Qin Zou
Papers
3
Total Citations
363
H-Index
2
About
Qin Zou is a leading researcher in autonomous navigation and 3D perception, whose work centers on simultaneous localization and mapping (SLAM) for both ground and aerial robots. His most influential contribution is a comprehensive comparative analysis of LiDAR SLAM-based indoor navigation for autonomous vehicles, which has garnered 302 citations and serves as a foundational reference for researchers and engineers building robust navigation systems. Zou also developed a parameter self-adaptive framework that transforms 3D LiDAR point clouds into 2D dense depth maps, a critical innovation for fusing LiDAR and camera data in autonomous driving and robotics. His latest work introduces ATCM, an aerial–terrestrial LiDAR-based collaborative SLAM system that enables heterogeneous multi-robot teams to build globally consistent maps—a significant step forward for large-scale, real-world deployments. With a career marked by technical depth and practical impact, Zou’s research continues to shape how autonomous systems perceive and navigate complex environments.
Research Focus
Key Achievements
Top Papers
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