I'm working on a differential drive rover which I would like to use to follow a path. In order to do this, I plan on using Wheel encoders and a 3DoF IMU. Is there a good way to combine the odometry and IMU measurements to create a more robust estimation of position and orientation?
I plan on modeling my state estimation off of this document.
However, he is getting his orientation solely from his IMU and his distance solely from his encoders. Is there a good way to combine the two? I.E. Could I use the acceleration values from my IMU and my encoder measurements to get a more robust estimation of position? How about using my relative wheel speeds and a gyroscope/compass to get a better estimation of orientation? I understand that Kalman and complimentary filters are typically used to combine noisy measurements. However, I have been unable to find an example using a Kalman filter combining IMU and encoder measurements.