Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning. - Jonas Günster; Puze Liu; Jan Peters 001; Davide Tateo (CoRL, 2024)

Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning. - Piotr Kicki; Davide Tateo; Puze Liu; Jonas Günster; Jan Peters 001; Krzysztof Walas (CoRL, 2024)

A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. - Puze Liu; Jonas Günster; Niklas Funk; Simon Gröger; Dong Chen; Haitham Bou-Ammar; Julius Jankowski; Ante Maric; Sylvain Calinon; Andrej Orsula; Miguel S. Olivares-Méndez; Hongyi Zhou; et al. (NeurIPS, 2024)

Towards Safe Robot Foundation Models. - Maximilian Tölle; Theo Gruner; Daniel Palenicek; Jonas Günster; Puze Liu; Joe Watson; Davide Tateo; Jan Peters 001 (CoRR, 2025)

Towards Safe Robot Foundation Models Using Inductive Biases. - Maximilian Tölle; Theo Gruner; Daniel Palenicek; Tim Schneider; Jonas Günster; Joe Watson; Davide Tateo; Puze Liu; Jan Peters 001 (CoRR, 2025)