Path Planning for a Mobile Robot using Genetic Algorithm and Artificial Bee Colony

Abstract

This article presents a comparison of two meta-heuristics techniques a) Artificial Bees Colony (ABC), and b) Genetic Algorithm (AG), for path planning problems. To validate the algorithms ten 2D maps were used each with different obstacles number and geometry. Results were compared according to the following measurements: 1) performance time and 2) length of the way. Results of the simulation show that the ABC algorithm is effective in finding the path in less time, and can be used for the implementation of a mobile robot in execution time.