Papers
10
Total Citations
99
H-Index
6
About
Yungeun Choe is a robotics researcher whose work bridges the gap between raw sensor data and actionable semantic understanding for autonomous systems operating in complex urban environments. His primary research areas include 3D mapping, urban scene understanding, and practical robot localization. Choe’s major contributions lie in developing efficient, real-time methods for robots to perceive and navigate their surroundings without overwhelming computational resources. Notably, his 2013 paper on “Urban structure classification using the 3D normal distribution transform” (25 citations) introduced a tractable approach using NDT grids, solving the intractable storage and computation issues of prior methods. He further advanced the field with work on online urban object recognition (18 citations) and geometric-featured voxel maps for 3D mapping (10 citations), directly addressing memory and time constraints in rescue robotics. Choe also made notable contributions to construction automation with his vision-based bolting robot system, which used Circular Hough Transform for precise bolt-hole localization. His consistent focus on making robots semantically aware—from autonomous surveillance to vehicle navigation—has established him as a key figure in practical, deployable urban robotics.
Research Focus
Key Achievements
Top Papers
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- 3Geometric-featured voxel maps for 3D mapping in urban environments10 citations · 2011
- 4Vision-based estimation of bolt-hole location using Circular Hough Transform9 citations · 2009
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- 10Bolting robot assistance system using image processing5 citations · 2010