Hyung-Rae Kim

Papers

Total Citations

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About

Hyung-Rae Kim is a robotics researcher whose work focuses on sensor fusion and perception systems for mobile service robots operating in human-centric environments. His most-cited paper, "Robust Elevator Door Recognition using LRF and Camera" (2012, 9 citations), addresses a critical challenge in autonomous navigation: enabling robots to move between floors in buildings. Kim proposed a novel sensor fusion approach combining Laser Range Finder (LRF) data with camera imagery, using laser scans to extract line segments and detect candidate elevator doors with improved robustness. This work exemplifies his broader contributions to integrating multiple sensing modalities to solve real-world robotic perception problems. While his citation count reflects a focused, early-career impact, Kim's research is notable for tackling practical, infrastructure-specific challenges that are essential for deploying service robots in complex indoor environments. His approach to elevator door recognition demonstrates a methodical engineering mindset, prioritizing reliability and real-world applicability over theoretical complexity. For students and researchers in robotics, Kim's work offers a clear example of how sensor fusion can overcome the limitations of individual sensors in autonomous navigation tasks.