首页|Joint path planning and scheduling for vehicle-assisted multiple Unmanned Aerial Systems plant protection operation
Joint path planning and scheduling for vehicle-assisted multiple Unmanned Aerial Systems plant protection operation
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
? 2022Unmanned Aircraft Systems (UAS) for plant protection have been playing increasingly important roles in agricultural field management. Nevertheless, constrained by pesticide loading capacity and battery endurance limit, the operation area of UAS or UAS swarm is quite limited, prohibiting them from serving large-scale applications. Previous works in the UAS or UAS swarm operation never considered vehicle scheduling, thus unable to cover multiple segmented agricultural fields distributed large-scale. Therefore, we propose a joint path planning and scheduling for vehicle-assisted multiple plant protection Unmanned Aerial Systems (UASs) operation. With the help of vehicle, UASs are able to spray pesticide on numerous fields distributed large-scale. Vehicle stop selection, the coordination between vehicle scheduling and UASs tasks assignment along with path planning could be determined and optimized. The test results show that the overall efficiency and the vehicle stop selection are greatly affected by the UAS number and loading capacity. Vehicle-assisted multi-UASs total operation time and non-spraying flight distance could be saved, with optimized vehicle stops utilizing a binary-coded genetic algorithm (GA). The total operation time difference could be minimal in certain cases when deploying different UAS swarms with the same UAS number but different loading capacity. A significant reduction in total operation time and UASs non-spraying flight distance could be achieved by using the proposed method. Compared with other methods, the total operation time could be reduced by 2 h when controlling 2 or 3 UASs; moreover, a sharp decrease (20–30%) in UAS swarm non-spraying flight distance wastage could be attained.
Genetic algorithmMulti-UASsNon-spraying flight distancePath planning and schedulingPlant protectionTotal operation timeVehicle
Xu Y.、Lan Y.、Xue X.、Sun Z.、Gu W.、Cui L.、Jin Y.
展开 >
College of Electronic Engineering South China Agricultural University
Nanjing Institute of Agriculture Mechanization Ministry of Agriculture and Rural Affairs
NSTL
Elsevier
