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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Except where otherwise noted, this item's license is described as 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/).