Papers
14
Total Citations
1,275
H-Index
10
About
Mingyou Chen is a pioneering researcher in agricultural robotics and intelligent harvesting systems, whose work sits at the intersection of computer vision, robotic manipulation, and precision agriculture. His most influential contribution, a 2020 review on vision-based fruit picking robots (546 citations), established a foundational framework for understanding how machine vision algorithms can enhance the intelligence and efficiency of harvesting robots in complex field environments. Building on this foundation, Chen has made substantial advances in path planning for agricultural manipulators, developing RRT-based and collision-free motion strategies specifically tailored for litchi-picking scenarios. His work on 3D orchard mapping using SLAM and stereo vision demonstrates a sophisticated understanding of unstructured real-world environments, while his dynamic visual servo control research pushes toward fully continuous orchard operation. Chen has also contributed innovations in deep learning-based fruit segmentation through architectures like DualSeg, lightweight detection models for multi-ripeness citrus, and flexible tactile sensors for soft robotic grippers. With a cumulative citation count exceeding 1,250, his body of work has meaningfully shaped the trajectory of smart agricultural robotics, offering practical solutions that bridge fundamental perception research with deployable harvesting technology.
Research Focus
Key Achievements
Top Papers
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- 2RRT-based path planning for an intelligent litchi-picking manipulator173 citations · 2018
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- 6Collision-free motion planning for the litchi-picking robot70 citations · 2021
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