An Experimental Study of Two-way Ranging Optimization in UWB-based Simultaneous Localization and Wall-Mapping Systems

Abstract

In this paper, we propose a new ultra-wideband (UWB)-based simultaneous localization and wall-mapping (SLAM) system, which adopts two-way ranging optimization on UWB anchor and tag nodes to track the target's real-time movement in an unknown area. The proposed UWB-based SLAM system captures time difference of arrival (TDoA) of the anchor nodes' signals over a line-of-sight propagation path and reflected paths. The real-time location of the UWB tag is estimated according to the real-time TDoA measurements. To minimize the estimation error resulting from background noise in the two-way ranging, a Least Squares Method is implemented to minimize the estimation error for the localization of a static target, while Kalman Filter is applied for the localization of a mobile target. An experimental testbed is built based on off-the-shelf UWB hardware. Experiments validate that a reflector, e.g., a wall, and the UWB tag can be located according to the two-way ranging measurement. The localization accuracy of the proposed SLAM system is also evaluated, where the difference between the estimated location and the ground truth trajectory is less than 15cm.

When Internet of Things Meets Metaverse: Convergence of Physical and Cyber Worlds

“…Digital twins are one of the core building blocks of the Metaverse due to their unique nature. The IoT-empowered Metaverse helps people create virtual worlds and experiences beyond the wildest dreams, and build exact replicas of reality that can bring reality to the digital world [202], [203].…”