Robot Vision Navigation in Precision Agriculture: Crop Planting and Intelligent Fertilization

摘要

Precision agriculture (PA) is an important component of agricultural modernization development. Traditional crop planting and fertilization are mainly done manually, which has strong subjectivity and is difficult to achieve precise grasp. In order to improve the accuracy of crop planting and fertilization, and improve the level of crop production, this article conducts in-depth research on the application of robot vision navigation in PA crop planting and intelligent fertilization. This article first analyzes the concept of PA and the challenges faced by crop planting and fertilization. Then, a robot vision navigation system is constructed, and based on the system, crop and farmland image samples are preprocessed and segmented. Finally, a navigation path is generated. To verify the application effect of robot visual navigation in PA, this article takes a certain agricultural product production area as the experimental environment, and takes corn, potatoes, and peanuts as the objects. The experimental analysis is conducted from two aspects: the positioning accuracy of crop planting navigation and the fertilization effect of the system. The results showed that compared with traditional manual methods, the average nutrient utilization rates of corn, potatoes, and peanuts increased by 9.29%, 9.56%, and 9.21%, respectively, after using robot vision navigation systems to assist intelligent fertilization. The conclusion indicates that robot visual navigation can effectively improve the scientific nature of crop planting and fertilization, and contribute to improving the quality and level of PA production.