Limei Song

Papers

Total Citations

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About

Limei Song is a researcher specializing in precision measurement and robotic vision systems. Her work focuses on advancing automated inspection technologies, particularly through the integration of computer vision with robotic platforms to achieve high-accuracy dimensional measurements. Song’s most cited paper, “Research on high-precision hole measurement based on robot vision method” (2014, 12 citations), introduces a novel approach for measuring hole geometries using vision-guided robots, addressing critical challenges in manufacturing quality control. This contribution demonstrates the potential for reducing human error and increasing efficiency in industrial metrology. In her subsequent work, “Multi-view coordinate system transformation based on robot” (2015, 3 citations), she explores methods for unifying coordinate frames across multiple camera views, a key step toward robust, automated inspection systems. While her citation counts reflect a focused, early-stage impact, Song’s research lays important groundwork for the development of intelligent, vision-based robotic measurement tools. Her contributions are particularly relevant for researchers and engineers working in precision engineering, robotics, and computer vision, offering practical solutions for real-world manufacturing challenges.