experiment consists of small reactive autonomous robots gathering and clustering randomly distributed objects. It is shown that, while the behaviour of the real robots can be faithfully reproduced in a sensor-based simulation, the evolution of the cluster sizes is perfectly described, both qualitatively and quantitatively, by a simple probabilistic model. Rather than simulating robots moving within an environment, the probabilistic model represents the clustering activity as a sequence of probabilistic events during which cluster sizes can be modified depending on simple geometrical considerations. (C) 1999 Elsevier Science B.V. All rights reserved.