Kyung-Bin Bae

Papers

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About

Kyung-Bin Bae is a robotics researcher whose work centers on ultra-wideband (UWB) localization and autonomous target-following systems for mobile robots. His primary contributions lie in developing robust, high-accuracy positioning methods that enable robots to track and follow targets reliably in real-world industrial environments. His most cited paper, "Component-Wise Error Correction Method for UWB-Based Localization in Target-Following Mobile Robot" (2022, 9 citations), introduces a novel approach that leverages a least-square approximation framework to correct component-wise errors in UWB signals. This method significantly enhances tracking precision and resilience against signal noise, addressing a critical bottleneck in autonomous following applications. Bae’s research bridges the gap between theoretical localization algorithms and practical deployment, offering solutions that improve robot autonomy and safety. His work is particularly relevant for logistics, manufacturing, and service robotics, where accurate, real-time target tracking is essential. With a growing citation impact, Bae is establishing himself as a contributor to the advancement of sensor fusion and error correction in mobile robotics, laying groundwork for more intelligent and responsive autonomous systems.