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A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context
dc.contributor.author | Outón Méndez, José Luis | |
dc.contributor.author | Merino Bermejo, Ibon | |
dc.contributor.author | Villaverde, Iván | |
dc.contributor.author | Ibarguren Soldevilla, Aitor | |
dc.contributor.author | Herrero Cueva, Héctor | |
dc.contributor.author | Daelman, Paul | |
dc.contributor.author | Sierra Araujo, Basilio ![]() | |
dc.date.accessioned | 2021-06-14T12:31:18Z | |
dc.date.available | 2021-06-14T12:31:18Z | |
dc.date.issued | 2021-05-27 | |
dc.identifier.citation | Electronics 10(11) : (2021) // Article ID 1276 | es_ES |
dc.identifier.issn | 2079-9292 | |
dc.identifier.uri | http://hdl.handle.net/10810/51859 | |
dc.description.abstract | In modern industry there are still a large number of low added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative tasks between a robot and a human. To be able to do this, AIMMs need to have a variety of advanced cognitive skills like autonomous navigation, smart perception and task management. In this paper, we report the project’s tackle in a paradigmatic industrial application combining accurate autonomous navigation with deep learning-based 3D perception for pose estimation to locate and manipulate different industrial objects in an unstructured environment. The proposed method presents a combination of different technologies fused in an AIMM that achieve the proposed objective with a success rate of 83.33% in tests carried out in a real environment. | es_ES |
dc.description.sponsorship | This research was funded by EC research project “SHERLOCK—Seamless and safe human-centered robotic applications for novel collaborative workplace”. Grant number: 820683 (https://www.sherlock-project.eu accessed on 12 March 2021). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/820683 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | autonomous industrial mobile manipulator | es_ES |
dc.subject | deep learning | es_ES |
dc.subject | robotics | es_ES |
dc.subject | perception | es_ES |
dc.subject | sensor fusion | es_ES |
dc.subject | autonomous navigation | es_ES |
dc.subject | computer vision | es_ES |
dc.subject | skills | es_ES |
dc.subject | state machine | es_ES |
dc.title | A Real Application of an Autonomous Industrial Mobile Manipulator within Industrial Context | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2021-06-10T13:46:33Z | |
dc.rights.holder | 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/2079-9292/10/11/1276/htm | es_ES |
dc.identifier.doi | 10.3390/electronics10111276 | |
dc.contributor.funder | European Commission | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala |
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Bestelakorik adierazi ezean, itemaren baimena horrela deskribatzen da:2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).