Yundong Wang
Papers
3
Total Citations
14
H-Index
2
About
Yundong Wang is a researcher at the forefront of agricultural robotics, specializing in autonomous perception and robotic manipulation for orchard environments. His work integrates computer vision, LiDAR-based mapping, and teleoperation to address critical challenges in precision agriculture and robotic harvesting. Wang’s most notable contribution is the development of an apple fruit localization system that combines accurate and flexible hand-eye pose acquisition, enabling robotic harvesters to reliably detect and grasp fruit in complex orchard settings—a paper that has garnered 8 citations since 2024. He further advanced field robotics with a LiDAR-based framework for obstacle identification and mapping, achieving 4 citations in 2025, which enhances safe autonomous navigation in unstructured agricultural spaces. Additionally, Wang pioneered a VR map construction method for orchard robot teleoperation, leveraging dual-source positioning and sparse point cloud segmentation to improve remote control accuracy. His research directly impacts the scalability of automated harvesting and reduces labor dependency in fruit production. With a growing citation record and a focus on real-world deployment, Wang’s work is shaping the next generation of intelligent agricultural systems, making him a key figure in the intersection of robotics, computer vision, and sustainable farming.
Research Focus
Key Achievements
Top Papers
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