Longfei Fan
Papers
2
Total Citations
61
H-Index
2
About
Longfei Fan is a leading researcher in the field of robotic sensing and subsurface infrastructure mapping, with a primary focus on fusing ground-penetrating radar (GPR) with vision-based systems. His major contributions center on developing novel, automated methods for detecting, mapping, and reconstructing underground pipelines—a critical challenge for urban infrastructure management and construction safety. Fan’s most influential work, “Toward Automatic Subsurface Pipeline Mapping by Fusing a Ground-Penetrating Radar and a Camera” (2019), has garnered 53 citations and introduces a groundbreaking approach that models the GPR sensing process to simultaneously detect multiple pipelines, even under non-perpendicular scanning angles. This work, along with his earlier 2018 study, demonstrates his ability to solve complex, real-world problems by mathematically proving the hyperbola response in GPR data, enabling more accurate 3D reconstruction. His research has significant implications for reducing excavation risks and improving utility mapping efficiency. By combining theoretical rigor with practical robotic applications, Fan has established himself as a key innovator in non-destructive subsurface sensing, making his work essential reading for engineers and researchers in robotics, civil engineering, and geophysics.
Research Focus
Key Achievements
Top Papers
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