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Abstract: Localization is one of the fundamental problems in mobile robot navigation. Recent experiments showed that in general grid-based Markov localization is more robust than Kalman filtering while the latter can be more accurate than the former. In this paper we present a novel approach called Markov-Kalman localization (ML-EKF) which is a combination of both methods. ML-EKF is well suited for robots observing known landmarks, having a rough estimate of their movements, and which might be displaced... (Update)
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6: An experimental comparison of localization methods - Gutmann, Burgard et al. - 1998
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BibTeX entry: (Update)
J.-S. Gutmann. Markov-Kalman localization for mobile robots. In Int. Conf. on Pattern Recognition (ICPR), 2002. http://citeseer.ist.psu.edu/gutmann02markovkalman.html More
@misc{ gutmann02markovkalman,
author = "J. Gutmann",
title = "Markov-Kalman localization for mobile robots",
text = "J.-S. Gutmann. Markov-Kalman localization for mobile robots. In Int. Conf.
on Pattern Recognition (ICPR), 2002.",
year = "2002",
url = "citeseer.ist.psu.edu/gutmann02markovkalman.html" }
Citations (may not include all citations):169 Tracking and Data Association (context) - Bar-Shalom, Fortmann - 1988
126 Mobile robot localization by tracking geometric beacons (context) - Leonard, Durrant-Whyte - 1991
102 Markov localization for mobile robots in dynamic environment.. - Fox, Burgard et al. - 1999
91 An experimental comparison of localization methods - Gutmann, Burgard et al. - 1998
88 Robust Monte Carlo localization for mobile robots - Thrun, Fox et al. - 2000
62 Fast and inexpensive color image segmentation for interactiv.. - Bruce, Balch et al. - 2000
47 The Kalman filter: An introduction to concepts (context) - Maybeck - 1990
12 Probabilistic self-localization for mobile robots - Olson - 2000
9 Sensor resetting localization for poorly modeled mobile robo.. (context) - Lenser, Veloso - 2000
3 The UNSW RoboCup (context) - Hengst, Ibbotson et al. - 2000
The graph only includes citing articles where the year of publication is known.
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