Xuanfan Lv
Papers
1
Total Citations
52
H-Index
1
About
Xuanfan Lv is a researcher in robotics and autonomous systems, with a primary focus on LiDAR-based localization and mapping. His most cited work introduces a novel single-shot global localization method that leverages a cross-section shape context descriptor, enabling robust and efficient place recognition in challenging environments. This contribution addresses a critical challenge in autonomous navigation—achieving reliable global localization without prior pose information—and has garnered significant attention, with 52 citations since its 2022 publication. Lv’s approach stands out for its ability to handle large-scale, unstructured outdoor scenes, making it highly applicable for self-driving cars and mobile robots. By combining geometric shape analysis with LiDAR point cloud processing, his work advances the state of the art in real-time localization systems. The impact of this research is reflected in its adoption by peers working on simultaneous localization and mapping (SLAM) and autonomous navigation, solidifying Lv’s reputation as an innovator in the field. His ongoing work continues to push the boundaries of robust perception for autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1