Papers
3
Total Citations
82
H-Index
3
About
Xi Hou is a leading researcher in precision robotics, with a focus on the calibration and control of robotic systems for high-accuracy manufacturing, particularly in the optical component industry. His work addresses a critical challenge: how to achieve sub-micron-level precision in robotic smoothing and polishing, where even tiny path errors can ruin an optical surface. Hou’s major contributions include the development of advanced, hybrid calibration algorithms. He pioneered the use of an adaptive residual extended Kalman filter for robotic smoothing system calibration (48 citations), a method that dramatically improves parameter estimation under noisy conditions. He further advanced the field by integrating the Levenberg–Marquardt algorithm with a novel opposition-based learning squirrel search optimizer (18 citations) to enhance positioning accuracy. Most notably, his work on compensating path errors using a Chebyshev interpolated Levenberg-Marquardt algorithm (16 citations) directly tackles the geometrical errors that degrade optical component quality. By fusing machine learning optimization with classical control theory, Hou’s research provides practical, high-impact solutions for next-generation precision manufacturing.
Research Focus
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