| Open X-Embodiment: Robotic Learning Datasets and RT-X Models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... International Conference on Robotics and Automation (ICRA), 2024 | 460* | 2024 |
| Learning to play table tennis from scratch using muscular robots D Büchler, S Guist, R Calandra, V Berenz, B Schölkopf, J Peters Transactions on Robotics (T-RO) 38 (6), 3850-3860, 2022 | 92 | 2022 |
| Jointly learning trajectory generation and hitting point prediction in robot table tennis Y Huang, D Büchler, O Koç, B Schölkopf, J Peters International Conference on Humanoid Robots (Humanoids), 650-655, 2016 | 52 | 2016 |
| A lightweight robotic arm with pneumatic muscles for robot learning D Büchler, H Ott, J Peters International Conference on Robotics and Automation (ICRA), 4086-4092, 2016 | 50 | 2016 |
| Open X-Embodiment: Robotic Learning Datasets and RT-X Models Q Vuong, S Levine, HR Walke, K Pertsch, A Singh, R Doshi, C Xu, J Luo, ... Towards Generalist Robots: Learning Paradigms for Scalable Skill Acquisition …, 2023 | 30 | 2023 |
| Hierarchical reinforcement learning with timed subgoals N Gürtler, D Büchler, G Martius Advances in Neural Information Processing Systems 34, 21732-21743, 2021 | 30 | 2021 |
| Learning to control highly accelerated ballistic movements on muscular robots D Büchler, R Calandra, J Peters Robotics and Autonomous Systems (RAS), 104230, 2022 | 27 | 2022 |
| DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems P Schumacher, D Häufle, D Büchler, S Schmitt, G Martius International Conference on Learning Representations (ICLR), 2023 | 26 | 2023 |
| Control of Musculoskeletal Systems using Learned Dynamics Models D Büchler, R Calandra, B Schölkopf, J Peters Robotics and Automation Letters (RA-L) 3 (4), 3161-3168, 2018 | 26 | 2018 |
| Action-conditional recurrent kalman networks for forward and inverse dynamics learning V Shaj, P Becker, D Büchler, H Pandya, N van Duijkeren, CJ Taylor, ... Conference on Robot Learning (CoRL), 765-781, 2021 | 17 | 2021 |
| A Learning-based Iterative Control Framework for Controlling a Robot Arm with Pneumatic Artificial Muscles H Ma, D Büchler, B Schölkopf, M Muehlebach Robotics: Science and Systems (R:SS), 2022 | 12 | 2022 |
| Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios V Shaj, D Büchler, R Sonker, P Becker, G Neumann International Conference on Learning Representations (ICLR), 2021 | 11 | 2021 |
| Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts J Achterhold, P Tobuschat, H Ma, D Buechler, M Muehlebach, J Stueckler Learning for Dynamics and Control Conference (L4DC), 878-890, 2023 | 10 | 2023 |
| Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks I Wochner, P Schumacher, G Martius, D Büchler, S Schmitt, D Haeufle Conference on Robot Learning (CoRL), 1178-1188, 2022 | 10 | 2022 |
| AIMY: an open-source table tennis ball launcher for versatile and high-fidelity trajectory generation A Dittrich, J Schneider, S Guist, N Gürtler, H Ott, T Steinbrenner, ... International Conference on Robotics and Automation (ICRA), 3058-3064, 2023 | 6 | 2023 |
| The o80 C++ templated toolbox: Designing customized Python APIs for synchronizing realtime processes V Berenz, M Naveau, F Widmaier, M Wüthrich, JC Passy, S Guist, ... Journal of Open Source Software, 2020 | 6 | 2020 |
| Reinforcement learning with model-based feedforward inputs for robotic table tennis H Ma, D Büchler, B Schölkopf, M Muehlebach Autonomous Robots 47 (8), 1387-1403, 2023 | 5 | 2023 |
| Investigating the Impact of Action Representations in Policy Gradient Algorithms J Schneider, P Schumacher, D Häufle, B Schölkopf, D Büchler Workshop on effective Representations, Abstractions, and Priors for Robot …, 2023 | 3 | 2023 |
| Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion S Guist, J Schneider, H Ma, V Berenz, J Martus, F Grüninger, ... Robotics: Science and Systems (R:SS), 2024 | 2* | 2024 |
| Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning S Guist, J Schneider, A Dittrich, V Berenz, B Schölkopf, D Büchler Robotics: Science and Systems (R:SS), 2023 | 2 | 2023 |
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHبريد إلكتروني تم التحقق منه على tuebingen.mpg.de
