Papers
12
Total Citations
603
H-Index
8
About
Fengyun Wu is a leading researcher in agricultural robotics and precision agriculture, with a particular focus on intelligent fruit detection, robotic harvesting systems, and autonomous navigation in complex orchard environments. Wu's work sits at the intersection of computer vision, deep learning, and robotic engineering, addressing one of modern agriculture's most pressing challenges: automating labor-intensive harvesting processes across diverse fruit crops. Wu's most impactful contributions include developing novel path planning algorithms for mobile robots navigating unstructured orchards, garnering 129 citations, alongside pioneering vision-based systems for banana harvesting that have collectively attracted hundreds of citations. Notably, Wu introduced YOLO-Banana, a lightweight neural network enabling real-time detection of banana bunches in natural field conditions, and advanced three-dimensional localization techniques for precise robotic cutting operations. Research has extended across multiple fruit species—including litchi, grapes, pineapple, tomatoes, and citrus—demonstrating remarkable breadth and versatility. Wu has also tackled difficult real-world challenges such as nighttime detection using generative adversarial networks, occlusion handling, and multi-target recognition under variable illumination and wind disturbance. With over 590 cumulative citations and a growing publication record through 2025, Wu's research is making measurable contributions to the practical deployment of intelligent agricultural robotics worldwide.
Research Focus
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