Accommodation of NLOS for ultra-wideband TDOA localization in single- and multi-robot systems

Abstract

Ultra-wideband (UWB) localization is one of the most promising indoor localization methods. Yet, non-line-of-sight (NLOS) positioning scenarios can potentially cause significant localization errors and remain a challenge. In this work, we propose a novel, probabilistic UWB TDOA error model which explicitly takes into account NLOS. In order to validate our approach systematically in a real world setup, we leverage the utility of a group of mobile robots, and introduce our error model into a real-time localization framework run onboard the robots. We subsequently extend our framework by employing a collaborative localization strategy which enables the sharing of inter-robot, relative position observations. Our experimental results show how the novel TDOA error model is able to improve localization performance when information on the LOS/NLOS path condition is available. These results are complemented by additional experiments which show how a collaborative team of robots is able to significantly improve localization performance when no information on the LOS/NLOS path condition is available.