Yanyue Pan
Papers
1
Total Citations
14
H-Index
1
About
Yanyue Pan is a researcher whose work lies at the intersection of robotics, perception, and artificial intelligence, with a particular focus on simultaneous localization and mapping (SLAM) for autonomous systems. Her most-cited paper, "A 2-D LiDAR-SLAM Algorithm for Indoor Similar Environment With Deep Visual Loop Closure" (2023, 14 citations), addresses a critical challenge in indoor robotics: maintaining accurate localization in environments with repetitive geometric features. Pan’s key contribution is the integration of deep visual loop closure detection with traditional LiDAR-based SLAM, effectively fusing geometric and visual cues to reduce drift and improve robustness in visually ambiguous spaces. This hybrid approach demonstrates her ability to bridge classical sensor fusion with modern deep learning techniques, offering a practical solution for real-world robot navigation. While her citation count is still growing, the work signals a promising trajectory in advancing SLAM reliability for indoor service robots and autonomous vehicles. Pan’s research is particularly relevant for students and engineers seeking to understand how neural networks can enhance traditional robotics pipelines, making her a rising voice in the field of intelligent perception systems.
Research Focus
Key Achievements
Top Papers
- 1