The traditional Particle Swarm Optimization (PSO) algorithm is prone to fall into local optimum during the running of the algorithm, which may lead to non-optimal result of final path planning.To solve the problem, the pheromone in the ant colony algorithm is introduced for each particle in the process of iterative optimization of the traditional PSO, giving the particle more information connotation to speed up the convergence.Then, the 3D path planning problem of Unmanned Aerial Vehicle (UAV) based on fuzzy-logic PSO is studied in consideration of fuzzy logic.The input of the path planning is controlled by fuzzy processing to prevent the system from falling into local optimum.The proposed algorithm combines the advantages of the PSO, ant colony algorithm and fuzzy logic, and its effectiveness is verified by simulation.