Papers
12
Total Citations
912
H-Index
10
About
Yuanyue Ge is a leading researcher in agricultural robotics, specializing in autonomous fruit harvesting systems, machine vision, and robotic manipulation in unstructured environments. His work sits at the intersection of computer vision, deep learning, and mechatronics, with a particular focus on solving the complex real-world challenges of robotic strawberry harvesting. Ge's most influential contribution is the development of a fully autonomous strawberry-harvesting robot capable of operating continuously within polytunnels, a landmark achievement that has garnered over 417 citations and demonstrated practical viability for commercial agricultural automation. Complementing this, his pioneering obstacle separation methodology — employing active "push and drag" manipulation strategies — addressed one of the field's most persistent challenges: selectively harvesting clustered fruits without damaging surrounding produce. His innovations in machine vision are equally significant, encompassing deep learning-based instance segmentation, symmetry-based 3D shape completion for improved fruit localization, and multi-view ripeness assessment using compact convolutional neural networks. With over 900 cumulative citations across his published works, Ge's research has meaningfully advanced the state of precision agriculture robotics. His integrated approach — combining perception, planning, and physical manipulation — positions him as a defining voice in the next generation of intelligent harvesting technologies.
Research Focus
Key Achievements
Top Papers
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- 2Fruit Localization and Environment Perception for Strawberry Harvesting Robots112 citations · 2019
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- 5An obstacle separation method for robotic picking of fruits in clusters51 citations · 2020
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