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I recently implemented some code to visualize a 3x3 (x-y-z) covariance matrix, which might be useful.

It decomposes the matrix into 3 principal vectors using PCA, and visualizes them (+/- 3 sigma width) using rviz markers. It's assumed that the matrix also has a 3x1 vector associated with it, which sets the mean x-y-z position.

The code is here, relevant function is at line 218:

feature_viewer.cpp

This is what it looks 3 covariance matrices look like in rviz:

image description

I recently implemented some code to visualize a 3x3 (x-y-z) covariance matrix, which might be useful.

It decomposes the matrix into 3 principal vectors using PCA, and visualizes them (+/- 3 sigma width) using rviz markers. It's assumed that the matrix also has a 3x1 vector associated with it, which sets the mean x-y-z position.

The code is here, relevant function is at line 218:

feature_viewer.cpp

This is what it looks 3 covariance matrices look like in rviz:

image description