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dc.contributor.authorHeczko, Dominik
dc.contributor.authorOščádal, Petr
dc.contributor.authorKot, Tomáš
dc.contributor.authorBoleslavský, Adam
dc.contributor.authorKrys, Václav
dc.contributor.authorBém, Jan
dc.contributor.authorVirgala, Ivan
dc.contributor.authorBobovský, Zdenko
dc.date.accessioned2022-06-20T07:35:30Z
dc.date.available2022-06-20T07:35:30Z
dc.date.issued2022
dc.identifier.citationSensors. 2022, vol. 22, issue 4, art. no. 1536.cs
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10084/146290
dc.description.abstractIn this paper, we examine a method for improving pose estimation by correctly positioning the sensors relative to the scanned object. Three objects made of different materials and using different manufacturing technologies were selected for the experiment. To collect input data for orientation estimation, a simulation environment was created where each object was scanned at different poses. A simulation model of the laser line triangulation sensor was created for scanning, and the optical surface properties of the scanned objects were set to simulate real scanning conditions. The simulation was verified on a real system using the UR10e robot to rotate and move the object. The presented results show that the simulation matches the real measurements and that the appropriate placement of the sensors has improved the orientation estimation.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesSensorscs
dc.relation.urihttps://doi.org/10.3390/s22041536cs
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectorientation estimationcs
dc.subjectlaser scanningcs
dc.subjectLLT sensorcs
dc.subjectvirtual scanningcs
dc.subjectoptimal configurationcs
dc.subjectoptimal posecs
dc.subjectICP algorithmcs
dc.subjectpose estimationcs
dc.titleFinding the optimal pose of 2D LLT sensors to improve object pose estimationcs
dc.typearticlecs
dc.identifier.doi10.3390/s22041536
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume22cs
dc.description.issue4cs
dc.description.firstpageart. no. 1536cs
dc.identifier.wos000775436200001


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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Except where otherwise noted, this item's license is described as © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.