The existing implementation will produce a cost of NaN if a tolerance of
infinity is entered, but the limit approaches zero. Being able to
specify that a state has no cost is useful, so this change adds support for
that.
The template argument order for UnscentedTransform was reversed to match
all the other UKF classes. Since UnscentedTransform is intended as a
class for internal use only, this shouldn't cause much breakage.
* Replace Matrix<> with Vector<> where vectors are explicitly intended.
I found these via `rg "Eigen::Matrix<double, \w+, 1>"`.
* Pass all Eigen matrices by const reference. I found these via `rg
"\(Eigen"` on main (the initializer list constructors make more false
positives).
* Replace MakeMatrix() and operator<< usage with initializer list
constructors. I found these via `rg MakeMatrix` and `rg "<<"`
respectively.
* Deprecate MakeMatrix()
Internal headers are no longer allowed as of
https://gitlab.com/libeigen/eigen/-/merge_requests/631. Based on
benchmarking I conducted in that thread, there doesn't seem to be a
performance penalty for including the full headers anymore.
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>.
