Research on UAV Path Planning Based on Improved Bat Algorithm
The bat algorithm is slow in the early iteration and easy to enter the local optimum when dealing with UAV route planning.In this paper,a Genetic-Bat Algorithm(GBA)is proposed by combining genetic factor algorithm with bat algorithm.First-ly,crossover and mutation operations of genetic algorithm are introduced for selective fusion to improve the convergence speed of earlier iteration.Then in the bat algorithm,the local search by stages is used to increase the search of the optimal solution.Finally,delete operations are added to reduce path redundancy.Through the simulation of map model,the results show that compared with other algorithms in path planning and iteration speed,the proposed algorithm can achieve fast convergence and fast iteration,and it is not easy to fall into the local optimal solution,so the selected path is better.
bat algorithmgenetic factor algorithmselect fusionpath planning
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