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http://dx.doi.org/10.18419/opus-13369
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DC Element | Wert | Sprache |
---|---|---|
dc.contributor.author | Kleeberger, Kilian | - |
dc.contributor.author | Bormann, Richard | - |
dc.contributor.author | Kraus, Werner | - |
dc.contributor.author | Huber, Marco F. | - |
dc.date.accessioned | 2023-08-04T11:57:33Z | - |
dc.date.available | 2023-08-04T11:57:33Z | - |
dc.date.issued | 2020 | de |
dc.identifier.issn | 2662-4087 | - |
dc.identifier.other | 1858462568 | - |
dc.identifier.uri | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-133881 | de |
dc.identifier.uri | http://elib.uni-stuttgart.de/handle/11682/13388 | - |
dc.identifier.uri | http://dx.doi.org/10.18419/opus-13369 | - |
dc.description.abstract | This review provides a comprehensive overview of machine learning approaches for vision-based robotic grasping and manipulation. Current trends and developments as well as various criteria for categorization of approaches are provided. Model-free approaches are attractive due to their generalization capabilities to novel objects, but are mostly limited to top-down grasps and do not allow a precise object placement which can limit their applicability. In contrast, model-based methods allow a precise placement and aim for an automatic configuration without any human intervention to enable a fast and easy deployment. Both approaches to robotic grasping and manipulation with and without object-specific knowledge are discussed. Due to the large amount of data required to train AI-based approaches, simulations are an attractive choice for robot learning. This article also gives an overview of techniques and achievements in transfers from simulations to the real world. | en |
dc.description.sponsorship | Projekt DEAL | de |
dc.language.iso | en | de |
dc.relation.uri | doi:10.1007/s43154-020-00021-6 | de |
dc.rights | info:eu-repo/semantics/openAccess | de |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | de |
dc.subject.ddc | 004 | de |
dc.subject.ddc | 620 | de |
dc.title | A survey on learning-based robotic grasping | en |
dc.type | article | de |
dc.date.updated | 2023-05-16T02:00:41Z | - |
ubs.fakultaet | Konstruktions-, Produktions- und Fahrzeugtechnik | de |
ubs.fakultaet | Externe wissenschaftliche Einrichtungen | de |
ubs.institut | Institut für Industrielle Fertigung und Fabrikbetrieb | de |
ubs.institut | Fraunhofer Institut für Produktionstechnik und Automatisierung (IPA) | de |
ubs.publikation.seiten | 239-249 | de |
ubs.publikation.source | Current robotics reports 1 (2020), S. 239-249 | de |
ubs.publikation.typ | Zeitschriftenartikel | de |
Enthalten in den Sammlungen: | 07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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s43154-020-00021-6.pdf | 1,69 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons