Task scheduling system for UAV operations in agricultural plant protection environment

Abstract

Unmanned aerial vehicle (UAV) can greatly reduce manpower in agricultural plant protection such as watering, sowing, pesticide spraying. It helps in creating an autonomous manufacturing system by executing tasks with less human intervention in time-efficient manner. Consequently, reasonable and efficient planning is one essential component to be focused on; yet to the best of our knowledge, there are few research on practical agricultural plant protection UAV scheduling. This work proposes method to solve the Agricultural Plant Protection UAV scheduling problem in practice such as pesticide spraying, flying and charging. At first, tasks are assigned to UAVs, then schedules are planned for UAVs. To find a near optimal schedule quickly, our method is incorporated with Dragonfly Algorithm. This proposed method is implemented and tested on datasets generated based on a real agricultural plant protection environment. Performance evaluation of our method is discussed in detail and the set of parameters that determining the best solution is reported.