Qingqing Wang
Papers
1
Total Citations
7
H-Index
1
About
Dr. Qingqing Wang is a leading researcher in agricultural robotics and autonomous navigation, with a focus on sensor fusion for precision agriculture. Her work centers on developing robust perception systems that enable robots to operate effectively in complex, unstructured environments, particularly dense orchards. Dr. Wang’s most notable contribution is her pioneering fusion of vision and 2D LiDAR data to extract reliable navigation lines for autonomous agricultural robots. In her highly cited 2025 paper, she proposed a novel method that integrates a YOLOv8-ResCBAM network with LiDAR point cloud data, achieving significantly higher accuracy than traditional single-sensor approaches in dense pomegranate orchards. This work, already garnering 7 citations, addresses a critical bottleneck in field robotics: maintaining navigation precision under heavy foliage and variable lighting. Her approach not only advances the state of the art in agricultural automation but also provides a scalable framework for other dense planting scenarios. Dr. Wang’s research is instrumental in moving toward fully autonomous farming, reducing labor costs, and improving crop management efficiency.
Research Focus
Key Achievements
Top Papers
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