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dc.contributor.author
Hardegger, Michael
dc.contributor.author
Roggen, Daniel
dc.contributor.author
Tröster, Gerhard
dc.date.accessioned
2022-08-16T13:57:56Z
dc.date.available
2017-06-11T13:21:52Z
dc.date.available
2017-10-25T16:54:06Z
dc.date.available
2019-10-31T17:29:59Z
dc.date.available
2022-08-16T13:57:56Z
dc.date.issued
2015-01
dc.identifier.issn
1617-4909
dc.identifier.issn
1617-4917
dc.identifier.issn
0949-2054
dc.identifier.other
10.1007/s00779-014-0815-y
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/91534
dc.identifier.doi
10.3929/ethz-b-000091534
dc.description.abstract
We present 3D ActionSLAM, a stand-alone wearable system that can track people in previously unknown multi-floor environments with sub-room accuracy. ActionSLAM stands for action-based simultaneous localization and mapping: It fuses dead reckoning data from a foot-mounted inertial measurement unit with the recognition of location-related actions to build and update a local landmark map. Simultaneously, this map compensates for position drift errors that accumulate in open-loop tracking by means of a particle filter. To evaluate the system performance, we analyzed 23 tracks with a total walked distance of 6,489 m in buildings with up to three floors. The algorithm robustly (93 % of runs converged) mapped the areas with a mean landmark positioning error of 0.59 m. As ActionSLAM is fully stand-alone and not dependent on external infrastructure, it is well suited for patient tracking in remote health care applications. The algorithm is computationally light-weight and runs in real-time on a Samsung Galaxy S4, enabling immediate location-aware feedback. Finally, we propose visualization techniques to facilitate the interpretation of tracking data acquired with 3D ActionSLAM.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Simultaneous localization and mapping
en_US
dc.subject
Indoor tracking
en_US
dc.subject
Pedestrian dead reckoning
en_US
dc.subject
Location- aware computing
en_US
dc.subject
Wearable systems
en_US
dc.title
3D ActionSLAM: Wearable person tracking in multi-floor environments
en_US
dc.type
Journal Article
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2014-09-19
ethz.journal.title
Personal and Ubiquitous Computing
ethz.journal.volume
19
en_US
ethz.journal.issue
1
en_US
ethz.pages.start
123
en_US
ethz.pages.end
141
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02634 - Institut für Elektronik / Institute for Electronics::03388 - Tröster, Gerhard (emeritus)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02634 - Institut für Elektronik / Institute for Electronics::03388 - Tröster, Gerhard (emeritus)
ethz.date.deposited
2017-06-11T13:22:32Z
ethz.source
ECIT
ethz.identifier.importid
imp593652764f2ef17986
ethz.ecitpid
pub:143915
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-10-25T16:54:07Z
ethz.rosetta.lastUpdated
2023-02-07T05:20:52Z
ethz.rosetta.versionExported
true
ethz.COinS
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