Route Planning and Distributed Airport Site Selection Method for UAV Swarm Road Inspection

In the process of UAV swarm road inspection, there are many problems such as difficulty in UAV route planning, unbalanced utilization of UAVs, and difficulty in determining the distributed airport site. In response, firstly, an inspection map is built to remove the redundant information irrelevant to road inspection. Secondly, route planning and airport site selection are unified in the framework of multi-objective optimization. Thirdly, the particle coding method, particle update rules and particle decoding method are proposed which combine route optimization and airport site selection. Fourthly, several evaluation indexes are proposed comprehensively to evaluate the effect of route planning and airport site selection. The experimental results show that: (1) By this method, the mileage of repeated part in optimized inspection route is less than 7% of the total mileage, and the UAV utilization balance rate is more than 75%. (2) After optimization, the reuse rate of distributed airports has been significantly improved. It shows that the method proposed in this research can plan the route for UAV road inspection task preferably, balance the utilization of UAV, and select a better location as the distributed airport site. It provides a firm foundation for autonomous UAV swarm road inspection system.