Papers
1
Total Citations
9
H-Index
1
About
Rufei He is a robotics researcher specializing in 3D LiDAR-based simultaneous localization and mapping (SLAM) for mobile robots operating in challenging indoor environments. His work addresses critical limitations in autonomous navigation, particularly the degradation of perception in homogeneous, feature-sparse spaces like long corridors and the constraints imposed by low-resolution laser scanners. He developed a tightly-coupled LiDAR-inertial SLAM framework that fuses 3D LiDAR data with inertial measurement units to enhance robustness and accuracy. This approach, detailed in his highly cited 2024 paper, has garnered 9 citations shortly after publication, reflecting its immediate relevance to the field. By improving SLAM performance in degraded indoor settings, He’s contributions advance the reliability of mobile robots in real-world applications such as warehouse logistics and facility inspection. His work stands out for tackling a persistent bottleneck in indoor autonomy, offering a practical solution that balances computational efficiency with precision.
Research Focus
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Top Papers
- 1