Fei Guo
Papers
2
Total Citations
27
H-Index
2
About
Fei Guo is a researcher whose work bridges mechanical engineering and artificial intelligence, with a focus on tribology and robotic manipulation. His key contributions lie in understanding the complex physics of rotary lip seals—critical components in modern industrial machinery—and in developing intelligent vision systems for automated manufacturing. In his highly cited 2021 paper (22 citations), Guo introduced a mixed lubrication model for lip seals that accounts for deterministic surface microdeformation, advancing beyond traditional reverse pumping theory to address the demands of robot joint seals and other challenging applications. This work has significant implications for the reliability and performance of seals under complex, incomplete-motion conditions. More recently, Guo has turned to deep learning for industrial robotics, proposing a novel pose estimation method for axisymmetric bodies in cluttered, stacked scenarios (2022, 5 citations). By using neural networks to determine optimal 6D poses for robotic grasping, his research directly supports the push toward fully unmanned manufacturing. Together, these contributions showcase Guo’s ability to tackle fundamental mechanical challenges while leveraging cutting-edge AI, making his work valuable for both seal design and intelligent automation.
Research Focus
Key Achievements
Top Papers
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- 2