Probabilistic sensor fusion

The objective of this course is to apply probabilistic sensor fusion methods to practical real life problems and datasets. The main focus is on implementing these methods as well as on understanding, evaluating and interpreting the estimation results and the workings of the algorithms. The course focuses on nonlinear filtering techniques (extended and unscented Kalman filtering, and particle filtering), Gaussian processes, as well as distributed versions of these algorithms.