Aiming at the problem of UAV searching for the target with uncertain moving speed and direction, this paper designs a search path planning algorithm based on improved genetic algorithm. The traditional method based on analysis has not strong adaptability and is not convenient for the realization of computer automatic calculation. In this paper, a search path planning algorithm based on improved genetic algorithm is proposed, which considers the probability time and other parameters of the target moving direction as a dynamic artificial potential field, improves the adaptability of the algorithm for solving the search path planning problem, and has a high degree of adaptability and automation for the complex search area and the target moving probability. According to the idea of survival of the fittest in genetic algorithm, a more optimal search path is selected. In this process, the path point of UAV is regarded as the gene of organism; the search path is regarded as the chromosome of organism; and then the search path is optimized through hybridization, selection, mutation and other operations. Then, an example is set up for simulation calculation. From the simulation results, we can see that the search path planning algorithm based on the improved genetic algorithm is feasible, and has the advantages of flexibility, efficiency and automation.
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