Path planning of UAVs formation based on improved ant colony optimization algorithm

Aimed at the problem about the path planning of multiple unmanned aerial vehicles (UAVs) formation in radar-threatening environment, an intelligent method based on improved ant colony optimization (ACO) algorithm is presented. To begin with, initialize the mission environment before the mathematically modeling of flight path and environment. Then, a path of a single UAV can be sought by ACO algorithm. The following step is the formation of multiple UAVs. Ultimately, a real flyable path comes out on condition that the formation remains unchanged. However, path planning based on the traditional ACO may not be the best when it comes to the fact that it may contain some dispensable routes. To solve this problem, the path is trimmed afterwards to make it more straightforward. Simulation results show that the proposed improved intelligent method have better dynamic nature and computing power.