Application of optimized generic algorithm in UAV route planning

The flight path planning method of UAV is studied to establish a more objective and reasonable flight path planning method that can integrate the real digital terrain. Because immune algorithm is easy to fall into the local optimum and the convergence speed is too slow, an improved immune algorithm based on Tabu criteria is proposed and applied to UAV track planning. It determines the individual evaluation criteria, crossover and high-frequency variation through gene coding, and optimizes the initial track of UAV on the digital elevation map established by the real geographical environment information, so that the track can meet various constraint conditions. Compared with the ant colony algorithm, the results show that the algorithm accelerates the convergence process and can obtain a better solution.