Chang Hun Sung

Korea Advanced Institute of Science and Technology

Papers

Total Citations

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About

Chang Hun Sung is a robotics researcher whose work centers on a critical challenge in autonomous navigation: Simultaneous Localization and Mapping (SLAM). His primary contributions lie in developing efficient, practical SLAM solutions specifically tailored for indoor mobile robots. Sung’s most influential work, "Fast SLAM using polar scan matching and particle weight based occupancy grid map" (2011, 11 citations), introduced a novel method that leverages particle weights to build occupancy grid maps, significantly improving mapping accuracy and speed in indoor settings. He further advanced this field with "Rapid SLAM using simple map representation in indoor environment" (2013, 9 citations), which proposed a streamlined map representation to reduce computational overhead without sacrificing performance. Beyond SLAM, Sung explored visual localization techniques, as seen in his work on "Point pattern matching based visual global localization using ceiling lights" (2011, 3 citations), which demonstrated a high-accuracy, fast-update system ideal for service guide robots in exhibitions. Collectively, Sung’s research has provided foundational algorithms that balance robustness with computational efficiency, making them particularly valuable for real-world robot deployment. His work continues to influence the design of practical, low-cost navigation systems for indoor autonomous agents.