An Improved Adaptive Genetic Algorithm for Robot Path Planning

To solve the problems of slow convergence speed and easy to fall into local optimum when adaptive genetic algorithm is applied to robot path planning, an improved adaptive genetic path planning method is proposed. In this method, turning angle evaluation index is introduced to improve the practicability of the path planning objective function; The adaptive adjustment strategy for optimizing the crossover probability and mutation probability, and the disaster operation and reversal operation are added, effectively improving the global optimization ability and convergence speed of path planning. The simulation results show that compared with the traditional adaptive genetic algorithm, this algorithm has stronger global optimization ability, requires fewer iterations, and its path planning performance is better than other improved algorithms.