230 citations · 298 across the 35 of their papers we have counts for
8 papers · 1 filter
Learning Fast and Precise Pixel-to-Torque Control
Steffen Bleher, Steve Heim, Sebastian Trimpe
In the field, robots often need to operate in unknown and unstructured environments, where accurate sensing and state estimation (SE) becomes a major challenge. Cameras have been u…
Event-Triggered Time-Varying Bayesian Optimization
Paul Brunzema, Alexander von Rohr, Friedrich Solowjow +1
We consider the problem of sequentially optimizing a time-varying objective function using time-varying Bayesian optimization (TVBO). Current approaches to TVBO require prior knowl…
On Controller Tuning with Time-Varying Bayesian Optimization
Paul Brunzema, Alexander von Rohr, Sebastian Trimpe
Changing conditions or environments can cause system dynamics to vary over time. To ensure optimal control performance, controllers should adapt to these changes. When the underlyi…
Improving the Performance of Robust Control through Event-Triggered Learning
Alexander von Rohr, Friedrich Solowjow, Sebastian Trimpe
Robust controllers ensure stability in feedback loops designed under uncertainty but at the cost of performance. Model uncertainty in time-invariant systems can be reduced by recen…
ECLAD: Extracting Concepts with Local Aggregated Descriptors
Andres Felipe Posada-Moreno, Nikita Surya, Sebastian Trimpe
Convolutional neural networks (CNNs) are increasingly being used in critical systems, where robustness and alignment are crucial. In this context, the field of explainable artifici…
Parameter Filter-based Event-triggered Learning
Sebastian Schlor, Friedrich Solowjow, Sebastian Trimpe
Model-based algorithms are deeply rooted in modern control and systems theory. However, they usually come with a critical assumption - access to an accurate model of the system. In…