Modeling self-organized aggregation in swarm robotic systems

In this paper, we propose a model for the self-organized aggregation of a swarm of mobile robots. Specifically, we use a simple probabilistic finite state automata (PFSA) based aggregation behavior and analyze its performance using both a point-mass and a physics-based simulator and compare the results against the predictions of the model. The results show that the probabilistic model predictions match simulation results and PFSA-based aggregation behaviors with fixed probabilities are unable to generate scalable aggregations in low robot densities. Moreover, we show that the use of a leave probability that is inversely proportional to the square of the neighbor count (as an estimate of aggregate size) does not improve the scalability of the behavior.