Byung-Hee Choi
Papers
3
Total Citations
10
H-Index
2
About
Byung-Hee Choi is a robotics researcher whose work focuses on robust perception and mapping for autonomous mobile robots operating in challenging, real-world environments. His key research areas include multi-modal sensor fusion, place recognition, and resilient localization. Choi’s major contributions address the fragility of traditional sensors—such as cameras and LiDAR—under adverse weather like heavy rain or snow. His highly cited work, “ReFeree” (2024, 5 citations), introduces a radar-based localization method that leverages both feature matching and free-space information to achieve robust place recognition, a critical capability for long-term autonomy. Building on this, his “Uni-Mapper” framework (2025, 3 citations) tackles the difficult problem of unifying maps from different LiDAR modalities, enabling scalable multi-session and multi-robot operations in dynamic environments. Additionally, his earlier work on loosely coupled LiDAR-visual mapping (2022, 2 citations) proposed a “timed elastic band” approach that integrates robot dynamics into path planning for logistics. Through these innovations, Choi is advancing the reliability of autonomous navigation, making his research highly relevant for students and engineers working on field robotics and robust perception systems.
Research Focus
Key Achievements
Top Papers
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