Papers
9
Total Citations
149
H-Index
7
About
Xinting Ding is a leading researcher in agricultural robotics, with a focused specialization in the automation of kiwifruit cultivation — spanning harvesting, pollination, and intelligent perception systems. Through a highly productive body of work, Ding has made substantial contributions to solving some of the most persistent challenges in orchard robotics, including collision-free path planning for double-arm harvesting robots, deep learning-based grasp detection, and the spatial identification of fruit clusters in complex natural environments. Among their most influential contributions is a 2022 study on double-arm robotic cooperation for kiwifruit harvesting (40 citations), which addressed the critical problem of inter-arm collision avoidance during picking operations. Complementing this, Ding's work on deep learning-based grasping detection (21 citations) and flower/cluster position prediction (18 citations) reflects a rigorous, systems-level approach to field automation. Their research on precision liquid pollination technology further demonstrates a commitment to full-season orchard mechanization beyond harvesting alone. More recently, Ding has explored deep reinforcement learning strategies for clustered fruit harvesting and soft end-effector design, positioning their work at the frontier of adaptive, human-safe agricultural robotics. With over 140 cumulative citations, Ding's research offers essential reading for anyone advancing autonomous systems in precision agriculture.
Research Focus
Key Achievements
Top Papers
- 1Double-Arm Cooperation and Implementing for Harvesting Kiwifruit40 citations · 2022
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- 6Development and evaluation of precision liquid pollinator for kiwifruit12 citations · 2023
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- 9Development and Evaluation of Precision Liquid Pollinator for Kiwifruit2 citations · 2023