Autonomous Motion

We are interested in understanding, how autonomous movement systems can bootstrap themselves into competent behavior by starting from a relatively simple set of algorithms and pre-structuring, and then learning from interacting with the environment. Using instructions from a teacher to get started can add useful prior information. Performing trial and error learning to improve movement skills and perceptual skills is another domain of our research. We are interested in investigating such perception-action-learning loops in biological systems and robotic systems, which can range in scale from nano systems (cells, nano-robots) to macro systems (humans, and humanoid robots).

Bernhard Schölkopf

Acting Director