关键词: 无人船, 路径规划, 模型构建, 粒子群算法

Abstract: On the basis of the design and implementation background of the developed FR unmanned ship, the particle swarm optimization (PSO) algorithm is used to improve the solution of optimal path to address the problems of local optimization, insufficient anti-interference adaptability and low control accuracy when the traditional algorithm was used in the path planning. The path population becomes more effective in initialization by adding fitness function during the particle initialization, improving the overall convergence speed and path tracking accuracy of the algorithm. The model establishment, algorithm optimization, simulation calculation and experimental verification are carried out. The results show that the FR unmanned ship in the complex environment can avoid obstacles on the water surface, escape from the local minimum point, reach the set point accurately, convergence faster and meet the needs of timely response by adopting the improved PSO algorithm.

Key words: unmanned ship, path planning, model construction, particle swarm optimization