Xujie Kang
Papers
1
Total Citations
22
H-Index
1
About
Xujie Kang is a leading researcher in the fields of 3D computer vision, robotics perception, and simultaneous localization and mapping (SLAM). His work focuses on fusing low-cost, lightweight RGB-D sensors—such as the Microsoft Kinect—with high-precision terrestrial LiDAR point clouds to achieve robust, real-time indoor 3D reconstruction and camera pose estimation. Kang’s most influential paper, “Real-Time RGB-D SLAM Guided by Terrestrial LiDAR Point Cloud for Indoor 3-D Reconstruction and Camera Pose Estimation” (2019), has garnered 22 citations, demonstrating its impact on advancing SLAM technology for applications in robotics and autonomous navigation. By integrating dense depth data with accurate LiDAR priors, Kang’s research addresses critical challenges in drift reduction and mapping consistency, enabling more reliable performance in complex indoor environments. His contributions are particularly valuable for the growing fields of self-driving vehicles and service robotics, where precise spatial awareness is essential. Kang’s work continues to inspire new approaches to sensor fusion and real-time mapping, making him a notable figure in modern computer vision and robotics research.
Research Focus
Key Achievements
Top Papers
- 1