Unmanned aerial vehicle (UAV) system joint charging station deployment and routing method

Abstract

The invention relates to an unmanned aerial vehicle (UAV) system joint charging station deployment and routing method, belonging to the technical field of wireless communication. The method includes the following steps: S1, modeling a set of source points and destination points of tasks executed by a UAV; S2, modeling a flight area of the UAV; S3, modeling charging station deployment variables; S4, modeling UAV charging variables; S5, modeling UAV routing variables; S6, modeling UAV system joint charging station deployment and routing constraints; S7, modeling a total delay required for the UAV to execute the tasks; and S8, based on the minimization of the total delay required for the UAV to execute the tasks, determining a UAV system joint charging station deployment and routing strategy.According to the scheme of the invention, the charging and task execution requirements of the UAV are comprehensively considered, and the design of the charging station deployment and UAV routing strategy is optimized by taking the minimization of the total delay required for the UAV to execute the tasks as the goal.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, relates to the deployment and routing management of unmanned aerial vehicle system charging stations, and in particular to a method for deploying and routing selection of unmanned aerial vehicle system joint charging stations. Background technique [0002] Unmanned aircraft, referred to as "UAV", is an unmanned aircraft operated by radio remote control equipment and its own program control device. It can be widely used in aerial reconnaissance, surveillance, communication, anti-submarine, electronic interference, etc. According to the instructions of the control center, the drone can fly from the source point to the destination point to perform specific tasks. However, since drones need to consume a certain amount of battery power to fly and perform tasks, if the distance between the source point and the destination point is too long, the drone needs to replenish power in time. An...

AI Technical Summary

Problems solved by technology

However, since drones need to consume a certain amount of battery power to fly and perform tasks, if the distance between the source point and the destination point is too long, the drone needs to replenish power in time. An important factor in the total flight time of UAV and the efficiency of task execution

[0003] In the existing research, some literatures have proposed the shortest path algorithm based on the Global Positioning System (Global Positioning System, GPS) and the prediction mechanism for the problem that the nodes of the UAV system move fast and the height of the network topology changes makes it difficult to apply the traditional routing algorithm. There are also studies that use deep reinforcement learning technology to realize model-free UAV control. By optimizing and determining the cruising route of the UAV and the moving route of the mobile unmanned charging station, efficient information collection of the UAV can be realized.

[0004] Existing research mainly considers the problem of UAV routing selection, but does not comprehensively consider the UAV system business requirements, charging station deployment and routing issues, and it is difficult to ensure efficient mission execution of UAVs.

Images