{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,5]],"date-time":"2026-04-05T09:32:36Z","timestamp":1775381556669,"version":"3.50.1"},"reference-count":16,"publisher":"Cambridge University Press (CUP)","issue":"3","license":[{"start":{"date-parts":[[2009,5,1]],"date-time":"2009-05-01T00:00:00Z","timestamp":1241136000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2009,5]]},"abstract":"<jats:title>SUMMARY<\/jats:title><jats:p>The present paper proposes a successful application of differential evolution (DE) optimized fuzzy logic supervisors (FLS) to improve the quality of solutions that extended Kalman filters (EKFs) can offer to solve simultaneous localization and mapping (SLAM) problems for mobile robots and autonomous vehicles. The utility of the proposed system can be readily appreciated in those situations where an incorrect knowledge of <jats:bold>Q<\/jats:bold> and <jats:bold>R<\/jats:bold> matrices of EKF can significantly degrade the SLAM performance. A fuzzy supervisor has been implemented to adapt the <jats:bold>R<\/jats:bold> matrix of the EKF online, in order to improve its performance. The free parameters of the fuzzy supervisor are suitably optimized by employing the DE algorithm, a comparatively recent method, popularly employed now-a-days for high-dimensional parallel direct search problems. The utility of the proposed system is aptly demonstrated by solving the SLAM problem for a mobile robot with several landmarks and with wrong knowledge of sensor statistics. The system could successfully demonstrate enhanced performance in comparison with usual EKF-based solutions for identical environment situations.<\/jats:p>","DOI":"10.1017\/s0263574708004827","type":"journal-article","created":{"date-parts":[[2008,7,9]],"date-time":"2008-07-09T08:29:20Z","timestamp":1215592160000},"page":"411-423","source":"Crossref","is-referenced-by-count":26,"title":["Differential evolution tuned fuzzy supervisor adapted extended Kalman filtering for SLAM problems in mobile robots"],"prefix":"10.1017","volume":"27","author":[{"given":"Amitava","family":"Chatterjee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2009,5,1]]},"reference":[{"key":"S0263574708004827_ref11","doi-asserted-by":"publisher","DOI":"10.1109\/NAFIPS.1996.534789"},{"key":"S0263574708004827_ref1","doi-asserted-by":"publisher","DOI":"10.1109\/70.938381"},{"key":"S0263574708004827_ref13","unstructured":"13. Available online. http:\/\/www-personal.acfr.usyd.edu.au\/tbailey\/software\/slam_simulations.htm. Last accessed 24-June-2008."},{"key":"S0263574708004827_ref2","unstructured":"2. Montemerlo M. , Thrun S. , Koller D. and Wegbreit B. , \u201cFastSLAM 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges,\u201d Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI), Acapulco, Mexico (2003)."},{"key":"S0263574708004827_ref16","doi-asserted-by":"crossref","unstructured":"16. Shi Y. and Eberhart R. C. , \u201cEmpirical study of particle swarm optimization,\u201d Proceedings of the IEEE Congress on Evolutionary Computation (1999), pp. 1945\u20131950.","DOI":"10.1109\/CEC.1999.785511"},{"key":"S0263574708004827_ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2003.11.008"},{"key":"S0263574708004827_ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.1970.1099422"},{"key":"S0263574708004827_ref9","doi-asserted-by":"publisher","DOI":"10.1109\/41.679010"},{"key":"S0263574708004827_ref6","doi-asserted-by":"publisher","DOI":"10.1109\/70.938382"},{"key":"S0263574708004827_ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2002.1017615"},{"key":"S0263574708004827_ref4","unstructured":"4. Bailey T. , Mobile Robot Localization and Mapping in Extensive Outdoor Environments PhD Thesis (University of Sydney, 2002)."},{"key":"S0263574708004827_ref14","unstructured":"14. Available online. http:\/\/www.icsi.berkeley.edu\/~storn\/code.html. 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