Riemannian Methods for Robot Learning (2400285)

The lecture provides an overview of the recent work Riemannian-geometry-based machine learning approaches with a particular focus on robotics applications. An introduction to Riemannian geometry will first be provided, including an overview of the Riemannian manifolds of interest for robotics and machine learning problems. Various methods and algorithms, their applications in robotics, and the current state of research will then be discussed.