Xuanfu Li
Papers
1
Total Citations
102
H-Index
1
About
Xuanfu Li is a leading researcher in robotics perception, with a primary focus on simultaneous localization and mapping (SLAM) in complex, real-world environments. His key contributions lie in developing robust SLAM systems that can operate reliably under challenging conditions, particularly in dynamic settings where traditional algorithms fail. His most cited work, "RGB-D Inertial Odometry for a Resource-Restricted Robot in Dynamic Environments" (2022, 102 citations), addresses the critical problem of SLAM failure in environments with moving objects. By integrating deep learning-based semantic information, Li’s approach enables resource-constrained robots to filter out dynamic disturbances, significantly improving localization accuracy and robustness. This work has been highly influential in advancing practical, deployable SLAM solutions for mobile robots. Li’s research bridges the gap between theoretical SLAM algorithms and real-world deployment, making him a notable figure in the field of autonomous navigation and robotic perception.
Research Focus
Key Achievements
Top Papers
- 1RGB-D Inertial Odometry for a Resource-Restricted Robot in Dynamic Environments102 citations · 2022