23 citations · 52 across the 10 of their papers we have counts for
4 papers · 1 filter
A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects
David Stenger, Paul Brunzema, Johanna Menn +3
In the past decade, Bayesian optimization (BO) has emerged as a powerful and adaptable framework for automatic controller tuning and robot learning. This article offers a comprehen…
Synergistic Action and Style Priors for Learning Legged Locomotion
Oliver Hausdörfer, Alexander von Rohr, Éric Lefort +1
Deep Reinforcement Learning (DRL) enables robots to learn complex behaviors through interaction with the environment. However, due to the unrestricted nature of the learning algori…
Robust Direct Data-Driven Control for Probabilistic Systems
Alexander von Rohr, Dmitrii Likhachev, Sebastian Trimpe
We propose a data-driven control method for systems with aleatoric uncertainty, for example, robot fleets with variations between agents. Our method leverages shared trajectory dat…
Gait learning for soft microrobots controlled by light fields
Alexander von Rohr, Sebastian Trimpe, Alonso Marco +2
Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize…