Comparison of the SLAM algorithms: Hangar experiments

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dc.contributor.authorKorkmaz, Mehmet
dc.contributor.authorYilmaz, Nihat
dc.contributor.authorDurdu, Akif
dc.date.accessioned2020-03-26T19:23:25Z
dc.date.available2020-03-26T19:23:25Z
dc.date.issued2016
dc.departmentSelçuk Üniversitesien_US
dc.description3rd International Conference on Control, Mechatronics and Automation (ICCMA) -- DEC 21-22, 2015 -- Barcelona, SPAINen_US
dc.description.abstractThis study purposes to compare two known algorithms in an application scenario of simultaneous localization and mapping (SLAM) and to present issues related with them as well. Mostly used SLAM algorithms Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared with respect to the point of accuracy of the robot states, localization and mapping. Because of considering the most implementations in the previous studies, the simulation environments are chosen as big as possible to provide reliable results. In this study, two different hangar regions are tried to be simulated. According to the outcomes of the applications, UKF-based SLAM algorithm has superior performance over the EKF-based one, apart from elapsed time.en_US
dc.identifier.doi10.1051/matecconf/20164203009en_US
dc.identifier.issn2261-236Xen_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://dx.doi.org/10.1051/matecconf/20164203009
dc.identifier.urihttps://hdl.handle.net/20.500.12395/33388
dc.identifier.volume42en_US
dc.identifier.wosWOS:000372745100025en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherE D P SCIENCESen_US
dc.relation.ispartof2015 3RD INTERNATIONAL CONFERENCE ON CONTROL, MECHATRONICS AND AUTOMATION (ICCMA 2015)en_US
dc.relation.ispartofseriesMATEC Web of Conferences
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleComparison of the SLAM algorithms: Hangar experimentsen_US
dc.typeConference Objecten_US

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