Research on accurate recognition and cutting algorithm of tree-head pruning robot for overhead transmission lines based on computer vision technology

This research focuses on developing a set of precise recognition and cutting algorithms for overhead power line tree-head pruning robot using computer vision technology and deep learning method. Through the integration of binocular vision system, the research achieved effective measurement of tree height, ensuring the accuracy of pruning operations. The system uses deep learning models, especially convolutional neural networks, to extract key features from images and achieve accurate identification of the relative position of trees and transmission lines. Combined with the three-dimensional information provided by binocular vision, the robot is able to make accurate tree height measurements and thus perform precise shear actions. The entire system is designed with self-learning and optimization capabilities in mind, and the algorithm can be adjusted based on real-time data and user feedback to improve recognition accuracy and shear efficiency. This study not only shows the application prospect of computer vision and deep learning in automated pruning robot technology, but also provides a strong technical support for ensuring the safe operation of transmission lines and improving the intelligence level of pruning operations.