Tae-kyeong Lee

Pohang University of Science and Technology

Papers

Total Citations

H-Index

About

Tae-kyeong Lee is a robotics researcher specializing in autonomous mobile systems, with a particular focus on simultaneous localization and mapping (SLAM) — a foundational challenge in enabling robots to navigate and understand unknown environments. His work addresses one of the field's most persistent practical hurdles: building accurate maps when robots are equipped with limited, sparse, or short-range sensors, as is common in consumer and industrial applications such as floor-cleaning robots. Lee's most notable contribution is his development of a hierarchical framework for Rao-Blackwellized Particle Filter (RBPF) SLAM, published in 2011 and accumulating 7 citations, which introduced innovative strategies to compensate for sensor constraints in indoor environments. Building on this foundation, his 2012 work on the Adaptive Sliding Window (ASW) approach advanced hierarchical pose-graph-based SLAM by dynamically adjusting optimization windows for more efficient and scalable mapping, garnering 5 citations. Together, these contributions reflect Lee's commitment to making SLAM algorithms more robust and practically deployable in real-world robotic systems. His research offers valuable insights for students and engineers working at the intersection of probabilistic robotics, computer vision, and autonomous navigation.