Xianjun Li
Papers
2
Total Citations
8
H-Index
2
About
Xianjun Li is a rising researcher in agricultural robotics and precision automation, with a focus on intelligent harvesting systems for specialty crops. Their work centers on computer vision-based maturity assessment and motion planning for robotic manipulators in complex agricultural environments. Li’s most-cited paper, “An end-to-end maturity prediction and hierarchical counting method for cherry tomatoes” (2025, 6 citations), introduces a novel deep learning framework that simultaneously predicts fruit ripeness and performs hierarchical counting, enabling real-time, non-destructive yield estimation. This contribution addresses a critical bottleneck in automated greenhouse harvesting by integrating visual perception with decision-making. In a complementary study, “Decoupled motion planning method for 7-DOF manipulator and lifting joint in automated tomato harvesting” (2025, 2 citations), Li proposes a decoupled trajectory optimization approach that enhances the efficiency and safety of high-degree-of-freedom robotic arms during fruit picking. Despite the early stage of their career, Li’s work demonstrates clear practical impact, bridging the gap between theoretical robotics and deployable agricultural solutions. Their research is particularly relevant for students and engineers interested in the intersection of computer vision, motion planning, and sustainable food production.
Research Focus
Key Achievements
Top Papers
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