Hyoungrae Kim
Papers
2
Total Citations
4
H-Index
2
About
Hyoungrae Kim is a robotics researcher whose work centers on mobile robot localization and sensor fusion for autonomous navigation in complex, human-centric environments. His key contributions address the persistent challenge of enabling robots to operate reliably in real-world settings like lobbies and halls, where traditional localization methods often fail. In his 2013 paper "INHA: Localization of Mobile Robots Based on Feature Matching with a Single Camera," Kim introduced the Intuitive Natural landmark-based Homography estimation Algorithm (INHA), a novel approach that leverages feature matching from a single camera to achieve robust localization without relying on expensive or bulky sensors. This work, with 2 citations, laid foundational ideas for vision-based navigation. Building on this, his 2014 study "Elevator Riding of Mobile Robot Using Sensor Fusion" tackled the practical problem of autonomous elevator use—a critical skill for service robots in multi-story buildings. By fusing data from multiple sensors, Kim demonstrated a system that allows robots to seamlessly transition between floors, showcasing his focus on bridging the gap between laboratory research and deployable, everyday robotics. His work exemplifies the incremental but essential steps toward truly autonomous mobile robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2Elevator Riding of Mobile Robot Using Sensor Fusion2 citations · 2014