Xinming Ding
Papers
1
Total Citations
53
H-Index
1
About
Xinming Ding is a leading researcher in agricultural robotics and precision horticulture, with a focus on automating harvesting in high-density orchard environments. His most cited work, "Recognition of sweet peppers and planning the robotic picking sequence in high-density orchards" (2022, 53 citations), addresses a critical bottleneck in robotic fruit harvesting: the accurate detection of occluded crops and the optimization of picking order to maximize efficiency and minimize damage. Ding’s contributions lie in developing computer vision algorithms that can distinguish ripe sweet peppers from dense foliage and in designing path-planning strategies that enable robots to navigate complex canopy structures. This work has direct implications for reducing labor costs and improving yield in modern orchards. By bridging the gap between perception and action in agricultural robots, Ding’s research has garnered attention from both academia and industry, with his 2022 paper serving as a foundational reference for subsequent studies in robotic fruit recognition and sequential harvesting. His achievements underscore a commitment to advancing sustainable, automated farming solutions.
Research Focus
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Top Papers
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