I'm trying to implement an indirect kalman filter to estimate the pose of a differential drive robot using gyroscope and wheel encoder data.
I found a fiew papers (1 - 3) describing this approach but am confused about one thing. The state-matrix looks something like this:
Elements of this matrix change over time in a non-linear fashon which seems wrong to me:
- The state matrix should be static and changing values should be encapsuled in the controll input.
- Non-linear changes should only occur when using an EKF or UKF eventhough all papers only mention Kalman Filter
Are these two points just left out or simplified for conveniece since its obvious or am I missunderstanding something?
- Dead Reckoning Navigation for Autonomous Mobile Robots. IFAC Proceedings Volumes. 1. March 1998;31(3):219–24.
- Panich. Indirect Kalman Filter in Mobile Robot Application. Journal of Mathematics and Statistics. 1. August 2010;6(3):381–4.
- Zunaidi I, Kato N, Nomura Y, Matsui H. Positioning System for 4-Wheel Mobile Robot: Encoder, Gyro and Accelerometer Data Fusion with Error Model Method. 2006;