Liuyang Qiu
Papers
1
Total Citations
10
H-Index
1
About
Liuyang Qiu is a robotics researcher specializing in LiDAR-based mapping and localization, with a focus on efficient, scalable solutions for autonomous navigation in urban environments. His work addresses the critical challenge of multi-session mapping, where a robot must build consistent maps over repeated traversals. In his most-cited paper, "Multi-Session, Localization-Oriented and Lightweight LiDAR Mapping Using Semantic Lines and Planes" (2023, 10 citations), Qiu introduces a novel framework that replaces traditional point cloud representations with lightweight semantic line and plane primitives. This coarse-to-fine approach enables robust global place recognition and consistent map merging across sessions, significantly reducing computational and storage demands. By prioritizing localization-oriented features, his method enhances long-term autonomy for robots operating in complex, dynamic settings. Qiu’s contributions advance the practicality of LiDAR mapping for real-world deployment, offering a path toward more efficient and reliable spatial understanding. His work is particularly valuable for researchers and engineers developing autonomous systems that require persistent, accurate mapping without the overhead of dense point clouds.
Research Focus
Key Achievements
Top Papers
- 1