Description: Route planning is the key technology for UAV to perform reconnaissance and combat tasks, and the performance of planning algorithm directly affects the quality of route planning. Aiming at the optimization and real-time performance of trajectory planning, an improved particle swarm optimization (UAV) trajectory planning algorithm is proposed, which combines the inertia weight "ladder" adjustment strategy with the strategy of jumping out of the local optimal solution.
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13_粒子群
13_粒子群\sample1
13_粒子群\sample1\MexicoHatnew.m
13_粒子群\sample1\PSO0.m
13_粒子群\sample1\PSO1.m
13_粒子群\sample1\PSO2.m
13_粒子群\sample1\PSO3.m
13_粒子群\sample1\PSO4.m
13_粒子群\sample1\fun.m
13_粒子群\sample1\main.m
13_粒子群\sample1\wchange.m
13_粒子群\sample2-Rastrgrin
13_粒子群\sample2-Rastrgrin\PSO.m
13_粒子群\sample2-Rastrgrin\fun.m
13_粒子群\sample2-Rastrgrin\pso.fig
13_粒子群\sample2-Rastrgrin\pso.mat
13_粒子群\sample2-Rastrgrin\rastrigrin.fig
13_粒子群\sample2-Rastrgrin\rastrigrin.m
13_粒子群\sample3-Griewankan
13_粒子群\sample3-Griewankan\Griewank.fig
13_粒子群\sample3-Griewankan\Griewank.m
13_粒子群\sample3-Griewankan\PSO.m
13_粒子群\sample3-Griewankan\fun.m
13_粒子群\sample3-Griewankan\pso.fig
13_粒子群\sample3-Griewankan\pso.mat
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