SoPC-Based Parallel ACO Algorithm and its Application to Optimal Motion Controller Design for Intelligent Omnidirectional Mobile Robots

Abstract

This paper presents an embedded system-on-a-programmable-chip (SoPC)-based parallel ant colony optimization (ACO) algorithm and its application to optimal motion controller design for intelligent omnidirectional mobile robots. Both polar-space parallel ACO (PACO) parameter tuner and kinematic motion controller are integrated in one field programmable gate arrays chip to efficiently construct an intelligent omnidirectional mobile robot. The optimal parameters of the motion controllers are obtained by minimizing the performance index using the proposed SoPC-based PACO algorithm. These polar-space optimal parameters are then employed in the PACO-based embedded kinematic motion controller to achieve trajectory tracking and stabilization. Experimental results are conducted to show the effectiveness and merit of the proposed PACO algorithm for embedded controllers of omnidirectional mobile robots. These results indicate that the proposed PACO-based embedded optimal controller outperforms the nonoptimal controllers and the conventional genetic algorithm optimal controllers in polar coordinates.