Robot Reinforcement Learning on the Constraint Manifold. - Puze Liu; Davide Tateo; Haitham Bou-Ammar; Jan Peters 001 (CoRL, 2021)

Efficient and Reactive Planning for High Speed Robot Air Hockey. - Puze Liu; Davide Tateo; Haitham Bou-Ammar; Jan Peters 001 (IROS, 2021)

Dimensionality Reduction and Prioritized Exploration for Policy Search. - Marius Memmel; Puze Liu; Davide Tateo; Jan Peters 001 (AISTATS, 2022)

Regularized Deep Signed Distance Fields for Reactive Motion Generation. - Puze Liu; Kuo Zhang; Davide Tateo; Snehal Jauhri; Jan Peters 001; Georgia Chalvatzaki (IROS, 2022)

Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction. - Puze Liu; Kuo Zhang; Davide Tateo; Snehal Jauhri; Zhiyuan Hu; Jan Peters 001; Georgia Chalvatzaki (ICRA, 2023)

Composable energy policies for reactive motion generation and reinforcement learning. - Julen Urain; Anqi Li 001; Puze Liu; Carlo D'Eramo; Jan Peters 001 (Int. J. Robotics Res., 2023)

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)

ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. - Christopher E. Mower; Yuhui Wan; Hongzhan Yu; Antoine Grosnit; Jonas Gonzalez-Billandon; Matthieu Zimmer; Jinlong Wang; Xinyu Zhang; Yao Zhao; Anbang Zhai; Puze Liu; Davide Tateo; et al. (CoRR, 2024)

Energy-based Contact Planning under Uncertainty for Robot Air Hockey. - Julius Jankowski; Ante Maric; Puze Liu; Davide Tateo; Jan Peters 001; Sylvain Calinon (CoRR, 2024)

Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks. - Piotr Kicki; Puze Liu; Davide Tateo; Haitham Bou-Ammar; Krzysztof Walas; Piotr Skrzypczynski; Jan Peters 001 (IEEE Trans. Robotics, 2024)

ROSCOM: Robust Safe Reinforcement Learning on Stochastic Constraint Manifolds. - Shangding Gu; Puze Liu; Alap Kshirsagar; Guang Chen 001; Jan Peters 001; Alois Knoll (IEEE Trans Autom. Sci. Eng., 2025)

Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. - Puze Liu; Haitham Bou-Ammar; Jan Peters 001; Davide Tateo (IEEE Trans. Robotics, 2025)

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

Adaptive Control Based Friction Estimation for Tracking Control of Robot Manipulators. - Junning Huang; Davide Tateo; Puze Liu; Jan Peters 001 (IEEE Robotics Autom. Lett., 2025)

Morphologically Symmetric Reinforcement Learning for Ambidextrous Bimanual Manipulation. - Zechu Li; Yufeng Jin; Daniel Felipe Ordoñez Apraez; Claudio Semini; Puze Liu; Georgia Chalvatzaki (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)

Maximum Total Correlation Reinforcement Learning. - Bang You; Puze Liu; Huaping Liu; Jan Peters 001; Oleg Arenz (CoRR, 2025)