Quncong Liang
Papers
1
Total Citations
2
H-Index
1
About
Quncong Liang is a robotics researcher specializing in 3D perception, LiDAR-based mapping, and dynamic environment understanding. Their work addresses a critical challenge in autonomous navigation: the reliable removal of dynamic objects from point cloud maps, which is essential for creating stable, long-term maps for robots operating in changing environments. Liang’s most cited paper, “A hybrid framework for robust dynamic 3D point clouds removal” (2023), tackles the specific difficulties posed by low-resolution LiDAR sensors like the VLP-16, where sparse vertical data makes dynamic point detection particularly hard. By proposing a novel hybrid approach, Liang has contributed to more robust and practical SLAM systems, directly improving map usability for real-world navigation. With 2 citations to date, this work is gaining recognition among researchers focused on dynamic scene filtering and sensor-limited robotics. Liang’s contributions are particularly valuable for field robotics, where reliable mapping under challenging sensor constraints is critical for autonomous deployment.
Research Focus
Key Achievements
Top Papers
- 1A hybrid framework for robust dynamic 3D point clouds removal2 citations · 2023