I cannot speak to their specific implementation.... but typically when one looks at classic tomography (eg. CT and MRI), there are tight tolerances or control o

I cannot speak to their specific implementation.... but typically when one looks at classic tomography (eg. CT and MRI), there are tight tolerances or control over the relative pose of the transmitter and receiver. This is required for the deterministic radon transform equations. For a robot system (especially a dual robot system), you could imagine a lot of pose uncertainty (especially angular). Eg. if using laser rangefinders and AMCL localization, you'd typically find ~10cm and ~5-deg of non-gaussian pose uncertainty indoors. I could imagine this causing complications. I'd be very curious to see some form of probabilistic extensions to tomography (not that they don't exist; I've just not researched the topic).