Friday Feb 13th at 11.00 at IDSIA Prof. Dr. Jonas Buchli Agile and Dexterous Robotics Lab Institute of Robotics and Intelligent Systems ETH Zürich http://www.adrl.ethz.ch Unlocking the treasure trove: Learning impedance control Autonomous robots are about to step out of the labs and factory floors. Out there they have to deal with an uncertain, complex and dynamically changing world. Allowing robots to make sense and to behave robustly in such a world requires us to combine control theory with machine learning in a principled way. While impedance control, be that active, passive or a combination, is long recognized as a principled and powerful way to control robots, its use is in complex scenarios is still fairly limited. In this talk, I will sketch out the tremendous opportunities that active, variable impedance control offers when combined with model based and learning control. By understanding that this combination is key to versatile and robust robot performance, we will understand why active, variable impedance control has been a bit of a forgotten treasure to this date: its use requires solving a very hard nonlinear optimal control problem. This problem can successfully be addressed with learning and iterative optimal control methods.