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dc.contributor.authorDyrstad, Jonatan Sjølund
dc.contributor.authorBakken, Marianne
dc.contributor.authorGrøtli, Esten Ingar
dc.contributor.authorSchulerud, Helene
dc.contributor.authorMathiassen, John Reidar Bartle
dc.date.accessioned2019-04-02T11:51:03Z
dc.date.available2019-04-02T11:51:03Z
dc.date.created2019-01-25T12:51:11Z
dc.date.issued2018
dc.identifier.issn2197-3768
dc.identifier.urihttp://hdl.handle.net/11250/2592926
dc.description.abstractWe consider the case of robotic bin picking of reflective steel parts, using a structured light 3D camera as a depth imaging device. In this paper, we present a new method for bin picking, based on a dual-resolution convolutional neural network trained entirely in a simulated environment. The dualresolution network consists of a high resolution focus network to compute the grasp and a low resolution context network to avoid local collisions.The reflectivity of the steel parts result in depth images that have a lot of missing data. To take this into account, training of the neural net is done by domain randomization on a large set of synthetic depth images that simulate the missing data problems of the real depth images. We demonstrate both in simulation and in a real-world test that our method can perform bin picking of reflective steel partsnb_NO
dc.language.isoengnb_NO
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)nb_NO
dc.titleBin Picking of Reflective Steel Parts using a Dual-Resolution Convolutional Neural Network Trained in a Simulated Environmentnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalRobotics and Biomimeticsnb_NO
dc.identifier.doi10.1109/ROBIO.2018.8664766
dc.identifier.cristin1665104
dc.relation.projectNorges forskningsråd: 262900nb_NO
dc.description.localcode© 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.nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedfalse
cristin.fulltextpostprint
cristin.qualitycode1


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