Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion

This article proposes a generalized UltraWideBand (UWB)-Zero-velocity-UPdaTe (ZUPT)-simultaneous localization and mapping (SLAM) algorithm, a SLAM approach, utilizing a combination of foot-mounted localization systems integrating inertial measurement units (IMUs), UWB modules, barometers, and dynami...

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Main Authors: Chi-Shih Jao, Danmeng Wang, Changwei Chen, Eudald Sangenis, Joe Grasso, Solmaz S. Kia, Andrei M. Shkel
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Indoor and Seamless Positioning and Navigation
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Online Access:https://ieeexplore.ieee.org/document/10283865/
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author Chi-Shih Jao
Danmeng Wang
Changwei Chen
Eudald Sangenis
Joe Grasso
Solmaz S. Kia
Andrei M. Shkel
author_facet Chi-Shih Jao
Danmeng Wang
Changwei Chen
Eudald Sangenis
Joe Grasso
Solmaz S. Kia
Andrei M. Shkel
author_sort Chi-Shih Jao
collection DOAJ
description This article proposes a generalized UltraWideBand (UWB)-Zero-velocity-UPdaTe (ZUPT)-simultaneous localization and mapping (SLAM) algorithm, a SLAM approach, utilizing a combination of foot-mounted localization systems integrating inertial measurement units (IMUs), UWB modules, barometers, and dynamically-deployed beacons incorporating UWB, IMUs, and reference barometers. The proposed approach leverages a ZUPT-aided Inertial Navigation System augmented with self-contained sensor fusion techniques to map unknown UWB beacons dynamically deployed in an environment during navigation and then utilizes the localized beacons to bound position error propagation. An experimental testbed was developed, and we conducted two series of experiments to validate the performance of the proposed approach. The first experiment involved high-accuracy motion capture cameras in generating ground truth, and the results showed that the proposed approach estimated positions of UWB beacons with a maximum localization error of 0.36 m, when deployed during the first 15 and 20 s of the navigation. In the second experiment, a pedestrian traveled for around 3.5 km in 1 h in a large multifloor indoor environment and deployed seven beacons, during the first 63, 151, 290, 399, 517, 585, and 786 s of the experiment. The proposed generalized UWB-ZUPT-SLAM had a 3-D mean absolute error of 0.48 m in this experiment, equivalent to 0.013% traveling distance.
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spelling doaj-art-0cf39a2d55bc47d4a3b9507102b2013e2025-08-20T02:57:17ZengIEEEIEEE Journal of Indoor and Seamless Positioning and Navigation2832-73222023-01-011809210.1109/JISPIN.2023.332427910283865Augmented UWB-ZUPT-SLAM Utilizing Multisensor FusionChi-Shih Jao0https://orcid.org/0000-0003-4695-2034Danmeng Wang1https://orcid.org/0000-0002-7671-0418Changwei Chen2https://orcid.org/0000-0001-6608-5519Eudald Sangenis3https://orcid.org/0009-0009-8476-4019Joe Grasso4https://orcid.org/0009-0000-6075-2958Solmaz S. Kia5https://orcid.org/0000-0002-8492-6913Andrei M. Shkel6https://orcid.org/0000-0001-5517-7709Department of Mechanical And Aerospace Engineering, University of California, Irvine, CA, USADepartment of Mechanical And Aerospace Engineering, University of California, Irvine, CA, USADepartment of Mechanical And Aerospace Engineering, University of California, Irvine, CA, USADepartment of Mechanical And Aerospace Engineering, University of California, Irvine, CA, USAPublic Safety Communications Research Division, National Institute of Standard and Technology, Boulder, CO, USADepartment of Mechanical And Aerospace Engineering, University of California, Irvine, CA, USADepartment of Mechanical And Aerospace Engineering, University of California, Irvine, CA, USAThis article proposes a generalized UltraWideBand (UWB)-Zero-velocity-UPdaTe (ZUPT)-simultaneous localization and mapping (SLAM) algorithm, a SLAM approach, utilizing a combination of foot-mounted localization systems integrating inertial measurement units (IMUs), UWB modules, barometers, and dynamically-deployed beacons incorporating UWB, IMUs, and reference barometers. The proposed approach leverages a ZUPT-aided Inertial Navigation System augmented with self-contained sensor fusion techniques to map unknown UWB beacons dynamically deployed in an environment during navigation and then utilizes the localized beacons to bound position error propagation. An experimental testbed was developed, and we conducted two series of experiments to validate the performance of the proposed approach. The first experiment involved high-accuracy motion capture cameras in generating ground truth, and the results showed that the proposed approach estimated positions of UWB beacons with a maximum localization error of 0.36 m, when deployed during the first 15 and 20 s of the navigation. In the second experiment, a pedestrian traveled for around 3.5 km in 1 h in a large multifloor indoor environment and deployed seven beacons, during the first 63, 151, 290, 399, 517, 585, and 786 s of the experiment. The proposed generalized UWB-ZUPT-SLAM had a 3-D mean absolute error of 0.48 m in this experiment, equivalent to 0.013% traveling distance.https://ieeexplore.ieee.org/document/10283865/Differential barometerextended Kalman filter (EKF)embedded systemsinertial measurement unit (IMU)indoor navigationinertial navigation
spellingShingle Chi-Shih Jao
Danmeng Wang
Changwei Chen
Eudald Sangenis
Joe Grasso
Solmaz S. Kia
Andrei M. Shkel
Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion
IEEE Journal of Indoor and Seamless Positioning and Navigation
Differential barometer
extended Kalman filter (EKF)
embedded systems
inertial measurement unit (IMU)
indoor navigation
inertial navigation
title Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion
title_full Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion
title_fullStr Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion
title_full_unstemmed Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion
title_short Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion
title_sort augmented uwb zupt slam utilizing multisensor fusion
topic Differential barometer
extended Kalman filter (EKF)
embedded systems
inertial measurement unit (IMU)
indoor navigation
inertial navigation
url https://ieeexplore.ieee.org/document/10283865/
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AT eudaldsangenis augmenteduwbzuptslamutilizingmultisensorfusion
AT joegrasso augmenteduwbzuptslamutilizingmultisensorfusion
AT solmazskia augmenteduwbzuptslamutilizingmultisensorfusion
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