Pseudo-measured LPV Kalman filter for SLAM
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EditorInstitute of Electrical and Electronics Engineers
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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.
CitacióGuerra, E.; Bolea, Y.; Grau, A. Pseudo-measured LPV Kalman filter for SLAM. A: IEEE International Conference on Industrial Informatics. "INDIN 2012: IEEE 10th International Conference on Industrial Informatics: 25-27 July, 2012, Beijing, China". Beijing: Institute of Electrical and Electronics Engineers, 2012, p. 700-705.
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