Songlu Xiao
Papers
1
Total Citations
10
H-Index
1
About
Songlu Xiao is a researcher at the forefront of precision engineering and automated metrology, with a primary focus on enhancing the accuracy and efficiency of coordinate measuring systems. Their most cited work, "Error Analysis of a Coordinate Measuring Machine with a 6-DOF Industrial Robot Holding the Probe" (2023, 10 citations), addresses a critical bottleneck in modern manufacturing: the need for high-speed, automated complex surface measurement. Xiao’s major contribution lies in systematically analyzing the error sources introduced when replacing traditional manual articulated arm coordinate measuring machines (AACMMs) with industrial robot arms. By identifying and quantifying these kinematic and dynamic errors, Xiao provides a foundational framework for developing fully automated, robot-driven inspection systems that maintain high precision. This work is pivotal for advancing quality control in industries like aerospace and automotive, where manual measurement is a significant efficiency bottleneck. Although early in their career, Xiao’s research is already shaping the next generation of intelligent manufacturing, promising to unlock faster, more reliable, and fully autonomous dimensional metrology.
Research Focus
Key Achievements
Top Papers
- 1