YBachmann
commented
3 months ago Hello @clalancette ,
could you please take a look at this PR?
I attached a small video showing a comparison of the current state of using the minimum value in each column (orange) and my proposed approach of using quantiles/percentiles (purple). In this test a scan_height of 180 pixels was used and for my version a quantile_value of 0.35.
In my opinion using a quantile instead of the minimum of a row greatly reduces noise and more accurately reflects the position of obstacles/walls.
It is also easily adjustable. If you have very little noise or want to detect small objects that might only take up a couple pixels in each row, you can set the quantile_value parameter to a small numer (or even to 0.0 to retain the current behavior). If you want smooth and accurate laserscans and only care about larger objects you can set the value to something bigger.
depthimage_to_laserscan_quantile_comparison.webm
Currently the minimum value of each column in the depthimage was used to calculate the distance values.
When dealing with noisy data it is benefitial to use e.g. the 10% quantile instead of the minimum value. This way we still get accurate data but ignore noise/outliers.
The parameter
quantile_valuecontrols which quantile should be used.0.0will have the effect of using the minimum value of each column (the current behavior and default value).0.5will use the median of each column.quantile_valueof around0.1. This way a lot of noise/outliers was removed, but the laserscan data still contained obstacles, even if they only covered a small part (>10%) of thescan_height.