Path Planning of Mobile Robots based on Improved Genetic Algorithm

Abstract

In this paper, the path planning algorithm is proposed based on the improved genetic algorithm. Firstly, the global environment for the grid model on mobile robot movement is built using the grid method. Then the classic genetic algorithm is applied into the grid map of path planning, and the gray wolf optimization algorithm is used into the grid map of path planning. Thereby, the genetic algorithm is optimized by gray wolf optimization and finally applied into path planning. The improved genetic algorithm is used into path planning of mobile robots and compared with the classic genetic algorithm and the gray wolf optimization algorithm. Finally, the simulation results confirm the improved algorithm has better convergence and effectiveness and is very valuable for path planning.