Path Planning for Mobile Robot Based on Improved Genetic Algorithm

Abstract

To deal with these issues such as low initial population quality and slow convergence in the traditional algorithm, this article improves the genetic algorithm and applies it to the path planning for mobile robot. In order to improve the quality of the initial pathways, it generates paths via heuristic strategies; The fitness function is improved by a multi-objective function. The main operators of the algorithm are improved in this article, and the numerical values of crossover and mutation probabilities are adjusted by an adaptive adjustment method to better fit the problem. A catastrophe factor is also introduced to increase the diversity of algorithms and the ability to search globally. (Abstract)