Integration and Simulation of Precision Weed Spraying System on Unmanned Ground Vehicle

Robotics is making significant inroads into agriculture. Automated systems are now being used for tasks such as planting, weeding, and harvesting, increasing efficiency and reducing labor costs. A higher cost of robots can be justified for high-value crops. This paper presents a robotics system aimed at blueberry production and targeting precision low-volume weed spraying for the blueberries planted on ridges. Equipped with visually-based machine learning weed segmentation and clusterization algorithms, it represents a powerful tool for precise, targeted weed eradication with minimum impact on the environment. The simulation of the system operation is an indispensable step in developing complex systems, hence this paper presents simulation results.