NDLI: Pseudo-measured LPV Kalman filter for SLAM

Content Provider	IEEE Xplore Digital Library
Author	Guerra, E. Bolea, Y. Grau, A.
Copyright Year	2012
Description	Author affiliation: Automatic Control Dept, Technical University of Catalonia, UPC, Barcelona, Spain (Guerra, E.; Bolea, Y.; Grau, A.)
Abstract	This paper describes a new approach to the well-known 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.
Starting Page	700
Ending Page	705
File Size	310839
Page Count	6
File Format	PDF
ISBN	9781467303125
e-ISBN	9781467303118
DOI	10.1109/INDIN.2012.6301358
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	pseudolinear modelling Simultaneous localization and mapping SLAM Kalman Filter LPV Robot kinematics linear varying parameter Estimation Mathematical model Kalman filters
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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