Hi,

I figured I'd ask and see if there was interest in something like this. In order to help remove salt and pepper noise from images, typically you might use dilation and erosion. The same concept could apply to navigation2 costmap layers, where an erroneous voxel layer or obstacle layer measurement (or static layer with SLAM session and things moving around) would make in the middle of free space incorrectly.

The idea would be to then offer some convolution or topological costmap layer to remove this noise. Is this something folks think is useful and would use?

To get rid of noise, erode then dilate https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_morphological_ops/py_morphological_ops.html