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Unscented Transformation of Vehicle States

  • Juan Andrade-Cetto
  • Alberto Sanfeliu
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 23)

Abstract

We have already seen that the Extended Kalman Filter (EKF) is the most widely accepted tool for solving SLAM [31, 85]. One drawback however with the use of the EKF, is in the linear propagation of means and covariances. Vehicle and sensor models are usually of a very high nonlinear nature, and the effects of linearization required in the EKF can lead to filter divergence [53].

Keywords

Kalman Filter Extend Kalman Filter Unscented Kalman Filter Vehicle State Sigma Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Authors and Affiliations

  • Juan Andrade-Cetto
    • 1
  • Alberto Sanfeliu
    • 1
  1. 1.Institut de Robòtica i Informàtica Industrial Universitat Politècnica de Catalunya – Consejo Superior de Investigaciones Científicas Llorens Artigas 4–6 08028 BarcelonaSpain

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