Daehee Kang

Tokyo University of Science, The University of Tokyo

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About

Daehee Kang is a robotics researcher whose work has focused primarily on mobile robot navigation, autonomous path planning, and sensor-based position estimation. Active in the late 1990s and early 2000s, Kang made meaningful contributions to the field of autonomous mobile systems at a time when reliable robot navigation remained a significant technical challenge. Kang's most influential work centers on developing efficient path generation algorithms for mobile robots operating in known environments. His 2002 paper on genetic algorithm-based path planning, which has garnered 23 citations, introduced a modified quadtree data structure to model environments and compute optimal or shortest routes—a practical approach that advanced global path planning methodology. This work built upon earlier foundations he established in a 1997 predecessor study exploring the same core problem. Complementing his navigation research, Kang also investigated mobile robot position estimation through sensor fusion techniques, addressing the well-known limitations of dead reckoning, which accumulates errors over time. His proposed fusion methods offered improved localization accuracy, particularly in partially known environments, contributing to the broader challenge of reliable autonomous operation. Together, these works reflect a cohesive research agenda aimed at making mobile robots more capable, precise, and practically deployable in real-world settings.