Xiaoying Feng
Papers
1
Total Citations
1
H-Index
1
About
Xiaoying Feng is a researcher specializing in advanced 3D measurement, robotic vision, and multi-sensor fusion. Her work focuses on developing robust, high-precision scanning methods for complex environments, particularly through dual-arm hand–eye systems. Her most notable contribution is a novel global calibration technique that enables collaborative 3D imaging under challenging noise conditions, addressing a critical bottleneck in automated inspection and manufacturing. She proposed the M3DHE-ICP algorithm—a multi-view scanning approach integrating multi-frequency heterodyne coding phase with Iterative Closest Point registration—which significantly improves accuracy and stability in multi-view reconstruction. This work, published in 2025, has already garnered early citations, signaling its growing influence in the field of optical metrology and robotic perception. Feng’s research bridges theoretical calibration models with practical system design, offering scalable solutions for dual-arm robotic platforms. Her achievements demonstrate a strong commitment to pushing the boundaries of non-contact 3D measurement, with implications for industrial automation, augmented reality, and digital twin technologies.
Research Focus
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Top Papers
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