Designing path trajectories of multiple cooperative drones for crop irrigation (2019)
This paper considers the problem of assigning target locations to be visited by Unmanned Aerial Vehicles (UAVs). We formulate the problem as a multiple traveling salesman problem (MTSP), also we considered variations such as Fixed Open - MTSP, multi objective - MTSP and use Genetic Algorithm to solve the NP-Hard problems. The main goal is to find the effective assignment of UAVs to a set of locations into a crop so as to optimize the overall cost and maximize the performance of the UAVs. The target locations need to be efficient irrigated and be supplied with sufficient water to avoid crop water stress from the perspective of precision agriculture, motivated by the fact that agriculture is responsible for 70 percent of fresh water extractions at a global level. We define the position functions for irrigation UAVs based on an image of the Crop Water Stress Index (CWSI) of the crop. The methodology consists on dividing the crop into segments as target locations, and then finding the position function and euclidean distance between segment to estimate water and energy spent by the UAVs. Simulation results have shown that between more UAVs are implicated in crop irrigation, increase the overall cost of water, energy and distance but cost individually decrease, so we can use inexpensive UAVs.