Effects of algorithmic parameters on swarm robotic search

As one of valid modeling and coordinated controlling tools, the particle swarm optimization algorithm can be extended for applying to task of swarm robotic search. To gain an insight into effects of key parameters on distributed swarm search, a series of simulations are conducted. In such control algorithm, main parameters including communication range, detection radius, and swarm size are paid close attentions. Similar to ideal “particles”, swarm robots are modeled at an abstract level with the extended particle swarm optimization method. Also, individual robots are designed to be controlled under three-state finite state machine mechanism having SingleSearch, SwarmSearch, and Declaration states. Then, control strategy and algorithm are developed. The statistical results from simulating data indicate the validity of modeling approach. Further, the effects of three parameters on overhead and efficiency of system running come out in compared analysis both of different size swarms and of specific size swarm.