USV Path Planning Based on ACO-SA Algorithm - Luo, Chuanshang; Tang, Yifeng; Huang, Zhihui; Xu, Yifan; Liu, Bin; Zhang, Hai-Tao (Chinese Control Conference, 2023)
This paper solves USV path planning problem constrained by multiple factors via ant-colony optimization algorithm. First, this paper uses the ways of multi-objective optimization to model the USV path planning problem. An improved ant colony algorithm named ACO-SA is put forward afterwards to effectively solve the problem. The algorithm is a combination of ACO algorithm(ant colony algorithm) and SA algorithm(simulated annealing algorithm), which has three improments: change the initial distribution of pheromone to guide the search when the algorithm has just started running; change the heuristic function and state transition probability taking three factors into consideration; change the pheromone update rule and make the ants compete for the right to update pheromone by simulated annealing algorithm, and update the best solution by the same algorithm. Finally, simulation experiment and field experiment are conducted to check the validity of ACO-SA algorithm.