Research on AUV Path Planning Based on Improved Ant Colony Algorithm

Abstract

Because the traditional ant colony algorithm has the disadvantages of slow convergence speed and easy to fall into the local optimal solution in complex environments, so the paper improves the traditional ant colony algorithm. The improved method sets the initial pheromone concentration based on the position information of the current feasible target point and the end point, to improve the early convergence speed of the algorithm. And by optimizing the pheromone update method to speed up the global convergence speed of the algorithm and reduce the generation of local optimal solutions. Increase the convergence speed of the algorithm by increasing the transfer factor and optimizing the transfer mode. Combined with the motion characteristics of AUV, the path is re-planned to further optimize the path and improve the feasibility of the algorithm. Simulation results show that compared with the traditional ant colony algorithm, the improved algorithm conforms to the motion characteristics of AUV, has a faster convergence speed, and reduces the generation of local optimal solutions.