Yinbao Cheng
Papers
1
Total Citations
4
H-Index
1
About
Yinbao Cheng is a researcher focused on precision measurement and uncertainty evaluation in industrial robotics. His work addresses the critical challenge of accurately assessing the position accuracy of industrial robots—a key factor for automation quality and reliability. Cheng’s most notable contribution is his development of a novel uncertainty evaluation method using grey models for small sample data, as demonstrated in his highly cited 2024 paper, “Small sample uncertainty evaluation of industrial robot position accuracy measurement based on grey model.” This study, which has already garnered 4 citations, provides a robust framework for measuring robot accuracy with laser trackers, even when data is limited. By improving the reliability of uncertainty assessments, Cheng’s research supports more precise and trustworthy robotic systems in manufacturing and industrial applications. His work bridges the gap between theoretical metrology and practical robot performance, offering valuable tools for engineers and researchers aiming to enhance automation precision. Cheng’s contributions are particularly significant for industries where small-batch production or complex measurement conditions challenge traditional evaluation methods.
Research Focus
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Top Papers
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