Path Planning for Underwater Glider Based on Ant Colony Algorithm Guided by Artificial Potential Field
Xiantao Jin, Chuangxia Huang, Changchun Bao · 2021
This paper studies the path planning of underwater gliders in a global static environment, and proposes an improved algorithm based on ant colony algorithm, which eliminates the problem of slow convergence due to the lack of initial pheromone in path planning of ant colony algorithm. Firstly, according to the operating characteristics of the glider, the grid method is used to model the known marine environment; Secondly, the improved artificial potential field method is introduced to construct the heuristic information function to speed up the convergence speed of the ant colony algorithm; Finally, the ant colony algorithm is used to search Path, improve the original pheromone update rule of the ant colony algorithm. The simulation results show that the algorithm in this paper is effective and superior.