Título:
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Pseudo-measured LPV Kalman filter for SLAM
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Autor/a:
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Guerra Paradas, Edmundo; Bolea Monte, Yolanda; Grau Saldes, Antoni
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Otros autores:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents |
Abstract:
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This paper describes a new approach to the wellknown
robotics problem of simultaneous location and mapping
(SLAM). The proposed technique introduces a linear varying
parameter (LPV) modeling solution for the estimation of
nonlinear models in a Kalman Filter based algorithm. In this
technique, the estimation model for the robotic device considered
is modeled as a quasi-LPV model, which in turn, is linearized
around a set of given points of the varying parameter. The
observation model is rearranged into a pseudo-measurement
model, which is used in form of a pseudo-linear model during the
update stage of the Kalman filter. The initial tests and
experimentations suggest that this technique can improve
Extended Kalman Filter SLAM results by avoiding a great deal
of the bias introduced by linearization of nonlinear models into
EKF equations. |
Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Automàtica i control -Kalman filtering -Filtres de Kalman |
Derechos:
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Tipo de documento:
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Artículo - Versión publicada Objeto de conferencia |
Editor:
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Institute of Electrical and Electronics Engineers
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