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About

Zhijie Qian is a leading researcher in agricultural robotics, with a primary focus on developing intelligent vision and manipulation systems for apple harvesting robots. His work addresses critical challenges in automating fruit picking, particularly in unstructured orchard environments. Qian’s major contributions include pioneering methods for apple tree branch segmentation from images with small gray-level differences, a technique that enables robots to navigate and avoid obstacles during harvesting. He also developed a nighttime image enhancement method based on Retinex and guided filter, allowing harvesting robots to operate continuously in low-light conditions—a key advancement for improving efficiency. Additionally, his research on branch localization using skeleton feature extraction and stereo matching provides precise 3D information for robotic manipulators, while his analysis of grasping damage using finite element modeling helps optimize end-effector design to minimize fruit bruising. With his most-cited papers accumulating over 160 citations, Qian’s work has significantly advanced the practical deployment of agricultural robots, earning recognition for its direct impact on reducing labor costs and increasing harvest yields.