Chiyun Noh
Papers
1
Total Citations
6
H-Index
1
About
Chiyun Noh is a robotics researcher whose work centers on advancing perception and localization in complex, real-world environments, with a particular focus on radar-based simultaneous localization and mapping (SLAM). His major contribution is the development of HeRCULES, a heterogeneous radar dataset designed for multi-session SLAM in challenging urban settings. This dataset uniquely integrates both spinning and phased-array radars, addressing a critical gap in the field where prior datasets only featured a single radar type. By enabling robust performance under adverse weather conditions—such as fog, rain, and snow—Noh’s work directly supports the deployment of autonomous systems in environments where cameras and LiDAR fail. Though recently published in 2025, HeRCULES has already garnered 6 citations, signaling strong early impact. Noh’s research is notable for its practical emphasis on sensor diversity and long-term autonomy, providing a foundational resource for researchers tackling real-world navigation challenges. His efforts are paving the way for more resilient robotic systems in complex urban landscapes.
Research Focus
Key Achievements
Top Papers
- 1