While classical industrial robots are mostly designed for repetitive tasks, assistive robots will be challenged by a variety of different tasks in close contact with humans. Hereby, learning through the direct interaction with humans provides a potentially powerful tool for an assistive robot to acquire new skills and to incorporate prior human knowledge during the exploration of novel tasks. Moreover, an intuitive interactive teaching process may allow non-programming experts to contribute to robotic skill learning and may help to increase acceptance of robotic systems in shared workspaces and everyday life.
In this talk, Dorothea Koert will discuss recent research she did on interactive robot skill learning and the remaining challenges on the route to human-centered teaching of assistive robots. The presented work covers learning a library of probabilistic movement primitives from human demonstrations, intention aware adaptation of learned skills in shared workspaces, and multi-channel interactive reinforcement learning for sequential tasks.
Speaker bio: Dorothea Koert is the head of the interdisciplinary junior research group IKIDA which started in October 2020 and a postdoctoral researcher at the Intelligent Autonomous Systems Lab and the University of Darmstadt in Germany.