Papers
2
Total Citations
12
H-Index
2
About
Lijuan Xu focuses on agricultural robotics and machine vision, with a particular emphasis on improving the accuracy and efficiency of fruit-picking automation. Her most cited work, "Mature pomegranate recognition methods in natural environments using machine vision" (2019, 9 citations), addresses a critical challenge in agricultural robotics: reliably identifying ripe fruit under varying natural lighting conditions. By analyzing color features of pomegranates in complex orchard settings, Xu's research directly enhances the applicability of picking robots, bridging the gap between controlled laboratory systems and real-world agricultural environments. In a complementary study on "Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement" (2018, 3 citations), she tackles the precision of robotic manipulation by integrating actual D-H parameter measurements with feedback compensation. This work contributes to improving robot pose control, a fundamental requirement for delicate harvesting tasks. Though her citation counts are modest, Xu's research is highly applied, targeting practical solutions for the growing field of precision agriculture. Her contributions are particularly valuable for researchers developing vision-guided robotic systems for specialty crops, where environmental variability poses significant technical hurdles.
Research Focus
Key Achievements
Top Papers
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