Comparative Study on the Performance of Heuristic Optimization Techniques in Robotic Path Planning

Abstract

This work presents a comparative study between the three popular optimization techniques namely the Genetic Algorithm (GA), Particle Swarm Optimization technique (PSO) and the Artificial Bee Colony (ABC) in the robotic path planning field. Path planning techniques suffer from a well-known trade-off between path quality and swiftness. Researchers had to always trade-off between shorter paths and higher computational execution time. However, with the invention of heuristic optimization techniques such as GA, PSO and ABC, there is an expect that these optimization techniques can overcome this trade-off. Thus, this paper investigates the performance of the three optimization techniques in robotic path planning problems.