Robot Learning focuses on the ability to learn complex skills through learning from demonstration, via self-improvement aka Reinforcement Learning, and most recently as well, via contrastive learning. Latest fundamental achievements in deep learning enabled researchers to utilize complex sensory data such as tactile receptor data, RGB video streams or depth camera measurements. In this talk, I will present our latest results in that direction with respect to tasks in robot grasping and manipulation, world model learning, representation learning and robot navigation in dynamic environments.