The Comparison of Estimation Algorithms for Mobile Robot Navigation

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dc.contributor.authorGuney, Selda
dc.contributor.authorBilen, Murat
dc.contributor.orcID0000-0002-0573-1326en_US
dc.contributor.researcherIDAAC-7404-2020en_US
dc.date.accessioned2023-06-19T08:57:28Z
dc.date.available2023-06-19T08:57:28Z
dc.date.issued2016
dc.description.abstractIn this study, a robot with different maneuvras is followed with different estimation algorithms. The mobile robot has acted first linear, then maneuver and finally linear again. It's speed is constant through the way. Standard Kalman Filter, Adaptive Kalman Filter, Extended Kalman Filter and Interacting Multiple Model consist of multiple model Kalman Filter combined of linear and non-linear model are used to follow the act of the robot. The results of these estimations are compared with each other. Multiple model Kalman Filter is the best estimation algorithm among them for this motion model.en_US
dc.identifier.endpage800en_US
dc.identifier.isbn978-1-5090-1679-2en_US
dc.identifier.scopus2-s2.0-84982798972en_US
dc.identifier.startpage797en_US
dc.identifier.urihttp://hdl.handle.net/11727/9680
dc.identifier.wos000391250900177en_US
dc.language.isoturen_US
dc.relation.isversionof10.1109/SIU.2016.7495860en_US
dc.relation.journal24th Signal Processing and Communication Application Conference (SIU)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectmobile robot navigationen_US
dc.subjectKalman filteren_US
dc.subjectextended Kalman filteren_US
dc.subjectmultiple model Kalman filteren_US
dc.titleThe Comparison of Estimation Algorithms for Mobile Robot Navigationen_US
dc.typeConference Objecten_US

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