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>
These classes are useful for storing previous robot positions to use in conjunction with the upcoming pose estimators.
Co-authored-by: Prateek Machiraju <prateek.machiraju@gmail.com>
Co-authored-by: Tyler Veness <calcmogul@gmail.com>
Co-authored-by: cttew <cttewari@gmail.com>
