  Understanding the location of ultra-wideband (UWB) tag-attached objects and
people in the real world is vital to enabling a smooth cyber-physical
transition. However, most UWB localization systems today require multiple
anchors in the environment, which can be very cumbersome to set up. In this
work, we develop XRLoc, providing an accuracy of a few centimeters in many
real-world scenarios. This paper will delineate the key ideas which allow us to
overcome the fundamental restrictions that plague a single anchor point from
localization of a device to within an error of a few centimeters. We deploy a
VR chess game using everyday objects as a demo and find that our system
achieves $2.4$ cm median accuracy and $5.3$ cm $90^\mathrm{th}$ percentile
accuracy in dynamic scenarios, performing at least $8\times$ better than
state-of-art localization systems. Additionally, we implement a MAC protocol to
furnish these locations for over $10$ tags at update rates of $100$ Hz, with a
localization latency of $\sim 1$ ms.

Human-Computer Interaction;Networking and Internet Architecture;Robotics;Signal Processing