Xiangdi Yue
Papers
1
Total Citations
50
H-Index
1
About
Xiangdi Yue is a leading researcher in robotic perception and autonomous navigation, with a primary focus on LiDAR-based simultaneous localization and mapping (SLAM) for robotic mapping. His most-cited work, the comprehensive 2023 survey "LiDAR-based SLAM for robotic mapping: state of the art and new frontiers," has already garnered 50 citations, reflecting its rapid impact as a definitive reference for both researchers and engineers. In this paper, Yue systematically reviews decades of progress in LiDAR SLAM, critically analyzing core algorithms from front-end odometry to back-end optimization, and identifies emerging frontiers such as deep learning integration and multi-sensor fusion. By distilling complex technical landscapes into clear taxonomies and performance benchmarks, his work serves as an essential guide for advancing robust, real-time mapping in unstructured environments. Yue’s contributions are pivotal for applications ranging from autonomous vehicles to field robotics, and his survey continues to shape the direction of next-generation SLAM research.
Research Focus
Key Achievements
Top Papers
- 1LiDAR-based SLAM for robotic mapping: state of the art and new frontiers50 citations · 2023