Show simple item record

dc.contributor.authorKonečný, Jaromír
dc.contributor.authorKrömer, Pavel
dc.contributor.authorPrauzek, Michal
dc.contributor.authorMusilek, Petr
dc.date.accessioned2019-10-07T11:57:43Z
dc.date.available2019-10-07T11:57:43Z
dc.date.issued2019
dc.identifier.citationElectronics. 2019, vol. 8, issue 8, art. no. 856.cs
dc.identifier.issn2079-9292
dc.identifier.urihttp://hdl.handle.net/10084/138811
dc.description.abstractScan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesElectronicscs
dc.relation.urihttp://doi.org/10.3390/electronics8080856cs
dc.rights© 2019 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.subjectscan matchingcs
dc.subjectindoor localizationcs
dc.subjectdifferential evolutioncs
dc.subjectcross-correlationcs
dc.subjectroboticscs
dc.titleScan matching by cross-correlation and differential evolutioncs
dc.typearticlecs
dc.identifier.doi10.3390/electronics8080856
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume8cs
dc.description.issue8cs
dc.description.firstpageart. no. 856cs
dc.identifier.wos000483554300013


Files in this item

This item appears in the following Collection(s)

Show simple item record

© 2019 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 © 2019 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.