A1 Refereed original research article in a scientific journal
Exploiting redundancy for UWB anomaly detection in infrastructure-free multi-robot relative localization
Authors: Salimpour Sahar, Torrico Morón Paola, Yu Xianjia, Westerlund Tomi, Peña-Queralta Jorge
Publisher: Frontiers Research Foundation
Publication year: 2023
Journal: Frontiers in Robotics and AI
Journal name in source: Frontiers in robotics and AI
Journal acronym: Front Robot AI
Article number: 1190296
Volume: 10
ISSN: 2296-9144
eISSN: 2296-9144
DOI: https://doi.org/10.3389/frobt.2023.1190296
Web address : https://doi.org/10.3389/frobt.2023.1190296
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/380480891
Ultra-wideband (UWB) localization methods have emerged as a cost-effective and accurate solution for GNSS-denied environments. There is a significant amount of previous research in terms of resilience of UWB ranging, with non-line-of-sight and multipath detection methods. However, little attention has been paid to resilience against disturbances in relative localization systems involving multiple nodes. This paper presents an approach to detecting range anomalies in UWB ranging measurements from the perspective of multi-robot cooperative localization. We introduce an approach to exploiting redundancy for relative localization in multi-robot systems, where the position of each node is calculated using different subsets of available data. This enables us to effectively identify nodes that present ranging anomalies and eliminate their effect within the cooperative localization scheme. We analyze anomalies created by timing errors in the ranging process, e.g., owing to malfunctioning hardware. However, our method is generic and can be extended to other types of ranging anomalies. Our approach results in a more resilient cooperative localization framework with a negligible impact in terms of the computational workload.
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