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dc.contributor.authorKonečný, Jaromír
dc.contributor.authorPrauzek, Michal
dc.contributor.authorKrömer, Pavel
dc.contributor.authorMusilek, Petr
dc.date.accessioned2016-06-15T07:31:54Z
dc.date.available2016-06-15T07:31:54Z
dc.date.issued2016
dc.identifier.citationMobile Information Systems. 2016, art. ID 6463945.cs
dc.identifier.issn1574-017X
dc.identifier.issn1875-905X
dc.identifier.urihttp://hdl.handle.net/10084/111648
dc.description.abstractThe localization of mobile robots in outdoor and indoor environments is a complex issue. Many sophisticated approaches, based on various types of sensory inputs and different computational concepts, are used to accomplish this task. However, many of the most efficient methods for mobile robot localization suffer from high computational costs and/or the need for high resolution sensory inputs. Scan cross-correlation is a traditional approach that can be, in special cases, used to match temporally aligned scans of robot environment. This work proposes a set of novel modifications to the cross-correlation method that extend its capability beyond these special cases to general scan matching and mitigate its computational costs so that it is usable in practical settings. The properties and validity of the proposed approach are in this study illustrated on a number of computational experiments.cs
dc.format.extent2065462 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoencs
dc.publisherHindawics
dc.relation.ispartofseriesMobile Information Systemscs
dc.relation.urihttp://dx.doi.org/10.1155/2016/6463945cs
dc.rightsCopyright © 2016 Jaromir Konecny et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.cs
dc.titleNovel point-to-point scan matching algorithm based on cross-correlationcs
dc.typearticlecs
dc.identifier.doi10.1155/2016/6463945
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.firstpageart. ID 6463945cs
dc.identifier.wos000375587500001


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