Intelligent motion controller design for four-wheeled omnidirectional mobile robots using hybrid GA-PSO algorithm

This paper presents an intelligent motion controller based on genetic algorithm (GA)-particle swarm optimization (PSO) hybrid metaheuristic algorithm for four-wheeled omnidirectional mobile robots. The optimal parameters of motion controller are obtained by minimizing the performance index using the proposed GA-PSO hybrid algorithm. GA has been combined with PSO in evolving new solutions by applying crossover and mutation operators on solutions constructed by particles. These optimal parameters are used in the GA-PSO motion controller to obtain better performance for four-wheeled omnidirectional mobile robots to achieve both trajectory tracking and stabilization. Simulation results are conducted to show the effectiveness and merit of the proposed hybrid GA-PSO intelligent motion controller for four-wheeled omnidirectional mobile robots.