Xiangrui Wu
Papers
1
Total Citations
9
H-Index
1
About
Xiangrui Wu is a researcher advancing the field of autonomous vehicle navigation, with a core focus on 3D LiDAR-based simultaneous localization and mapping (SLAM). His most cited work, "3D Lidar SLAM Based on Ground Segmentation and Scan Context Loop Detection" (2021), tackles the critical challenge of reducing cumulative error in vehicle positioning. By integrating ground segmentation with Scan Context—a global 3D feature descriptor for loop detection—Wu’s method significantly enhances SLAM accuracy and robustness in complex environments. This contribution, garnering 9 citations, addresses a hot issue in robotics and autonomous driving, offering a practical solution for long-term navigation. Wu’s research underscores his expertise in sensor fusion, point cloud processing, and real-time mapping, positioning him as a contributor to scalable, reliable autonomy. His work is particularly relevant for students and engineers seeking to understand how advanced loop closure techniques can mitigate drift in LiDAR-based systems, making it a valuable reference for improving SLAM performance in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1