Robot reinforcement learning on the constraint manifold P Liu, D Tateo, HB Ammar, J Peters Conference on Robot Learning, 1357-1366, 2022 | 37 | 2022 |
Regularized deep signed distance fields for reactive motion generation P Liu, K Zhang, D Tateo, S Jauhri, J Peters, G Chalvatzaki 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 22 | 2022 |
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning J Urain, A Li, P Liu, C D'Eramo, J Peters Robotics: Science and Systems (RSS), 2021 | 22 | 2021 |
Efficient and Reactive Planning for High Speed Robot Air Hockey P Liu, D Tateo, H Bou-Ammar, J Peters 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 8 | 2021 |
Fast kinodynamic planning on the constraint manifold with deep neural networks P Kicki, P Liu, D Tateo, H Bou-Ammar, K Walas, P Skrzypczyński, J Peters IEEE Transactions on Robotics, 2023 | 7 | 2023 |
Safe reinforcement learning of dynamic high-dimensional robotic tasks: navigation, manipulation, interaction P Liu, K Zhang, D Tateo, S Jauhri, Z Hu, J Peters, G Chalvatzaki 2023 IEEE International Conference on Robotics and Automation (ICRA), 9449-9456, 2023 | 7 | 2023 |
Dimensionality reduction and prioritized exploration for policy search M Memmel, P Liu, D Tateo, J Peters International Conference on Artificial Intelligence and Statistics, 2134-2157, 2022 | 4 | 2022 |
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications P Liu, H Bou-Ammar, J Peters, D Tateo arXiv preprint arXiv:2404.09080, 2024 | 1 | 2024 |
ReDSDF: Regularized Deep Signed Distance Fields for Robotics P Liu, K Zhang, D Tateo, S Jauhri, J Peters, G Chalvatzaki | | 2022 |