Abstract: |
In agriculture, weeds reduce soil productivity and harvest quality. A common practice for weed control is via weed spraying. Ground spray of weeds is a common approach that may be harmful, destructive, and too slow, while aerial UAV spraying can be safe, non-destructive, and quick. Spraying efficiency and accuracy can be enhanced when adopting multiple UAVs. In this context, we propose a new multiple UAV spraying system that autonomously and accurately sprays weeds within the field. In our proposed system, a weed pressure map is first clustered. Then, the Voronoi approach generates the appropriate number of waypoints. Finally, a variant of the Traveling Salesman Problem (TSP) is solved to find the best UAV tour for each cluster. The latter task is performed using two nature-inspired techniques, namely, NSGA2 and MOEA/D. To assess the performance of each method, we conducted a set of simulation tests. The results reported in this paper demonstrate the superiority of NSGA2 over MOEA/D. In addition, the heterogeneity of UAVs is studied, where we have a mix of fixed-wing and multi-rotor drones for spraying. |