UAV Track Planning Based on Improved Marine Predator Algorithm

Abstract

Aiming at the optimization problem in the field of automatic control of unmanned aerial vehicles (UAVs) for track planning, this paper proposes an optimization method of UAV track planning based on improved Marine predator algorithm, adopts uniform distribution space and pseudo-reverse learning strategy to improve population initialization, and uses T distribution as disturbance factor to update position. The objective function of the improved Marine predator algorithm considering the cost of track length, terrain and flight height is established, and the simulation test is carried out on MATLAB software. The simulation results show that an optimal path to avoid obstacles and threat areas can be obtained with particle swarm optimization and snake optimization, indicating that this method has stronger robustness and feasibility in UAV path planning.