Quote:
Originally Posted by Matt H.
This is false. Simplified models of your system can be used in effective Kalman filters provided you add uncertainty from the model.
See this paper which is an overview of the Kalman filter (esp. the section on Filter Parameters and Tuning and the Extended Kalman filter):
http://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf
That being said, I agree that Kalman filters are generally overkill for FRC. |
My point was that even with the extended Kalman filter, you have to have significantly more equations to get an acceptable answer compared to an effectively tuned PID. Kalman filters for simple sensing (encoders + gyro) are ineffective compared to PID due to their overly complicated sets of equations.
When using multiple IMUs and sensing devices, Kalman is the ONLY way to go, but for us I still say ineffective.