Ling Xie
Papers
1
Total Citations
4
H-Index
1
About
Ling Xie is a researcher whose work centers on robotics perception and simultaneous localization and mapping (SLAM), with a particular focus on visual loop closure detection. Her most cited paper, "An improved bag of words method for appearance based visual loop closure detection" (2018), addresses a critical challenge in SLAM: enabling a robot to recognize when it has returned to a previously visited location. In this work, Xie proposed an enhanced bag-of-words algorithm that integrates the inverse depth of feature words, improving the robustness and accuracy of appearance-based loop closure detection. This contribution is foundational for long-term autonomous navigation in complex environments, directly impacting place recognition and map consistency in robotics. With 4 citations, this paper has served as a reference for subsequent research in visual SLAM and place recognition. Xie's work demonstrates a clear commitment to solving practical problems in autonomous systems, and her methodological improvements continue to inform the development of more reliable and efficient robotic navigation systems.
Research Focus
Key Achievements
Top Papers
- 1