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[wpimath] Use Odometry for internal state in Pose Estimation (#4668)

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This effectively replaces the Unscented Kalman Filter used for Pose Estimation with the Odometry model, and uses a recalculable Kalman gain matrix to update pose estimations whenever a vision measurement is added.

Notably, this change removes the need for the confusing generics used in Java, and the C++ implementation got quite a bit less complex as well.

Co-authored-by: Tyler Veness <calcmogul@gmail.com>
This commit is contained in:
Jordan McMichael
2022-12-02 11:36:10 -05:00
committed by GitHub
parent 68dba92630
commit e22d8cc343
35 changed files with 2288 additions and 1884 deletions
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styleguide/spotbugs-exclude.xml
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@@ -17,6 +17,10 @@
<Match>
<Bug pattern="DMI_RANDOM_USED_ONLY_ONCE" />
</Match>
<Match>
<Bug pattern="EC_BAD_ARRAY_COMPARE" />
<Class name="edu.wpi.first.math.estimator.SwerveDrivePoseEstimator$InterpolationRecord" />
</Match>
<Match>
<Bug pattern="EI_EXPOSE_REP" />
</Match>