GUIDING UNMANNED AERIAL VEHICLE PATH PLANNING DESIGN BASED ON IMPROVED ANT COLONY ALGORITHM

This paper is specific to the requirements of guiding flight and navigation control of an unmanned aerial vehicle (UAV) and the problems such as slow convergence rate and unreasonable path planning occurred in the path planning of a traditional ant colony algorithm. In this paper, the ant colony algorithm combined with the manual correction algorithm added with angle calculation operators is adopted, and systematic angle calculation operators are introduced as a part of the heuristic information so that the combined algorithm has higher global searching ability and reasonable guiding ability, and local optimum caused by misleading of heuristic information in the traditional ant colony algorithm can be avoided. To verify the validity of this algorithm, a simulation experiment based on MATLAB simulation is conducted, and meanwhile, experiments are conducted at a practical guiding ground station. The experimental results indicate that the motion path of the UAV is smooth, which is close to the optimal path.