Heterogeneous UAV cooperative reconnaissance path planning based on improved Harris hawks algorithm

Aiming at the problems that the path planning algorithm of heterogeneous UAV cooperative reconnaissance is difficult to improve convergence accuracy and convergence speed at the same time, and easy to fall into local optimality, a new trajectory planning algorithm based on improved Harris hawks algorithm for heterogeneous UAV cooperative reconnaissance is proposed. Firstly, a heterogeneous UAV collaborative reconnaissance model with multiple payloads is established. Taking the shortest path as the objective function, an improved Harris hawks algorithm is designed to solve the model. Secondly, the reverse learning mechanism is used to initialize the population, which is conducive to increasing the diversity of the population and improving the quality of the solution. Differential variation disturbance is used in the early stage of the algorithm to accelerate the convergence speed, and the Gaussian distribution function coefficient is used in the later stage of the algorithm to reduce the possibility of falling into local optimum, so as to avoid premature maturity of the algorithm. Finally, simulation experiments are carried out based on the model. Compared with the improved particle swarm optimization algorithm and the multi-strategy Harris hawks algorithm, the convergence accuracy of the designed algorithm is increased by 12% and 10%, and convergence speed is increased by 42% and 44%, respectively. © 2023 Editorial Department of Journal of Chinese Inertial Technology. All rights reserved.