A. Martinoli et al., Understanding collective aggregation mechanisms: From probabilistic modelling to experiments with real robots, ROBOT AUT S, 29(1), 1999, pp. 51-63
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.