Kalman Filter MOOC
(see KalMOOC)
Localization with Kalman Filter
The robots can measure angles (with a goniometer) from landmarks or from the other robot if the distance is small. Using these measurements, each robot can estimate its position and we show how their covariance evolve.
Tracking with Extended Kalman Filter
A robot is localized and tracked from two noisy radars using an EKF.
Regulation and state observation with Extended Kalman Filter
An inverse pendulum is regularized using an EKF for state observation.
Simultaneous Localization and Mapping (SLAM) with KF for Underwater Robot
A Kalman filter is used to predict the robot position and correct it by detecting seamarks. At the end a backward pass, is used to further refine the seamarks and the robot positions.
