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dc.contributor.authorIsachsen, Ulrich Johan
dc.contributor.authorTheoharis, Theoharis
dc.contributor.authorMisimi, Ekrem
dc.description.abstractIf we are to develop robust robot-based automation in primary production and processing in the agriculture and ocean space sectors, we have to develop solid vision-based perception for the robots. Accurate vision-based perception requires fast 3D reconstruction of the object in order to extract the geometrical features necessary for robotic manipulation. To this end, we present an accurate, real-time and high-resolution ICP-based 3D registration algorithm for eye-in-hand configuration using an RBG-D camera. Our 3D reconstruction, via an efficient GPU implementation, is up to 33 times faster than a similar CPU implementation, and up to eight times faster than a similar library implementation, resulting in point clouds of 1 mm resolution. The comparison of our 3D reconstruction with other ICP-based baselines, through trajectories from 3D registration and reference trajectories for an eye-in-hand configuration, shows that the point-to-plane linear least squares optimizer gives the best results, both in terms of precision and performance. Our method is validated for the eye-in-hand robotic scanning and 3D reconstruction of some representative examples of food items and produce of agricultural and marine origin.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleFast and accurate GPU accelerated, high resolution 3D registration for robotic 3D reconstruction of compliant Food objectsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalComputers and Electronics in Agricultureen_US
dc.relation.projectNorges forskningsråd: 255596en_US
dc.relation.projectNorges forskningsråd: 299757en_US
dc.description.localcode© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal