Hoo-Cheol Lee

Papers

Total Citations

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About

Hoo-Cheol Lee is a researcher whose work sits at the intersection of construction automation and mobile robotics, with a particular focus on visual servoing and state estimation. His most influential contribution, "Vision-based estimation of bolt-hole location using Circular Hough Transform" (2009, 9 citations), introduced a novel visual servo control scheme for a Bolting Robot, enabling precise tracking of bolt holes in structural steel frames—a key step toward automating construction tasks. Lee also advanced particle filtering techniques in "Improved adaptive particle filter using adjusted variance and gradient data" (2008, 6 citations), addressing the critical challenge of real-time position estimation in mobile robotics by optimizing sample efficiency. His work demonstrates a pragmatic engineering approach, bridging computer vision and probabilistic robotics to solve real-world problems in unstructured environments. While his citation counts reflect a focused, early-career impact, Lee’s contributions are notable for their direct applicability to construction automation—a field where robust, vision-guided manipulation remains a frontier. His research offers valuable insights for students and engineers working at the nexus of robotics, computer vision, and field automation.