Sung Kee Park

Korea Institute of Science and Technology

Papers

Total Citations

H-Index

About

Sung Kee Park is a researcher specializing in mobile robotics, computer vision, and autonomous navigation systems. His most notable contribution lies in the development of innovative environment modeling techniques for indoor mobile robots, particularly through his 2004 work on direct depth and color-based environment modeling. In this influential study, Park pioneered a method that leverages stereo camera technology to perform simultaneous mapping and localization, using raw depth and color information extracted directly from image pixels as visual features — a streamlined approach that reduced computational complexity by focusing analysis on the horizontal centerline of captured images. This work demonstrated practical advances in how robots perceive and navigate real-world indoor spaces, contributing meaningfully to the broader field of robot perception and SLAM (Simultaneous Localization and Mapping). With 11 citations, his research has informed subsequent work in autonomous mobile systems. Park's contributions reflect a strong commitment to bridging theoretical computer vision principles with applied robotics, making his work particularly relevant to students and researchers exploring sensor-based navigation, environmental representation, and intelligent robotic systems operating in unstructured indoor environments.