4 papers
Scaling CrossQ with Weight Normalization
Daniel Palenicek, Florian Vogt, Jan Peters
Reinforcement learning has achieved significant milestones, but sample efficiency remains a bottleneck for real-world applications. Recently, CrossQ has demonstrated state-of-the-a…
Towards Safe Robot Foundation Models Using Inductive Biases
Maximilian Tölle, Theo Gruner, Daniel Palenicek +6
Safety is a critical requirement for the real-world deployment of robotic systems. Unfortunately, while current robot foundation models show promising generalization capabilities a…
Analysing the Interplay of Vision and Touch for Dexterous Insertion Tasks
Janis Lenz, Theo Gruner, Daniel Palenicek +2
Robotic insertion tasks remain challenging due to uncertainties in perception and the need for precise control, particularly in unstructured environments. While humans seamlessly c…
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
Daniel Palenicek, Michael Lutter, Joao Carvalho +1
Model-based reinforcement learning is one approach to increase sample efficiency. However, the accuracy of the dynamics model and the resulting compounding error over modelled traj…