Design and Implementation of Kalman Filters applied to Lego NXT based Robots

As it is well known, the Kalman filter (KF) provides an efficient computational tool to estimate the state of a process, minimizing the mean squared error. By allowing the estimation of past, present and future states, even dealing with some uncertainty in the process model, the KF presents a very good solution in state estimation. This work will deal with the design and the implementation of this powerful and important tool for the control engineering students in an easy to set-up laboratory environment. For that purpose the LEGO NTX robot is proposed. With this motivating tool the students can implement different estimators, like a velocity and acceleration observer of the robot wheels, or an observer of the position and orientation of the robot, and analyze different alternatives and solutions.