Kyoung Ho Lee

Seoul National University, Incheon National University

Papers

Total Citations

100

H-Index

About

Kyoung Ho Lee is a pioneering researcher in robotics and autonomous systems, whose work bridges the gap between classical perception and modern deep learning for intelligent navigation. His early, highly influential contribution—the 2006 paper on "Visual SLAM with Line and Corner Features," which has garnered 95 citations—established a foundational approach to simultaneous localization and mapping by fusing geometric landmarks within an extended Kalman filter framework. This work remains a touchstone for vision-based SLAM systems. More recently, Dr. Lee has advanced the frontier of robotic path planning by integrating mission specifications expressed through Linear Temporal Logic (LTL) with deep learning architectures. His 2024 papers introduce novel frameworks—including a Transformer Variational Autoencoder and a deep learning model for co-safe LTL specifications—that enable robots to generate high-quality, cost-aware trajectories while adhering to complex temporal logic constraints. Though newly published, these works signal a significant shift toward semantically aware, mission-conditioned autonomy. Dr. Lee’s research trajectory demonstrates a rare ability to evolve from robust geometric methods to cutting-edge, logic-driven AI, making his contributions essential for students and researchers seeking to understand the future of intelligent robotic navigation.