Shuai Song
Papers
2
Total Citations
10
H-Index
2
About
Shuai Song’s research centers on the precision and reliability of industrial robotics, with a particular focus on the kinematic and dynamic performance of tool-changing systems for shield machines. His work addresses critical challenges in robot accuracy by modeling motion errors arising from dimensional and drive parameter variations, and by investigating how clearance in kinematic pairs affects dynamic behavior through contact and collision analysis. In his 2022 study on motion error analysis using a screw-vector method, Song established a mathematical framework that enhances absolute positioning accuracy—a key limitation in industrial robots. His subsequent work on clearance effects provides essential insights into the nonlinear dynamics of mechanical systems, directly informing the design of more robust and reliable robotic manipulators. Although early in his career, with his most-cited paper accumulating 8 citations, Song’s contributions are foundational for advancing the precision of automated tool-changing in tunnel engineering. His research bridges theoretical kinematics with practical robotics, offering valuable guidance for engineers seeking to mitigate error sources in high-stakes industrial environments.
Research Focus
Key Achievements
Top Papers
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