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Adapting this for single-measurement cases #2

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cherriesandwine opened this issue Feb 17, 2022 · 2 comments
Open

Adapting this for single-measurement cases #2

cherriesandwine opened this issue Feb 17, 2022 · 2 comments

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@cherriesandwine
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Hi, I am new to SLAM and interested in seeing how this performs when only one measurement is available, for example, bearing-only. I am finding it difficult to adapt the existing code for this case; I tried the following:

  • reducing H to a 2x1 matrix, with bearing only measurements
  • reducing .P to a single value
  • reducing R to single value

However, I am running into errors where the matrix Q becomes invertible.

@xiaolangWJ
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xiaolangWJ commented Feb 17, 2022 via email

@randvoorhies
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Hi @cherriesandwine unfortunately I haven't really thought about this code in the 10 years since I wrote it, so I'm not going to be a ton of help here. Want to post your code somewhere so others can take a look? I don't even have a copy of Matlab at this point, but perhaps Octave will work.

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