Xuan Tan

Changsha University of Science and Technology, Hunan University

Papers

Total Citations

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About

Xuan Tan is a robotics and indoor positioning researcher whose work sits at the intersection of sensor fusion, autonomous navigation, and mobile robotics — with particular emphasis on ultra-wideband (UWB) technology and its practical applications. Tan's most significant contribution lies in developing robust indoor localization frameworks that address the persistent challenges of multipath interference and non-line-of-sight (NLOS) errors inherent to UWB systems. Their 2022 paper introducing a Dynamic Window-Based UWB-Odometer Fusion approach has garnered 27 citations, establishing it as a noteworthy contribution to the field, while complementary work on Weight Adaptive Kalman Filter localization further demonstrates a sophisticated command of probabilistic estimation techniques for robot positioning. Beyond foundational localization research, Tan has applied these capabilities to socially relevant problems, including epidemic prevention robots and UVC disinfection systems designed for hospital ward environments — research motivated in part by the challenges of the COVID-19 pandemic. This blend of technical rigor and real-world application reflects a research philosophy centered on deployable, cost-effective robotic solutions. With a growing body of work spanning graph-based SLAM and multi-sensor fusion, Tan represents an emerging voice in intelligent mobile robotics and healthcare automation.