Yuexin Fu
Papers
1
Total Citations
5
H-Index
1
About
Yuexin Fu is a researcher specializing in visual simultaneous localization and mapping (VSLAM) for mobile robotics, with a particular focus on indoor navigation and perception. Her most cited work introduces a closed-loop detection algorithm that enhances VSLAM performance by dynamically updating the bag-of-words model in real time, addressing critical challenges such as poor loop closure and low localization accuracy in monocular camera-based systems. This contribution directly improves the reliability of autonomous robots operating in complex indoor environments. With over 5 citations on this key paper, Fu’s research demonstrates practical impact in advancing real-time mapping and localization technologies. Her work is notable for bridging algorithmic efficiency with robust deployment, offering a scalable solution for mobile robots that require continuous adaptation to changing scenes. Fu’s contributions are valuable for students and researchers exploring VSLAM, computer vision, and autonomous navigation, as they highlight the importance of adaptive models in overcoming traditional limitations of static bag-of-words approaches.
Research Focus
Key Achievements
Top Papers
- 1