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Video data validation by sonar measures for robot localization and environment feature estimation

Published online by Cambridge University Press:  29 August 2008

A. Bonci
Affiliation:
Dipartimento di Ingegneria Informatica, Gestionale e dell'Automazione, Università Politecnica delle Marche Via Brecce Bianche, 60131 Ancona, Italy.
G. Ippoliti
Affiliation:
Dipartimento di Ingegneria Informatica, Gestionale e dell'Automazione, Università Politecnica delle Marche Via Brecce Bianche, 60131 Ancona, Italy.
A. La Manna
Affiliation:
Dipartimento di Ingegneria Informatica, Gestionale e dell'Automazione, Università Politecnica delle Marche Via Brecce Bianche, 60131 Ancona, Italy.
S. Longhi*
Affiliation:
Dipartimento di Ingegneria Informatica, Gestionale e dell'Automazione, Università Politecnica delle Marche Via Brecce Bianche, 60131 Ancona, Italy.
*
*Corresponding author. E-mail: sauro.longhi@univpm.it
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In this paper, the robust robot localization problem with respect to uncertainties on environment features is formulated in a stochastic setting, and an extended Kalman filtering approach is proposed for the integration of odometric, video camera, and sonar measures. The environment is supposed to be only partially known, and a probabilistic method for sensor data fusion aimed at increasing the environment knowledge is considered.

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Article
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Copyright © Cambridge University Press 2008