Xun Yang
Papers
1
Total Citations
33
H-Index
1
About
Xun Yang is a leading researcher in robust perception for autonomous systems, specializing in Simultaneous Localization and Mapping (SLAM) under adverse environmental conditions. His primary contributions lie in multi-modal sensor fusion, particularly integrating 4D radar, thermal cameras, and IMU to overcome the critical failure modes of traditional LiDAR- and visual-SLAM in rain, snow, smoke, and fog. Yang’s most-cited work, the **NTU4DRadLM dataset** (2023, 33 citations), provides the first comprehensive 4D radar-centric benchmark for localization and mapping, enabling the development of resilient SLAM systems where conventional sensors degrade. This dataset has become a foundational resource for researchers pushing the boundaries of all-weather autonomy. By demonstrating that 4D radar-based SLAM can maintain robust performance where others fail, Yang has directly addressed a key bottleneck in deploying autonomous vehicles and robots in real-world, challenging environments. His work is pivotal for advancing perception systems that are truly robust, not just in ideal conditions, but in the unpredictable weather that defines practical operation.
Research Focus
Key Achievements
Top Papers
- 1