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dc.contributor.author
Fankhauser, Péter
dc.contributor.author
Bloesch, Michael
dc.contributor.author
Hutter, Marco
dc.date.accessioned
2019-03-26T10:33:56Z
dc.date.available
2018-06-25T13:45:27Z
dc.date.available
2018-06-25T14:02:33Z
dc.date.available
2019-03-26T10:33:56Z
dc.date.issued
2018-10
dc.identifier.issn
2377-3766
dc.identifier.other
10.1109/lra.2018.2849506
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/272110
dc.identifier.doi
10.3929/ethz-b-000272110
dc.description.abstract
Mobile robots build on accurate, real-time mapping with onboard range sensors to achieve autonomous navigation over rough terrain. Existing approaches often rely on absolute localization based on tracking of external geometric or visual features. To circumvent the reliability-issues of these approaches, we propose a novel terrain mapping method which bases on proprioceptive localization from kinematic and inertial measurements only. The proposed method incorporates the drift and uncertainties of the state estimation and a noise model of the distance sensor. It yields a probabilistic terrain estimate as a grid-based elevation map including upper and lower confidence bounds. We demonstrate the effectiveness of our approach with simulated datasets and real-world experiments for real-time terrain mapping with legged robots and compare the terrain reconstruction to ground truth reference maps.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Mapping
en_US
dc.subject
Field Robots
en_US
dc.subject
Legged Robots
en_US
dc.title
Probabilistic Terrain Mapping for Mobile Robots with Uncertain Localization
en_US
dc.type
Journal Article
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2018-06-21
ethz.journal.title
IEEE Robotics and Automation Letters
ethz.journal.volume
3
en_US
ethz.journal.issue
4
en_US
ethz.pages.start
3019
en_US
ethz.pages.end
3026
en_US
ethz.size
8 p.
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09570 - Hutter, Marco / Hutter, Marco
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02620 - Inst. f. Robotik u. Intelligente Systeme / Inst. Robotics and Intelligent Systems::09570 - Hutter, Marco / Hutter, Marco
en_US
ethz.tag
RSL
en_US
ethz.tag
ANYmal Research
en_US
ethz.tag
ETH Zurich
en_US
ethz.date.deposited
2018-06-25T13:45:28Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-03-26T10:34:07Z
ethz.rosetta.lastUpdated
2019-03-26T10:34:07Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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