Recombinant Rule Selection in Evolutionary Algorithm for Fuzzy Path Planner of Robot Soccer

A rule selection scheme of evolutionary algorithm is proposed to design fuzzy path planner for shooting ability in robot soccer. The fuzzy logic is good for the system that works with ambiguous information. Evolutionary algorithm is employed to deal with difficulty and tediousness in deriving fuzzy control rules. Generic evolutionary algorithm, however, evaluate and select chromosomes which may include inferior genes, and generate solutions with uncertainty. To ameliorate this problem, we propose a recombinant rule selection method for gene level selection, which grades genes at the same position in the chromosomes and recombine new parent for next generation. The method was evaluated with application of designing the fuzzy path planner, where each fuzzy rule was encoded as a gene. Simulation and experimental results showed the effectiveness and the applicability of the proposed method.