A4 Refereed article in a conference publication

Autocalibration of a Mobile UWB Localization System for Ad-Hoc Multi-Robot Deployments in GNSS-Denied Environments




AuthorsCarmen Martínez Almansa, Wang Shule, Jorge Peña Queralta, Tomi Westerlund

EditorsA. Ometov, J. Nurmi, S. Lohan, J. Torres-Sospedra, H. Kuusniemi

Conference nameInternational Conference on Navigation and GNSS

PublisherCEUR-WS

Publication year2020

JournalCEUR Workshop Proceedings

Book title WiP Proceedings of the International Conference on Localization and GNSS (ICL-GNSS 2020) Tampere, Finland, June 2nd to 4th, 2020

Journal name in sourceCEUR Workshop Proceedings

Series titleCEUR Workshop Proceedings

Volume2626

ISSN1613-0073

Web address http://ceur-ws.org/Vol-2626/paper15.pdf

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/50940808


Abstract

Ultra-wideband (UWB) wireless technology has seen an increased penetration in the robotics field as a robust localization method in recent years. UWB enables high accuracy distance estimation from time-of-flight measurements of wireless signals, even in non-line-of-sight measurements. UWB-based localization systems have been utilized in various types of GNSS-denied environments for ground or aerial autonomous robots. However, most of the existing solutions rely on a fixed and well-calibrated set of UWB nodes, or anchors, to estimate accurately the position of other mobile nodes, or tags, through multilateration. This limits the applicability of such systems for dynamic and ad-hoc deployments, such as post-disaster scenarios where the UWB anchors could be mounted on mobile robots to aid the navigation of UAVs or other robots. We introduce a collaborative algorithm for online autocalibration of anchor positions, enabling not only ad-hoc deployments but also movable anchors, based on Decawave's DWM1001 UWB module. Compared to the built-in autocalibration process from Decawave, we drastically reduce the amount of calibration time and increase the accuracy at the same time. We provide both experimental measurements and simulation results to demonstrate the usability of this algorithm.


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Last updated on 2024-26-11 at 11:41