NDLI: Triangulation-based indoor robot localization using extended FIR/Kalman filtering

Content Provider	IEEE Xplore Digital Library
Author	Granados-Cruz, M. Pomarico-Franquiz, J. Shmaliy, Y.S. Morales-Mendoza, L.J.
Copyright Year	2014
Description	Author affiliation: Dept. of Electron. Eng., Univ. de Guanajuato, Salamanca, Mexico (Granados-Cruz, M.; Pomarico-Franquiz, J.; Shmaliy, Y.S.) \|\| Dept. of Electron., Univ. Veracruzana, Poza Rica, Mexico (Morales-Mendoza, L.J.)
Abstract	A combined extended finite impulse response (EFIR) and Kalman (EFIR/Kalman) algorithm is proposed for mobile robot localization via triangulation. A distinctive advantage of the EFIR algorithm is that it completely ignores the noise statistics which are typically not well known to the engineer. Instead, it requires an optimal averaging interval of $N_{opt}$ points. To run this algorithm, several initial Kalman estimates are used for the roughly set noise covariances. We consider a mobile robot travelling on an indoor floorspace and localized via triangulation with three nodes in a view. We show that the EFIR/Kalman filter is more accurate than the extended Kalman filter under the uncertain noise statistics and initial state.
Starting Page	1
Ending Page	5
File Size	245592
Page Count	5
File Format	PDF
e-ISBN	9781479962303
DOI	10.1109/ICEEE.2014.6978256
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-29
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Finite impulse response filters Robot kinematics Noise Vectors Kalman filters Mobile robots
Content Type	Text
Resource Type	Article

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