Path planning method based on neural network and genetic algorithm

Abstract

In this paper, a method of dynamic obstacle avoidance and path planning based on neural network and genetic algorithm is proposed. The neural network model of dynamic environmental information in the workspace for a robot is constructed. The relationship between dynamic obstacle pveidaace and t8e alpat ef tko model is embiished based on this model and the two-dimensional coding for the via-points of path is converted to onedimensional one. Then the fitness of the dynamic obstacle avoidance and that of the shortest distance are fused to a fitness function. The simulation results show that the proposed method is correct and effective.