Research on UAV Route Planning Based on Ant Colony Algorithm

Unmanned aerial vehicles (UAVs) are of great significance in the inspection of key areas, and route planning is a key link for UAVs in performing their tasks. To this end, an optimal route planning method for UAVs based on the ant colony algorithm is proposed to solve the multi-UAV scheduling problem in the inspection of key areas. First, the ant colony algorithm is used to find the approximate Hamilton circle of each key area, and then the shortest inspection time of each area can be found. Then, 0–1 linear programming is applied to find the optimal flight route from base H to each focus area and the minimum number of UAVs. Further, the UAV coverage problem is solved using classical generalization approximation to find the minimum number of 3 UAVs required with 95.7270% coverage and the optimal flight routes. Finally, to ensure that the time interval between two adjacent inspections of the above inspected places is not greater than 3 hours, the rectangular orbit model as well as the time-drone numbering model are solved in three steps. Finally, a minimum of 78 UAVs are required, and the flight time and route of each UAV is obtained.