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dc.contributor.authorTammaro, Antonioen_US
dc.contributor.authorSegura, Álvaroen_US
dc.contributor.authorMoreno, Aitoren_US
dc.contributor.authorSánchez, Jairo R.en_US
dc.contributor.editorFco. Javier Melero and Nuria Pelechanoen_US
dc.date.accessioned2017-06-26T16:32:47Z
dc.date.available2017-06-26T16:32:47Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-046-8
dc.identifier.issn-
dc.identifier.urihttp://dx.doi.org/10.2312/ceig.20171204
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/ceig20171204
dc.description.abstractIn the last year, the concept of Industry 4.0 and smart factories has increasingly gained more importance. One of the central aspects of this innovation is the coupling of physical systems with a corresponding virtual representation, known as the Digital Twin. This technology enables new powerful applications, such as real-time production optimization or advanced cloud services. To ensure the real-virtual equivalence it is necessary to implement multimodal data acquisition frameworks for each production system using their sensing capabilities, as well as appropriate communication and control architectures. In this paper we extend the concept of the digital twin of a production system adding a virtual representation of its operational environment. In this way the paper describes a proof of concept using an industrial robot, where the objects inside its working volume are captured by an optical tracking system. Detected objects are added to the digital twin model of the cell along with the robot, having in this way a synchronized virtual representation of the complete system that is updated in real time. The paper describes this tracking system as well as the integration of the digital twin in a Web3D based virtual environment that can be accessed from any compatible devices such as PCs, tablets and smartphones.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subject> Virtual reality
dc.subjectApplied computing
dc.subject> Industry and manufacturing
dc.titleExtending Industrial Digital Twins with Optical Object Trackingen_US
dc.description.seriesinformationSpanish Computer Graphics Conference (CEIG)
dc.description.sectionheadersObject Recognition
dc.identifier.doi10.2312/ceig.20171204
dc.identifier.pages23-26


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  • CEIG17
    ISBN 978-3-03868-046-8

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