Tae Bum Kwon

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About

Tae Bum Kwon is a robotics researcher whose work focuses on advancing autonomous navigation for mobile robots, particularly in challenging outdoor environments where GPS signals are unreliable or unavailable. His key research areas include simultaneous localization and mapping (SLAM), topological mapping, and elevation map-based localization. Kwon’s most influential contribution is his 2007 paper on “SLAM of a Mobile Robot using Thinning-based Topological Information,” which has garnered 23 citations and introduced a novel approach to topological SLAM by leveraging thinning algorithms to extract meaningful spatial features. Building on this, his 2009 work on “Extraction and Matching of Elevation Moment of Inertia for Elevation Map-based Localization of an Outdoor Mobile Robot” (9 citations) tackles the critical problem of GPS-denied outdoor navigation. In this paper, Kwon proposes a groundbreaking feature—the elevation moment of inertia—that enables robots to localize themselves using only elevation maps, offering a robust alternative to satellite-based positioning. His research has practical implications for field robotics, including search-and-rescue and planetary exploration. By addressing fundamental limitations of GPS, Kwon’s work continues to inspire new approaches to reliable, autonomous outdoor navigation.