Application Research Of Route Planning Of UAV Based On Improved Ant Colony Algorithm

With the rapid development of modern technology, the development of UAV technology is increasingly mature and complete. Route planning of UAV is a key technology. It improves aircraft operational efficiency and guarantees safe and reliable flight. It mainly plans an optimal flying route which meet some performance index. At present, most of intelligent algorithm including genetic algorithm, artificial neural networks, simulated annealing optimization algorithm are applied to route planning. Ant colony algorithm,as a new bionic swarm algorithm, has the advantages of excellent distribution mechanism,information feedback, strong robustness and convenient integration with other algorithms. It has been successfully applied in many combinatorial optimization problems such as TSP, network routing etc.In this paper, the basic principles and mathematical model of ant colony algorithm are discussed. The reason which the basic ant colony algorithm is easy to fall into local optimal solution is analyzed. Two typical improved ant colony algorithm:ANT-Q System and MAX-MIN ant system are introduced. At last, an improvement strategy to improve the global convergence performance is proposed, its basic idea is:dual population searching at the same time, different population of ants can exchange and cooperation. In the iterative process, when the algorithm is trapped into a local optimum, change the pheromone of the corresponding path of different populations. At the same time, bi-directional dynamic adjust adaptively the volatile coefficient of the pheromone. Use as a source of reference of MAX-MIN Ant System, the pheromone is limited within a certain range. The concussion change of the pheromone and the adaptive adjustments of the volatile coefficient can expand the search space and improve the overall searching performance. It is proved that the algorithm is feasible and effective in the emulation experiments.Then the algorithm model of UAV route planning is established. How is ant colony algorithm applied to general route planning process is studied. In order to verify the feasibility and validity of the scheme, the basic algorithm and improved algorithm are implemented with computer simulation.By comparing the simulation results, the global convergence and stability of improved algorithm is superior.