Active Model Learning using Informative Trajectories for Improved Closed-Loop Control on Real Robots
Weixuan Zhang Marco Tognon Lionel Ott Roland Siegwart Juan Nieto Weixuan Zhang Marco Tognon Lionel Ott Roland Siegwart Juan Nieto
Model-based controllers on real robots require accurate knowledge of the system dynamics to perform optimally. For complex dynamics, first-principles modeling is not sufficiently precise, and data-driven approaches can be leveraged to learn a statistical model from real experiments. However, the efficient and effective data collection for such a data-driven system on real robots is still an open c...