Distribution Planning of UAV Automatic Charging Station Based on Genetic Algorithm

As the UAV industry develops rapidly, UAVs are seeing wider application. They have the potential to play a crucial role in future smart cities and bring in enormous economic benefits. Presently, the battery life of UAVs is short and it is difficult to make breakthroughs in the short term. In addition, the requirements for UAV battery life get higher and higher. Under this situation, to deploy autonomous charging stations for UAVs becomes an inevitable trend. However, it remains a challenge to minimize the deployment cost due to various factors involved. Against the backdrop of taking the lead in putting forward the planning and layout of UAV charging station, this paper carried out the cost modeling of various factors affecting the cost in the charging process of the initial station and the later UAVs. Moreover, this paper used the weighted Voronoi diagram to introduce the influence of real environmental factors on the layout planning of charging station, flight route and working efficiency, thus quantifying the cost of the space environment. Finally, the comprehensive cost model was established and the optimal location of UAV charging station was selected by iterative optimization calculation based on genetic algorithm. Additionally, the paper selected the practical examples, assigned the parameters reasonably, solved the self-built model using the genetic algorithm, adjusted the iteration times and the corresponding parameters of the algorithm and obtained the optimization results finally. Therefore, applicability of the model as well as feasibility and optimality of the algorithm were verified. Under the condition of modifying and optimizing the parameters and corresponding values of the model in this paper, the calculation process of genetic algorithm was adjusted appropriately. The models and methods in this paper could be applied to the planning of UAV charging stations in the future under the actual comprehensive situation of cities or other regions, which maximizes some of the economic benefits in the field of UAV applications and the coincidence with the actual situation.