Title: Inertially-Aided Navigation with Ultra-Wideband Wireless Ranging
Date: Wednesday, April 16th, 2025
Time:  4 PM - 6 PM EST
Location: Virtual
Virtual Link: Teams
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Meeting ID: 246 749 870 46
Passcode: db64fe2E
Fan Jiang
Robotics PhD Candidate
WiSciTech Lab & BORG Lab
Georgia Institute of Technology

Committee
Dr. Ashutosh Dhekne (Advisor), School of Interactive Computing, Georgia Tech
Dr. Frank Dellaert (Advisor), School of Interactive Computing, Georgia Tech
Dr. Seth Hutchinson, Khoury College of Computer Sciences, Northeastern University
Dr. Lu Gan, Daniel Guggenheim School of Aerospace Engineering, Georgia Tech
Dr. Deepak Vasisht, Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign

Abstract
Radio-based sensing offers compelling advantages over optical systems, particularly in challenging environments where visual solutions face limitations. However, their deployment in real applications was limited by effects such as non-line-of-sight (NLOS) propagation. This dissertation investigates the integration of Ultra-Wideband (UWB) range sensing with inertial measurements for robust localization and navigation. Despite UWB's one-dimensional measurement constraint compared to rich visual data, we demonstrate that strategic fusion with inertial sensors can robustly achieve centimeter-level accuracy. The thesis presents three significant new contributions: (1) a comprehensive framework for indoor localization using low-power UWB-IMU fusion; (2) a novel motion capture system achieving competitive accuracy to visual systems for AR/VR applications; and (3) self-calibrated localization methods for UWB-IMU sensor networks in unknown environments. Through theoretical analysis and experimental validation, we provide solutions to fundamental challenges in sensor calibration, optimal data fusion, and real-time implementation, establishing a foundation for radio-based localization in diverse applications where reliability and precision are paramount.