Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/10832
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dc.contributor.authorCarlos Miguel Costaen
dc.contributor.authorLuís Freitas Rochaen
dc.contributor.authorMalaca,Pen
dc.contributor.authorPedro Gomes Costaen
dc.contributor.authorAntónio Paulo Moreiraen
dc.contributor.authorTavares,Pen
dc.contributor.authorArmando Sousaen
dc.contributor.authorGermano Veigaen
dc.contributor.other6164en
dc.contributor.other5152en
dc.contributor.other5157en
dc.contributor.other5159en
dc.contributor.other5364en
dc.contributor.other5674en
dc.date.accessioned2020-02-14T14:08:44Z-
dc.date.available2020-02-14T14:08:44Z-
dc.date.issued2019en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/10832-
dc.identifier.urihttp://dx.doi.org/10.1016/j.autcon.2019.04.020en
dc.description.abstractThe optimization of the information flow from the initial design and through the several production stages plays a critical role in ensuring product quality while also reducing the manufacturing costs. As such, in this article we present a cooperative welding cell for structural steel fabrication that is capable of leveraging the Building Information Modeling (BIM) standards to automatically orchestrate the necessary tasks to be allocated to a human operator and a welding robot moving on a linear track. We propose a spatial augmented reality system that projects alignment information into the environment for helping the operator tack weld the beam attachments that will be later on seam welded by the industrial robot. This way we ensure maximum flexibility during the beam assembly stage while also improving the overall productivity and product quality since the operator no longer needs to rely on error prone measurement procedures and he receives his tasks through an immersive interface, relieving him from the burden of analyzing complex manufacturing design specifications. Moreover, no expert robotics knowledge is required to operate our welding cell because all the necessary information is extracted from the Industry Foundation Classes (IFC), namely the CAD models and welding sections, allowing our 3D beam perception systems to correct placement errors or beam bending, which coupled with our motion planning and welding pose optimization system ensures that the robot performs its tasks without collisions and as efficiently as possible while maximizing the welding quality. © 2019 Elsevier B.V.en
dc.languageengen
dc.titleCollaborative Welding System using BIM for Robotic Reprogramming and Spatial Augmented Realityen
dc.typePublicationen
dc.typearticleen
Appears in Collections:CRIIS - Articles in International Journals

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