Pose and state estimators can filter latency-compensated global measurements and fuse them with state-space drivetrain model information to estimate robot position. They are drop-in replacements for the existing odometry classes.
Co-authored-by: Declan Freeman-Gleason <declanfreemangleason@gmail.com>
Co-authored-by: Prateek Machiraju <prateek.machiraju@gmail.com>
Co-authored-by: Claudius Tewari <cttewari@gmail.com>
Co-authored-by: Matt <matthew.morley.ca@gmail.com>
This helps reduce compilation overhead. I tried slimming down includes
of <Eigen/QR>, but the householderQr() function we use from there
requires including dependency headers from Eigen that don't fit with
lexographic ordering. It didn't seem worth the effort to work around.
This won't affect user code at all since all the Eigen feature usage
here is internal only; users generally only need <Eigen/Core>.
