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How do you calculate the likelihood of making an observation ?

Does someone have a link to a book or article that explains the math that you need to do to implement a PF algorithm? Conceptually i understand the implementation but I'm having a hard time updating the particles after a measurement update. Any resource that goes over the math in details/ with examples would really help.

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"Probabilistic Robotics" by Sebastian Thrun, Wolfram Burgard, Dieter Fox is the book you are looking for.

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  • $\begingroup$ Can someone explain to me why this was downvoted? I'm interested in improving my answer. $\endgroup$ Commented Mar 26, 2021 at 21:41
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    $\begingroup$ I didn't downvote it, but I'm here looking at the question and answers now and OP is asking a pretty direct question: "How do you calculate the likelihood of making an observation?" and you're giving them the title of a book. The book might contain the answer, but the title of a book is not the answer. $\endgroup$
    – Chuck
    Commented Mar 29, 2021 at 20:22
  • $\begingroup$ "Any resource that goes over the math in details/ with examples would really help". Probabilistic Robotics is such a resource. $\endgroup$
    – Ezward
    Commented Aug 23, 2022 at 1:02
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Here you can find a really interesting video explanation on particle filters.

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    $\begingroup$ Welcome to Robotics nionios. Thanks for your answer but we prefer answers to be self contained where possible. Links tend to rot so answers which rely on a link can be rendered useless if the linked content disappears. If you add more context from the link, it is more likely that people will find your answer useful. See How to Answer for more info. $\endgroup$
    – Chuck
    Commented Mar 29, 2021 at 20:23

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