To improve the time efficiency of agricultural unmanned aerial vehicle(UAV)to complete the given task,reduce the relevant input cost and aircraft inspection operation cost during agriculture task,a collaborative route planning algorithm based on multiple UAVs is proposed in this paper.The algorithm considers more than one UAV to improve the time efficiency with multifighters parallel processing,different optimization criteria to reduce input costs(e.g.,fuel,herbicides)and avoiding refilling operations to reduce aircraft inspection operation cost.Metaheuristic algorithms can provide optimal or at least near optimal results if they run long enough and avoid trapping in local optimum.It can be used for collaborative route planning in agricultural fields taking into account multi-UAVs.In this context,simulated annealing algorithm(SA)and genetic algorithm(GA)are combined to optimize the routes considering different criteria such as the travelled distance,the time required to perform the task and the input costs,even simultaneously.The proposed approach also has special relevance for collaborative route planning in herbicide applications.This case requires a tank on board the UAV to store an agrochemical product.Specifically in some cases,the tank capacity may not be sufficient to treat the entire field even when working in cooperation with other UAVs.In order to avoid refilling,its capacity must be considered because it affects the routes to be followed.The routing problem can be expressed as a combinatorial optimization problem in which the optimal order to cover the field without overlap.Objective functions are used to evaluate how well a solution performs in terms of some specific criterion(i.e.,an objective)and yield a value,which is typically known as the objective value or cost that measures the aptness of a solution.In this paper,the distance travelled,the input cost(i.e.,the money spent on herbicide and fuel)and the spent time(i.e.,the time that it takes the fleet to complete the given agricultural task)are considered in objective functions.Based on the total objective function,experiments are conducted with the algorithm proposed in this paper.The proposed approach was validated by solving several agricultural spraying problems.The results showed that the proposed collaborative route planning covers a broad range of agricultural situations and that the optimal routes may vary considerably depending on the features of the fleet UAVs,the variability of the field and the optimization criteria selected.Finally,a comparative study against other rout planning algorithms was carried out.