Support Surface Estimation for Legged Robots
dc.contributor.author
Homberger, Timon
dc.contributor.author
Wellhausen, Lorenz
dc.contributor.author
Fankhauser, Péter
dc.contributor.author
Hutter, Marco
dc.date.accessioned
2019-12-10T08:03:36Z
dc.date.available
2019-12-10T08:00:45Z
dc.date.available
2019-12-10T08:03:36Z
dc.date.issued
2019
dc.identifier.isbn
978-1-5386-6027-0
en_US
dc.identifier.isbn
978-1-5386-6026-3
en_US
dc.identifier.isbn
978-1-5386-8176-3
en_US
dc.identifier.other
10.1109/ICRA.2019.8793646
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/384181
dc.identifier.doi
10.3929/ethz-b-000328256
dc.description.abstract
The high agility of legged systems allows them to operate in rugged outdoor environments. In these situations, knowledge about the terrain geometry is key for foothold planning to enable safe locomotion. However, on penetrable or highly compliant terrain (e.g. grass) the visibility of the supporting ground surface is obstructed, i.e. it cannot directly be perceived by depth sensors. We present a method to estimate the underlying terrain topography by fusing haptic information about foot contact closure locations with exteroceptive sensing. To obtain a dense support surface estimate from sparsely sampled footholds we apply Gaussian process regression. Exteroceptive information is integrated into the support surface estimation procedure by estimating the height of the penetrable surface layer from discrete penetration depth measurements at the footholds. The method is designed such that it provides a continuous support surface estimate even if there is only partial exteroceptive information available due to shadowing effects. Field experiments with the quadrupedal robot ANYmal show how the robot can smoothly and safely navigate in dense vegetation.
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.title
Support Surface Estimation for Legged Robots
en_US
dc.type
Conference Paper
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-08-12
ethz.book.title
2019 International Conference on Robotics and Automation (ICRA)
en_US
ethz.pages.start
8470
en_US
ethz.pages.end
8476
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.event
International Conference on Robotics and Automation (ICRA 2019)
en_US
ethz.event.location
Montreal, Canada
en_US
ethz.event.date
May 20-24, 2019
en_US
ethz.identifier.wos
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
en_US
ethz.tag
ANYmal Research
en_US
ethz.date.deposited
2019-02-28T12:02:45Z
ethz.source
FORM
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-12-10T08:00:55Z
ethz.rosetta.lastUpdated
2019-12-10T08:03:50Z
ethz.rosetta.versionExported
true
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/328256
dc.identifier.olduri
http://hdl.handle.net/20.500.11850/383570
ethz.COinS
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