Comparing Task Simplifications to Learn Closed-Loop Object Picking Using Deep Reinforcement Learning
dc.contributor.author
Breyer, Michel
dc.contributor.author
Furrer, Fadri
dc.contributor.author
Novkovic, Tonci
dc.contributor.author
Siegwart, Roland
dc.contributor.author
Nieto, Juan
dc.date.accessioned
2019-02-18T14:54:41Z
dc.date.available
2019-01-31T22:26:35Z
dc.date.available
2019-02-18T13:39:42Z
dc.date.available
2019-02-18T14:08:18Z
dc.date.available
2019-02-18T14:16:08Z
dc.date.available
2019-02-18T14:54:41Z
dc.date.issued
2019
dc.identifier.uri
http://hdl.handle.net/20.500.11850/322242
dc.identifier.doi
10.3929/ethz-b-000322242
dc.format
application/pdf
dc.language.iso
en
en_US
dc.publisher
Cornell University Library
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.title
Comparing Task Simplifications to Learn Closed-Loop Object Picking Using Deep Reinforcement Learning
en_US
dc.title.alternative
Flexible Robotic Grasping with Sim-to-Real Transfer based Reinforcement Learning
en_US
dc.type
Working Paper
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2019-01-31
ethz.journal.title
arXiv
ethz.pages.start
1803.04996
en_US
ethz.size
8 p.
en_US
ethz.version.edition
Version 2
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ethz.identifier.arxiv
1803.04996
ethz.publication.place
Ithaca, NY
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::03737 - Siegwart, Roland Y. / Siegwart, Roland Y.
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication
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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::03737 - Siegwart, Roland Y. / Siegwart, Roland Y.
ethz.relation.isNewVersionOf
https://arxiv.org/abs/1803.04996v1
ethz.date.deposited
2019-01-31T22:26:35Z
ethz.source
BATCH
ethz.eth
yes
en_US
ethz.availability
Open access
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ethz.rosetta.installDate
2019-02-18T14:08:31Z
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2021-02-15T03:39:05Z
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