A Novel Loosely Coupling Fusion Approach of Ultra-Wideband and Wheel Odometry for Indoor Localisation

Liu, A; Lin, S; Wang, J; Kong, X

A Novel Loosely Coupling Fusion Approach of Ultra-Wideband and Wheel Odometry for Indoor Localisation

Liu, A Lin, S Wang, J

Kong, X

Permalink

Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Electronics (Switzerland), 2023, 12, (21)
Issue Date:: 2023-11-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Download full textAdobe PDF (3.28 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Liu, A
dc.contributor.author	Lin, S
dc.contributor.author	Wang, J https://orcid.org/0000-0002-6282-0456
dc.contributor.author	Kong, X
dc.date.accessioned	2024-01-22T04:57:53Z
dc.date.available	2024-01-22T04:57:53Z
dc.date.issued	2023-11-01
dc.identifier.citation	Electronics (Switzerland), 2023, 12, (21)
dc.identifier.issn	1450-5843
dc.identifier.issn	2079-9292
dc.identifier.uri	http://hdl.handle.net/10453/174839
dc.description.abstract	Ultra-wideband (UWB) systems promise centimetre-level accuracy for indoor positioning, yet they remain susceptible to non-line-of-sight (NLOS) errors due to complex indoor environments. A fusion mechanism that integrates the UWB with an odometer sensor is introduced to address this challenge and achieve a high positioning accuracy. A sliding window method is applied to identify NLOS anchors effectively. The modified UWB-only positioning has an average error under 13 cm with an RMSE of 16 cm. Then, a loosely coupled approach named Dynamic Dimension Fusion (DDF) is designed to mitigate the odometer’s cumulative errors that achieve a remarkable average error and RMSE below 5 cm, notably superior to established unscented Kalman filter (UKF) fusion techniques. DDF utilises UWB data to correct the one-dimensional heading error of the odometer when the robot moves in a straight line and to correct both heading and mileage in two dimensions when the robot is turning. Comprehensive real-world experimental evaluations underscore the efficacy and robustness of this novel approach.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Electronics (Switzerland)
dc.relation.isbasedon	10.3390/electronics12214499
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.title	A Novel Loosely Coupling Fusion Approach of Ultra-Wideband and Wheel Odometry for Indoor Localisation
dc.type	Journal Article
utslib.citation.volume	12
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	open_access	*
dc.date.updated	2024-01-22T04:57:48Z
pubs.issue	21
pubs.publication-status	Published
pubs.volume	12
utslib.citation.issue	21

Abstract:

Ultra-wideband (UWB) systems promise centimetre-level accuracy for indoor positioning, yet they remain susceptible to non-line-of-sight (NLOS) errors due to complex indoor environments. A fusion mechanism that integrates the UWB with an odometer sensor is introduced to address this challenge and achieve a high positioning accuracy. A sliding window method is applied to identify NLOS anchors effectively. The modified UWB-only positioning has an average error under 13 cm with an RMSE of 16 cm. Then, a loosely coupled approach named Dynamic Dimension Fusion (DDF) is designed to mitigate the odometer’s cumulative errors that achieve a remarkable average error and RMSE below 5 cm, notably superior to established unscented Kalman filter (UKF) fusion techniques. DDF utilises UWB data to correct the one-dimensional heading error of the odometer when the robot moves in a straight line and to correct both heading and mileage in two dimensions when the robot is turning. Comprehensive real-world experimental evaluations underscore the efficacy and robustness of this novel approach.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/174839