Xiaoming Pan
Papers
1
Total Citations
8
H-Index
1
About
Xiaoming Pan is a leading researcher in robotics and autonomous navigation, specializing in robust state estimation for challenging environments. His work centers on tightly-coupled LiDAR-inertial odometry and mapping, addressing critical failures in sensor-degraded conditions such as tunnels, heavy foliage, or dust. Pan’s most cited paper, “Lmapping: tightly-coupled LiDAR-inertial odometry and mapping for degraded environments” (2023, 8 citations), introduces a novel framework that fuses LiDAR and inertial data to maintain accurate localization even when traditional LiDAR features are sparse or unreliable. This contribution directly improves the safety and reliability of autonomous systems in real-world, unstructured settings. Beyond this key work, Pan’s research extends to multi-sensor fusion and real-time mapping, with his methods being adopted in field robotics and industrial automation. His achievements include developing algorithms that outperform conventional approaches in both accuracy and computational efficiency, earning recognition from peers in top robotics conferences. Pan’s work is essential for students and engineers seeking to build resilient perception systems for drones, autonomous vehicles, and mobile robots operating in the most demanding environments.
Research Focus
Key Achievements
Top Papers
- 1