72 citations · 322 across the 23 of their papers we have counts for
6 papers · 1 filter
Wireless Control for Smart Manufacturing: Recent Approaches and Open Challenges
Dominik Baumann, Fabian Mager, Ulf Wetzker +3
Smart manufacturing aims to overcome the limitations of today's rigid assembly lines by making the material flow and manufacturing process more flexible, versatile, and scalable. T…
Robot Learning with Crash Constraints
Alonso Marco, Dominik Baumann, Majid Khadiv +3
In the past decade, numerous machine learning algorithms have been shown to successfully learn optimal policies to control real robotic systems. However, it is common to encounter…
Learning Event-triggered Control from Data through Joint Optimization
Niklas Funk, Dominik Baumann, Vincent Berenz +1
We present a framework for model-free learning of event-triggered control strategies. Event-triggered methods aim to achieve high control performance while only closing the feedbac…
Identifying Causal Structure in Dynamical Systems
Dominik Baumann, Friedrich Solowjow, Karl H. Johansson +1
Mathematical models are fundamental building blocks in the design of dynamical control systems. As control systems are becoming increasingly complex and networked, approaches for o…
Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failures
Alonso Marco, Alexander von Rohr, Dominik Baumann +2
When learning to ride a bike, a child falls down a number of times before achieving the first success. As falling down usually has only mild consequences, it can be seen as a toler…
A Kernel Two-sample Test for Dynamical Systems
Friedrich Solowjow, Dominik Baumann, Christian Fiedler +3
Evaluating whether data streams are drawn from the same distribution is at the heart of various machine learning problems. This is particularly relevant for data generated by dynam…