Abstract:
This report is a comprehensive study of a novel variable rate sprayer system intended for deployment on agricultural drones. The primary goal is to formulate and execute a system capable of spraying orchard spraying products with precision and efficiency, ensuring targeted application. The variable rate sprayer integrates an electronic flow control system designed to dynamically adjust the sprayer's flow rate in real-time, responding to orchard imagery for enhanced accuracy and effectiveness.
Robot Operating System (ROS) has been effectively utilized as a communication interface bridging the simulation environment and neural networks. Leveraging frameworks and packages such as dronekit, alongside neural networks, the study is into the synergistic integration of these technologies. The objective is precision spraying which targets only the needed areas, boosting efficiency, cutting costs, and safeguarding the environment.
The Pixhawk flight controller exhibits the capability to concurrently manage both the UAV's flight dynamics and the flow rate of the sprayer, eliminating the necessity for a secondary sprayer controller. CFD simulations are employed to analyze the flow physics within the nozzle of the variable rate sprayer. In a large-scale implementation, the project effectively diminishes manual labor time in agriculture fields, consequently reducing the overall costs associated with spraying.
