Optimal Distribution of UAVs in Crop Spraying Considering Energy Consumption

Abstract

The population growth rate has increased, leading to a need for new technologies like unmanned aerial vehicles (UAVs) to expand crop production and growth. UAVs are used in mapping, spraying, planting, crop monitoring, irrigation, and insect pest diagnosis. However, challenges such as maximum effective signal range, fuel limitations, uncovered crop areas, overlapped spraying, and pesticide waste need to be considered. In this context, we propose a multi-agent control method that associates the energy consumption with the total crop coverage. Our proposed method is able to generate the path planning for the UAVs considering a target density function, while the total flying time is decreased. The simulation results show that the proposed method decreases the total energy consumption with a negligible increment in the spray error.