Hyun Chul Roh
Papers
7
Total Citations
52
H-Index
4
About
Hyun Chul Roh is a robotics researcher whose work sits at the intersection of computer vision, sensor fusion, and autonomous navigation. His primary contributions lie in two key areas: biologically inspired video stabilization and efficient SLAM (Simultaneous Localization and Mapping) for mobile robots. Drawing inspiration from the human vestibulo-ocular reflex, Roh pioneered video stabilization systems for robot eyes that fuse vision with inertial measurement units (IMUs), enabling robust motion estimation even in challenging 3D environments—a critical capability for humanoid robots and autonomous vehicles. His most cited work, "Video stabilization for robot eye using IMU-aided feature tracker" (19 citations), exemplifies this approach. In SLAM, Roh developed fast, lightweight methods using polar scan matching and particle-weight-based occupancy grid maps, as seen in his 2011 paper (11 citations), which prioritize computational efficiency for real-time indoor navigation. He also contributed to scene understanding for autonomous vehicles through graph-based segmentation of 3D urban maps. With a total of over 50 citations across his published works, Roh’s research has advanced practical, sensor-driven solutions for robot perception and localization, bridging the gap between biological inspiration and engineering application.
Research Focus
Key Achievements
Top Papers
- 1Video stabilization for robot eye using IMU-aided feature tracker19 citations · 2010
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- 3Rapid SLAM using simple map representation in indoor environment9 citations · 2013
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