Particle Swarm Optimization Applied to Intelligent Vehicles Squad Coordination

This paper presents the modeling, implementation and evaluation of the Particle Swarm Optimization (PSO) applied to intelligent vehicles group formation and coordination. The robotic task discussed in this paper is performed over a natural disaster scenario, simulated as a forest fire. The intelligent vehicles squad mission should surround the fire and avoid fire's propagation. Experiments have been carried out with several PSO parameter's variation (e.g. inertia, confidence, social models, swarm size) seeking to get the more efficient optimization for the formation of the group. This paper describes all performed experiments detailing all sets of parameters, including positive and negative results. The simulation's results showed that with an adequate set of parameters is possible to get satisfactory strategic positions for a multirobotic system's operation using PSO.