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The robot pose ekf is meant to fuse continuous sources of odometry, where the assumption of Gaussian uncertainty is reasonable. The output of amcl does not fit this description: the output pose can arbitrary 'jump' to a new location when the localization module computes a new best guess for the robot pose. You should think through really well what you're actually trying to achieve when you merge all the sources you mention. Our approach has been to separate continuous odometry sources from discontinuous localization sources. You can read more about this in this REP.