Robot path planning based on improved genetic algorithm

Abstract

In order to solve the problems of the basic genetic algorithm in robot path planning, such as the path is not smooth enough, the number of turns is too many, and it is easy to fall into the local optimal solution, an improved genetic algorithm is proposed. The method introduces the turning angle and turning times as the evaluation objectives, improving the practicability of the fitness function; The elitist retention strategy is added to improve the convergence speed of the algorithm; The adaptive change strategy of crossover probability and mutation probability is optimized, so that the algorithm can adapt to various scenarios and improve the optimization ability and convergence speed of the algorithm. The simulation results show that the improved genetic algorithm is more suitable for robot movement than the basic genetic algorithm.