Jinan Gu
Papers
8
Total Citations
176
H-Index
6
About
Jinan Gu is a leading researcher at the intersection of robotics, computer vision, and agricultural automation, with a focus on developing intelligent, real-time perception systems for harvesting robots. His work addresses critical challenges in Agriculture 4.0, where machines must autonomously sense, decide, and act in unstructured environments. Gu’s most impactful contribution is his parameter identification method for robot manipulators using an improved chaotic sparrow search algorithm (62 citations), which enables precise handling of unknown payloads. He has also made significant advances in fruit detection and localization, notably through an improved YOLOX model combined with RGB-D imaging (41 and 34 citations), achieving the real-time performance essential for selective harvesting. His research extends to calibrating visual positioning for Delta robots using artificial neural networks and developing combined image segmentation and point cloud registration schemes for sensing obscured tree branches. Gu’s work has been widely recognized for bridging the gap between high-accuracy computer vision models and the stringent speed requirements of agricultural robotics. His recent review on visual detection methods for fruit harvesting robots (2025) further underscores his role as a thought leader in the field, synthesizing trends to guide future smart farming technologies.
Research Focus
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Top Papers
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- 8Design of robot visual servo controller based on neural network4 citations · 2018