dc.contributor.author | Isachsen, Ulrich Johan | |
dc.contributor.author | Theoharis, Theoharis | |
dc.contributor.author | Misimi, Ekrem | |
dc.date.accessioned | 2021-01-18T11:58:55Z | |
dc.date.available | 2021-01-18T11:58:55Z | |
dc.date.created | 2020-09-09T11:09:36Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 0168-1699 | |
dc.identifier.uri | https://hdl.handle.net/11250/2723457 | |
dc.description.abstract | If 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.language.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Fast and accurate GPU accelerated, high resolution 3D registration for robotic 3D reconstruction of compliant Food objects | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.journal | Computers and Electronics in Agriculture | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.compag.2020.105929 | |
dc.identifier.cristin | 1828335 | |
dc.relation.project | Norges forskningsråd: 255596 | en_US |
dc.relation.project | Norges forskningsråd: 299757 | en_US |
dc.description.localcode | © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |