Cooperative Control of Multiple Swarms of Mobile Robots with Communication Constraints

We study the effect of limited communication range and noise on the cooperative control of a group of swarms of mobile robots using the Particle Swarm Optimization algorithm. The advantage of multiple swarms is the parallel search for a common goal, in addition to the implicit parallelism built. in each independent swarm. We demonstrate the method on a problem where a group of swarms searches for multiple similar minima or multiple similar objects in a given domain of the plane. The algorithm is robust with respect to limited communication range for range values of more than 20% of the characteristic size of the domain. The method is applied to the problem of swarms formations, where several swarms of mobile robots are initially dispersed over a given domain in the plane. The formation of the group of swarms breaks down when the communication range is less than half the typical size of the formation.