We have seen the grid localization, and the advantage of this approach is that we can deal with any kind of probability distribution; in particular we don't need to do a Gaussian assumption. The drawback is that the solution becomes very expensive. There exists another solution that is the Kalman filter, this is a completely different solution because it is a totally analytical solution.

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  • 2017-01-23T05:59:30Z
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  • 2015-06-01
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  • We have seen the grid localization, and the advantage of this approach is that we can deal with any kind of probability distribution; in particular we don't need to do a Gaussian assumption. The drawback is that the solution becomes very expensive. There exists another solution that is the Kalman filter, this is a completely different solution because it is a totally analytical solution. (fr)
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  • 2. Bayes and Kalman Filters (fr)
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  • 26405
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  • Droits réservés à l'éditeur et aux auteurs. This course material is provided under Creative Commons License BY-NC-ND: the name of the author should always be mentioned ; the user can exploit the work except in a commercial context and he cannot make changes to the original work. (fr)
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  • autonomous vehicles (fr)
  • informatics (fr)
  • mobile robots (fr)
  • robotics (fr)
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  • en
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  • 2.8. The Extended Kalman Filter (EKF) (fr)
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