Jaehong Lee

Papers

Total Citations

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About

Jaehong Lee is a robotics researcher specializing in mobile robot perception, sensor fusion, and autonomous navigation in complex indoor environments. His work focuses on enabling service robots to operate seamlessly in human-centric spaces, particularly addressing the challenge of moving between building floors—a critical capability for practical deployment. Lee’s most notable contribution is his pioneering approach to elevator door recognition and riding, where he developed a robust sensor fusion method combining Laser Range Finder (LRF) data with camera vision. This technique, detailed in his 2012 paper (9 citations), extracts line segments from laser scans to detect elevator doors, overcoming limitations of single-sensor systems. He further advanced this with the INHA (Intuitive Natural landmark-based Homography estimation Algorithm) localization method, which uses feature matching with a single camera to solve robot positioning in challenging real-world lobbies and halls. His 2014 work on elevator riding integrates these approaches into a complete system for autonomous floor transitions. While his citation counts reflect a focused, early-career impact, Lee’s contributions are foundational for mobile service robotics, directly addressing practical barriers to multi-floor autonomy. His research exemplifies how sensor fusion can bridge the gap between laboratory prototypes and real-world robotic assistants.