Papers
15
Total Citations
305
H-Index
9
About
Lijia Xu is a leading researcher in agricultural robotics and computer vision, whose work is transforming how machines perceive and interact with complex, unstructured environments. Xu’s primary research areas include real-time object detection, motion planning for manipulators, and multimodal sensor fusion, with a strong focus on applications in precision agriculture—particularly for citrus and grape harvesting. Their major contributions are highlighted by a series of high-impact papers: the HPL-YOLOv4 model for real-time citrus detection (67 citations) and the YOLACTFusion method for RGB-NIR image fusion (47 citations) demonstrate breakthroughs in accurate, lightweight detection under challenging conditions. Xu also advanced robotic manipulation with the TO-RRT algorithm for time-optimal motion planning (31 citations) and an improved A* algorithm for greenhouse navigation (38 citations). Notable achievements include developing the YOLOC-tiny model for multi-ripeness fruit detection (12 citations) and a review on multi-arm harvesting robots (11 citations), addressing the critical balance between accuracy and efficiency. With over 300 total citations, Xu’s work is pivotal for enabling robust, real-time robotic systems in agriculture, directly tackling labor shortages and operational inefficiencies.
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- 10Design of an efficient combined multipoint picking scheme for tea buds9 citations · 2022