In order to enhance the ability of Particle Swarm Optimization (PSO) to jump out of the local optimum and improve the performance of PSO in solving complex practical engineering problems,and to improve the optimization effect of PSO in path planning problems,a PSO algorithm based on Compression strategy and Mutation strategy,called CMPSO,is proposed.Based on the compression strategy,a new mutation strategy is designed.The fusion of the two strategies effectively realizes the adaptive adjustment of particles,enhances the diversity of the population,and increases the probability of the algorithm jumping out of the local optimum.Through the verification of partial CEC2017 test functions,it is proved that CMPSO has excellent optimization ability.Finally,taking various constraints into consideration,CMPSO is applied to complex UAV path planning.Compared with other improved PSO,CMPSO can obtain shorter paths with less time consumption and cost.It is shown that this method can provide a strong technical support for complex UAV path planning.