dc.contributor.author | Stensrud, Mathias | |
dc.contributor.author | Haakstad, Ole Henrik | |
dc.contributor.author | Sakseid, Olav | |
dc.contributor.author | Westby, Baard | |
dc.contributor.author | Alcocer, Alex | |
dc.date.accessioned | 2019-01-31T13:15:09Z | |
dc.date.accessioned | 2019-08-09T07:32:20Z | |
dc.date.available | 2019-01-31T13:15:09Z | |
dc.date.available | 2019-08-09T07:32:20Z | |
dc.date.issued | 2018-12-13 | |
dc.identifier.citation | Stensrud M, Haakstad, Sakseid O, Westby, Alcocer AA. Towards Automated 3D reconstruction in SME factories and Digital Twin Model generation. International Conference on Control, Automation and Systems. 2018 | en |
dc.identifier.isbn | 978-89-93215-16-8 | |
dc.identifier.issn | 2093-7121 | |
dc.identifier.uri | https://hdl.handle.net/10642/7432 | |
dc.description.abstract | This paper presents preliminary results towards the development of digital twin models for Small to Medium Enterprise (SME) factories in a partially automated and cost-effective manner. In many cases it is desirable to obtain a 3D model of a factory floor and machinery, that can be used for visualization of Digital Twin models. Current commercial 3D reconstruction solutions involve the use of high-end LiDAR sensors which increase the cost of the 3D scanning process and suppose a barrier for SME factories on their path towards Industry 4.0. The paper presents a comparison of 3D reconstruction results using low-cost sensors including a Zenfone AR mobile phone, an Intel RealSense ZR300 and a Kinect v2. The small size and weight of the sensors make it possible to be mounted on small unmanned aerial vehicles and enable future 3D reconstruction in an autonomous manner. The data was processed using an open source Simultaneous Localization and Mapping (SLAM) library RTAB-Map. The results were compared with a professional 3D scan using a GeoSLAM LiDAR. Experimental results from a scanning of a university research lab with a small simulated production line and two UR3 industrial manipulators is presented. The obtained 3D model was used to generate a simple Digital Twin model that can be visualized using a VR headset. | en |
dc.description.sponsorship | The research was supported by Norwegian Research Council through project DigiFab, and OsloMet lighthouse project Autonomic Systems. | en |
dc.language.iso | en | en |
dc.publisher | IEEE | en |
dc.relation.ispartofseries | 2018 18th International Conference on Control, Automation and Systems (ICCAS); | |
dc.rights | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en |
dc.subject | Digital twins | en |
dc.subject | Autonomous systems | en |
dc.subject | Industry 4.0 | en |
dc.subject | 3D reconstruction | en |
dc.subject | Unmanned aerial vehicles | en |
dc.subject | Simultaneous localizations | |
dc.subject | Mapping | |
dc.subject | Unmanned aerial vehicles | |
dc.subject | RGB-D cameras | |
dc.title | Towards Automated 3D reconstruction in SME factories and Digital Twin Model generation | en |
dc.type | Journal article | en |
dc.type | Peer reviewed | en |
dc.date.updated | 2019-01-31T13:15:09Z | |
dc.description.version | acceptedVersion | en |
dc.identifier.doi | https://ieeexplore.ieee.org/document/8571914 | |
dc.identifier.cristin | 1670593 | |
dc.identifier.cristin | 1670593 | |
dc.identifier.cristin | 1670593 | |
dc.identifier.cristin | 1670593 | |
dc.source.journal | International Conference on Control, Automation and Systems | |