Duan Guangxue
Papers
1
Total Citations
3
H-Index
1
About
Duan Guangxue is a researcher whose work centers on advancing autonomous navigation and perception systems, with a particular focus on lidar-based simultaneous localization and mapping (SLAM). His major contribution lies in addressing critical limitations of traditional Rao-Blackwellized particle filter (RBPF) methods, which often suffer from low accuracy, high particle requirements, and particle degradation. In his 2019 paper, "Simultaneous Localization and Mapping based on Lidar," Duan proposed an improved RBPF-SLAM approach that enhances localization precision and computational efficiency, making it more viable for real-world robotics applications. While his citation count remains modest, with this key work garnering three citations, his research represents a meaningful step toward more robust and scalable SLAM solutions. Duan’s work is particularly relevant for students and researchers exploring sensor fusion and probabilistic robotics, as it highlights the ongoing challenges and innovations in lidar-based mapping. His contributions underscore the importance of refining core algorithms to enable reliable autonomous systems in complex environments.
Research Focus
Key Achievements
Top Papers
- 1Simultaneous Localization and Mapping based on Lidar3 citations · 2019