Intelligent motion control for omnidirectional mobile robots using parallel ACO algorithm

This paper presents a parallel ACO (ant colony optimization) algorithm and its application to optimal motion controller design for omnidirectional mobile robots. Both parallel ACO (PACO) parameter tuner and motion controller are integrated in one FPGA (field programmable gate arrays) chip to efficiently construct an experimental omnidirectional mobile robot. The optimal parameters of the motion controller are obtained by minimizing the performance index using the proposed PACO algorithm. These optimal parameters are then employed in the PACO-based embedded motion controller to achieve trajectory tracking and stabilization with better performance. Experimental results are conducted to show the effectiveness and merit of the proposed PACO algorithm for omnidirectional mobile robots.