To solve the path planning problem of UAVs in three-dimensional space, the standard artificial fish swarm algorithm is improved from the perspectives of accelerating the convergence and ensuring the convergence effect.Firstly, the improvement factor α of adaptive field-of-view and adaptive step size is introduced to speed up the convergence of the algorithm.Then, the minimum field-of-view and the minimum step size are set to ensure the search ability of the algorithm.Finally, the jumping behavior is added to ensure that the algorithm can jump out of the local optimum at the later stage.The algorithm is simulated and compared with other algorithms through software.The simulation results show that the algorithm has fast search speed and good convergence effects at the initial stage of search, and can jump out of the local optimum at the later stage of search, and the effectiveness of the algorithm is verified.The comparative experiment results show that the optimal fitness of the algorithm is improved at the later stage of search, and the superiority of the algorithm is verified.