Zheping Yan
Papers
8
Total Citations
117
H-Index
6
About
Zheping Yan is a robotics and autonomous systems researcher whose work spans underwater robotics, computer vision, and intelligent control systems. His research is particularly focused on advancing underwater target detection and bionic underwater robot control — two areas where he has made meaningful and measurable contributions to the field. Yan's most impactful work addresses the notoriously difficult challenge of underwater optical image processing, where conventional algorithms struggle with complex imaging environments. His development of hybrid deep learning architectures, including YOLOX combined with MobileViT and the CBAM-YOLO network, has pushed the boundaries of real-time underwater fish detection and small target recognition, together accumulating over 50 citations. Complementing this vision-based research, he has made significant advances in robust nonlinear model predictive control for bionic underwater robots, tackling external disturbance rejection and trajectory tracking using Central Pattern Generator (CPG) frameworks — work that has drawn over 45 citations collectively. Beyond underwater systems, Yan has explored agricultural mobile robot path planning and multi-robot formation control, demonstrating breadth across autonomous systems. His career-long interest in intelligent motion control, from early fuzzy decoupling methods to modern predictive control architectures, reflects a sustained commitment to making autonomous robots more capable, adaptable, and deployable in real-world environments.
Research Focus
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Top Papers
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