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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578539
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dc.contributor.authorHamzah Ahmad (UMP)
dc.contributor.authorNur Aqilah Othman (UMP)
dc.date.accessioned2023-11-06T03:03:19Z-
dc.date.available2023-11-06T03:03:19Z-
dc.date.issued2017-06
dc.identifier.issn0128-7680
dc.identifier.otherukmvital:116005
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578539-
dc.descriptionThis paper deals with the analysis of different Fuzzy membership type performance for Extended Kalman Filter (EKF) based mobile robot navigation. EKF is known to be incompetent in non-Gaussian noise condition and therefore the technique alone is not sufficient to provide solution. Motivated by this shortcoming, a Fuzzy based EKF is proposed in this paper. Three membership types are considered which includes the triangular, trapezoidal and Gaussian membership types to determine the best estimation results for mobile robot and landmarks locations. Minimal rule design and configuration are also other aspects being considered for analysis purposes. The simulation results suggest that the Gaussian memberships surpassed other membership type in providing the best solution in mobile robot navigation.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journals
dc.relation.urihttp://www.pertanika.upm.edu.my/regular_issues.php?jtype=2&journal=JST-25-S-6
dc.rightsUKM
dc.subjectFuzzy logic
dc.subjectKalman Filter
dc.subjectMembership
dc.subjectMobile robot
dc.subjectNavigation
dc.titleFuzzy logic based ekf for mobile robot navigation: an analysis of different fuzzy membership functions
dc.typeJournal Article
dc.format.volume25
dc.format.pages189-198
dc.format.issueSpecial Issue
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