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Our current implementation, based on the discussion in #15 is more consistent with using wheel odometry as an initial guess. However, many different implementations will work in this scenario; for example, @benemer proposes inferring from the map parameters as simple.
$\tau = 6 \cdot \frac{\text{voxel size}}{\sqrt{\text{max points in voxel}}}$
According to our evaluation, this gives identical results. This raises the question of how we can properly decide on a threshold value just based on data. Our main issue is a lack of proper data to test this, and we will need lots of data to make a final decision based on a bunch of different scenarios. @benemer and I want to come back to this, and anyone is welcome to this discussion in this issue or future PRs.
The text was updated successfully, but these errors were encountered:
Motivation
Our current implementation, based on the discussion in #15 is more consistent with using wheel odometry as an initial guess. However, many different implementations will work in this scenario; for example, @benemer proposes inferring from the map parameters as simple.
According to our evaluation, this gives identical results. This raises the question of how we can properly decide on a threshold value just based on data. Our main issue is a lack of proper data to test this, and we will need lots of data to make a final decision based on a bunch of different scenarios. @benemer and I want to come back to this, and anyone is welcome to this discussion in this issue or future PRs.
The text was updated successfully, but these errors were encountered: