Qimin Xu
Papers
4
Total Citations
63
H-Index
3
About
Qimin Xu is a leading researcher in autonomous navigation and robotics, specializing in LiDAR-based perception and localization for long-term, dynamic environments. His work addresses critical challenges in place recognition, loop closure detection, and global positioning, where environmental changes—such as moving objects, varying viewpoints, and seasonal shifts—can disrupt system reliability. Xu’s major contributions include the development of SC_LPR, a semantically consistent LiDAR place recognition framework that uses a chained cascade network to filter out high-frequency dynamic objects, achieving 37 citations since 2024. He also pioneered a viewpoint- and condition-invariant loop closure detection method (14 citations) and a novel LiDAR submap-based observation model for robust global positioning in changing conditions (10 citations). Additionally, his Bi-HS-RRT\(^\text{X}\) algorithm advances sampling-based motion planning for unknown dynamic environments. With cumulative citations exceeding 60, Xu’s work is pivotal for autonomous vehicles and robots operating in real-world, unstructured settings, offering practical solutions for long-term autonomy. His research continues to push the boundaries of reliable, high-frequency localization and mapping in complex outdoor environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4