Eventually we want to get to a point where we can remove OpenCV from the internals of cscore. The start to doing that is converting the existing CvSource and CvSink methods to RawFrame.
For CvSource, this is 100% a free operation. We can do everything the existing code could have done (with one small exception we can fairly easily fix).
For CvSink, by defaut this change would incur one extra copy, but no extra allocations. A set of direct methods were added to CvSink to add a method to avoid this extra copy.
Java was missing the motor safety thread entirely
C++ accidentally used a manual reset event, causing the motor safety thread to spin.
C++ PWMMotorController would not feed the watch kitty.
Both languages would call feed() from the StopMotor call, causing some ping ponging.
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 also makes the Gradle build work with JDK 17.
The extra JVM args in gradle.properties works around a bug with spotless
and JDK 17: https://github.com/diffplug/spotless/issues/834
PMD.CloseResource was ignored because it's almost always a false
positive, and there are many of them.
UpdateEntries() and Flush() are called from methods that lock the mutex,
so locking it again will cause deadlocks. This also updates the Java
code to make MechanismObject2d::update synchronized like in the C++
version.
