Multi-objective UAV Trajectory Planning Based on Improved Wolf Pack Algorithm Improved Wolf Pack Algorithm

Abstract

For multi-objective trajectory planning problem of an unmanned aerial vehicle(UAV) in complex environment, a problem model is constructed based on flight environment information, mission objectives, and flight performance constraints. A multi-objective optimization function is established, and an improved wolf pack algorithm is proposed for verification. Fixed wing aircraft cannot change its speed direction instantly. Based on the characteristics of the problem and the two-dimensional Dubins curve, it has effectively solved the three-dimensional shortest path. Compared with ant colony algorithms, the results shows the improved wolf pack algorithm can search the optimal track faster, and the optimized track can consider both the number of correction times and track length to achieve multi-objective optimization. It has better global optimization ability and faster rate of convergence, which proves its effectiveness in solving UAV track planning.