Papers
2
Total Citations
8
H-Index
2
About
Yukun Shi is a researcher whose work bridges the frontiers of robotic control and industrial computer vision. His primary research areas include adaptive nonlinear control, predefined-time stability, and structure-from-motion systems. Shi’s most notable contribution is the development of an adaptive global predefined-time control framework for robotic systems with output constraints, leveraging a multiple multidimensional Taylor network. This work, published in 2025, has already garnered 4 citations for its innovative approach to ensuring rapid, predictable convergence in complex robotic tasks. In parallel, Shi has made significant strides in industrial vision with his 2020 paper on the simultaneous identification of points and circles within structure-from-motion systems, also earning 4 citations. This method enhances the accuracy and robustness of 3D reconstruction in factory settings, directly impacting automation and quality control. With a growing citation footprint, Shi’s dual focus on theoretical control guarantees and practical vision solutions positions him as a rising figure in robotics and intelligent systems, offering valuable insights for students and researchers working at the intersection of control theory and real-world industrial applications.
Research Focus
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Top Papers
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