{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T22:52:47Z","timestamp":1780354367438,"version":"3.54.1"},"reference-count":85,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper proposes a novel fuzzy-adaptive extended Kalman filter (FAEKF) for the real-time attitude estimation of agile mobile platforms equipped with magnetic, angular rate, and gravity (MARG) sensor arrays. The filter structure employs both a quaternion-based EKF and an adaptive extension, in which novel measurement methods are used to calculate the magnitudes of system vibrations, external accelerations, and magnetic distortions. These magnitudes, as external disturbances, are incorporated into a sophisticated fuzzy inference machine, which executes fuzzy IF-THEN rules-based adaption laws to consistently modify the noise covariance matrices of the filter, thereby providing accurate and robust attitude results. A six-degrees of freedom (6 DOF) test bench is designed for filter performance evaluation, which executes various dynamic behaviors and enables measurement of the true attitude angles (ground truth) along with the raw MARG sensor data. The tuning of filter parameters is performed with numerical optimization based on the collected measurements from the test environment. A comprehensive analysis highlights that the proposed adaptive strategy significantly improves the attitude estimation quality. Moreover, the filter structure successfully rejects the effects of both slow and fast external perturbations. The FAEKF can be applied to any mobile system in which attitude estimation is necessary for localization and external disturbances greatly influence the filter accuracy.<\/jats:p>","DOI":"10.3390\/s20030803","type":"journal-article","created":{"date-parts":[[2020,2,5]],"date-time":"2020-02-05T03:18:48Z","timestamp":1580872728000},"page":"803","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":75,"title":["A Novel Fuzzy-Adaptive Extended Kalman Filter for Real-Time Attitude Estimation of Mobile Robots"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9554-9586","authenticated-orcid":false,"given":"\u00c1kos","family":"Odry","sequence":"first","affiliation":[{"name":"Department of Control Engineering and Information Technology, University of Duna\u00fajv\u00e1ros, T\u00e1ncsics Mih\u00e1ly u. 1, 2400 Duna\u00fajv\u00e1ros, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Istvan","family":"Kecskes","sequence":"additional","affiliation":[{"name":"Department of Control Engineering and Information Technology, University of Duna\u00fajv\u00e1ros, T\u00e1ncsics Mih\u00e1ly u. 1, 2400 Duna\u00fajv\u00e1ros, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4050-8231","authenticated-orcid":false,"given":"Peter","family":"Sarcevic","sequence":"additional","affiliation":[{"name":"Technical Department, Faculty of Engineering, University of Szeged, Moszkvai krt. 9, 6725 Szeged, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zoltan","family":"Vizvari","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Faculty of Engineering and Information Technology, University of P\u00e9cs, Boszork\u00e1ny \u00fat 2, 7624 P\u00e9cs, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Attila","family":"Toth","sequence":"additional","affiliation":[{"name":"Institute of Physiology, Medical School, University of P\u00e9cs, Szigeti \u00fat 12, 7624 P\u00e9cs, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"P\u00e9ter","family":"Odry","sequence":"additional","affiliation":[{"name":"Department of Control Engineering and Information Technology, University of Duna\u00fajv\u00e1ros, T\u00e1ncsics Mih\u00e1ly u. 1, 2400 Duna\u00fajv\u00e1ros, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/j.ymssp.2018.03.053","article-title":"Kalman filter for mobile-robot attitude estimation: Novel optimized and adaptive solutions","volume":"110","author":"Odry","year":"2018","journal-title":"Mech. 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