Global Path Planning for AUV Based on the IACO Algorithm

In order to address the issues about slow convergence and susceptibility to local optima in ACO algorithm for AUV’s path planning, and to improve the quality of pathfinding and reduce the number of path turns, we propose an improved ACO(IACO) algorithm. Firstly, an improved A* algorithm is employed and a turning constraint factor is introduced to design a new heuristic factor, aiming to reduce the number of path turns and enhance path smoothness. Secondly, max-min ant system is introduced, and an updated strategy for pheromone trail updates based on the turning constraint factor is proposed, accelerating the iteration speed. Finally, simulations are conducted using a grid map in MATLAB. The results demonstrate that the improved ACO algorithm achieves favorable outcomes in terms of quality and reduced number of turns. It helps AUV reduce energy consumption, thereby enhancing their endurance capabilities.