The Design and Testing of Intelligent Orchard Picking System for Agricultural Machinery based on Image Processing Technology

This paper proposes an intelligent orchard-picking system for agricultural machinery based on image processing technology. The system uses binocular vision technology to obtain high-precision 3D point cloud data of fruit trees and uses the Mask RCNN algorithm to detect and segment fruit. The system design includes two parts: hardware selection and software algorithm implementation. The hardware part mainly includes a binocular camera, robot arm and end actuator, while the software part integrates image preprocessing, target recognition and positioning, path planning, and grasp control. In the system simulation stage, the whole process is optimized several times to ensure its stability and reliability in practical application. Finally, the effectiveness and practicability of the system are verified by testing in a natural orchard environment. The experimental results show that the system can accurately identify and locate fruits under complex backgrounds, realize efficient and automatic picking operations, and significantly improve orchards’ production efficiency and economic benefits. The research results of this paper are of great significance for promoting the intelligent development of agricultural machinery.