3D TRAJECTORY PLANNING MODEL OF UNMANNED AERIAL VEHICLES (UAVS) IN A DYNAMIC COMPLEX ENVIRONMENT BASED ON AN IMPROVED ANT COLONY OPTIMIZATION ALGORITHM

In this paper, a mixed integer programming mathematical model for 3D trajectory planning of UAVs in a dynamic complex environment was proposed by considering constraints such as UAV falling risks, radio interference threats, dynamic restriction airspace, and terrain obstacles. According to the origin/destination and departure time of a flight task, a feasible shortest trajectory was determined with thresholds of radio signal intensity and safe distance under different conditions satisfied. Meanwhile, an improved ant colony optimization (ACO) algorithm was designed on the basis of the characteristics of the problem. During the solution construction process, the searching steps were adjusted adaptively by considering the size of the feasible solution space. Besides, a neighborhood search algorithm was embedded to improve the quality of the optimal solution. Finally, an optimized safe trajectory of UAVs in a complex dynamic environment can be rapidly identified using this model through numerical experiments. Compared with conventional ACOs, the proposed algorithm can reduce the flight mileage and calculation time.