A Taguchi-Based Heterogeneous Parallel Metaheuristic ACO-PSO and Its FPGA Realization to Optimal Polar-Space Locomotion Control of Four-Wheeled Redundant Mobile Robots

Abstract

This paper presents an efficient Taguchi-based heterogeneous parallel metaheuristic ant colony optimization (ACO)-particle swarm optimization (PSO), called THPACOPSO, and its field-programmable gate array (FPGA) realization to optimal polar-space locomotion control of four-wheeled redundant mobile robots. This THPACOPSO consists of one slave Taguchi-based ACO (TACO) and one slave Taguchi-based PSO (TPSO) along with a master communication operator in one chip using system-on-a-programmable chip (SoPC) methodology. This approach takes the advantages of the Taguchi quality method, ACO, PSO, parallel processing, and FPGA technique, thereby obtaining better population diversity, avoiding premature convergence and keeping parallelism. Experimental results and comparative works are conducted to present effective optimization and high accuracy of the proposed FPGA-based THPACOPSO locomotion controller for four-wheeled Swedish redundant mobile robots.