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dc.contributor.authorImani, Vandad
dc.contributor.authorHaataja, Keijo
dc.contributor.authorToivanen, Pekka
dc.contributor.editorVerikas, Antanas; Radeva, Petia; Nikolaev, Dmitry; Zhou, Jianhongen
dc.date.accessioned2019-02-21T13:27:38Z
dc.date.available2019-02-21T13:27:38Z
dc.date.issued2018
dc.identifier.urihttps://erepo.uef.fi/handle/123456789/7467
dc.description.abstractSimultaneous Localization and Mapping (SLAM) is oneof the most challenging research areas within computer and machine vision for automated scene commentary and explanation. The SLAM technique has been a developing research area in the robotics context during recent years. By utilizing the SLAM method robot can estimate the different positions of the robot at the distinct points of time which can indicate the trajectory of robot as well as generate a map of the environment. SLAM has unique traits which are estimating the location of robot and building a mapin the various types of environment. SLAM is effective in different types of environment such as indoor, outdoor district, Air, Underwater, Underground and Space. Several approaches have been investigated to use SLAM technique in distinct environments. The purpose of this paper is to provide an accurate perceptive review of case history of SLAM relied on laser/ultrasonic sensors and camera as perception input data. In addition, we mainly focus on three paradigms of SLAM problem with all its pros and cons. In the future, use intelligent methods and some new idea will be used on visual SLAM to estimate the motion intelligent underwater robot and building a feature map of marine environment.en
dc.language.isoenglantien
dc.publisherSPIEen
dc.relation.ispartofProceedings of SPIE: Tenth International Conference on Machine Vision (ICMV 2017)en
dc.relation.ispartofseriesProceedings of SPIE : the International Society for Optical Engineeringen
dc.relation.urihttps://doi.org/10.1117/12.2310094en
dc.rightsAll rights reserveden
dc.subjectsimultaneous localization and mappingen
dc.subjectlocalizationen
dc.subjectmappingen
dc.subjectEKFen
dc.subjectparticle filteren
dc.subjectgraph-based SLAMen
dc.titleThree main paradigms of simultaneous localization and mapping (SLAM) problemen
dc.description.versionpublished versionen
dc.contributor.departmentTietojenkäsittelytieteen laitos / Tietojenkäsittelytieteen laitoksen toimintaen
uef.solecris.id54570762en
dc.type.publicationconferenceObjecten
dc.rights.accessrights© SPIEen
dc.relation.doi10.1117/12.2310094en
dc.description.reviewstatuspeerRevieweden
dc.relation.articlenumber106961Pen
dc.relation.isbn9781510619418en
dc.relation.issn0277-786Xen
dc.rights.accesslevelopenAccessen
dc.type.okmA4en
dc.type.versioninfo:eu-repo/semantics/publishedVersionen


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