Calibrating the Kalman Filter Values

The Kalman Filter values from here work, but I think I can make it more responsive. The Lego motor has a optical sensor to track the rotation of the motor, so I have set up a simple program to compare the difference between the angle from the Kalman filter and the angle suggested by the optical sensor.

I really need to upgrade to the latest TI development board simply because it has a hardware quadrature decoder. I not 100% convinced that my software solution does not miss things. 

Kalman Filter

Kalman Filter

The Kalman filter is pretty straight forward filter that seeks to turn noisy measurements into not so noisy measurements. It does so by combining the observed measurement with a predicted measurement.

The blue line is the raw gyroscope measurement of the X axis. The red line is the Kalman filtered version.

This was just the sensor sitting on my bench, so the prediction model is trivial. That is the predicted gyroscope value is the previous gyroscope value.

Once the gyroscope is mounted on the robot the model will be based upon the model described in earlier post.

Stellaris and Gyroscopic Sensor

I've kind of settled on the Stellaris simply because of its 5 Volt tolerant pins.

A fair bit of effort was spent into integrating the gyroscopic sensor to the Stellaris. The problem ended up being the drive current from the micro controller was too low and was intermittently failing (i.e. the sensor was either not getting the command or getting the wrong one). On the Stellaris, you can set the drive current. The default was 2mA. 4mA seemed to work fine. So I am using 8mA to be sure to be sure.