Xiangpeng Xiao
Papers
2
Total Citations
19
H-Index
2
About
Xiangpeng Xiao is a pioneering researcher at the intersection of fiber optics and robotics, whose work is redefining how machines perceive touch. His primary research areas include optical fiber distributed sensing, tactile sensor design, and deep learning-based signal demodulation for dexterous manipulation. Xiao’s most impactful contribution is the development of a novel strain measurement method using an adaptive local feature extraction technique for optical frequency domain reflectometer (OFDR) systems. This innovation, detailed in his 2024 paper (16 citations), enables high-spatial-resolution strain sensing crucial for biomedical devices and soft robotics, overcoming the challenge of weak Rayleigh scattering signals. His 2025 work, "Fibertouch," introduces a groundbreaking fiber-optic tactile sensor paired with deep learning demodulation, achieving 3 citations in its first year. This sensor promises to endow robotic hands with a sense of touch akin to human skin, advancing prosthetics and industrial automation. Xiao’s research bridges fundamental photonics and applied robotics, with his OFDR method already influencing short-distance measurement fields. His achievements signal a future where fiber-optic sensors become the nervous system of next-generation robots.
Research Focus
Key Achievements
Top Papers
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