Dieter Büchler
Dieter Büchler
Group leader @ Max Planck Institute for Intelligent Systems
Verified email at - Homepage
Cited by
Cited by
Jointly learning trajectory generation and hitting point prediction in robot table tennis
Y Huang, D Büchler, O Koç, B Schölkopf, J Peters
2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids …, 2016
A lightweight robotic arm with pneumatic muscles for robot learning
D Büchler, H Ott, J Peters
2016 IEEE International Conference on Robotics and Automation (ICRA), 4086-4092, 2016
Learning to play table tennis from scratch using muscular robots
D Büchler, S Guist, R Calandra, V Berenz, B Schölkopf, J Peters
IEEE Transactions on Robotics 38 (6), 3850-3860, 2022
Control of Musculoskeletal Systems using Learned Dynamics Models
D Büchler, R Calandra, B Schölkopf, J Peters
IEEE Robotics and Automation Letters 3 (4), 3161-3168, 2018
Hierarchical reinforcement learning with timed subgoals
N Gürtler, D Büchler, G Martius
Advances in Neural Information Processing Systems 34, 21732-21743, 2021
Learning to control highly accelerated ballistic movements on muscular robots
D Büchler, R Calandra, J Peters
Robotics and Autonomous Systems, 104230, 2022
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, 765-781, 2021
DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems
P Schumacher, D Häufle, D Büchler, S Schmitt, G Martius
arXiv preprint arXiv:2206.00484, 2022
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, ...
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, 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, 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
arXiv preprint arXiv:2305.15189, 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, 1178-1188, 2023
Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning
S Guist, J Schneider, A Dittrich, V Berenz, B Schölkopf, D Büchler
arXiv preprint arXiv:2303.02234, 2023
AIMY: An Open-source Table Tennis Ball Launcher for Versatile and High-fidelity Trajectory Generation
A Dittrich, J Schneider, S Guist, B Schölkopf, D Büchler
arXiv preprint arXiv:2210.06048, 2022
Robot Learning for Muscular Robots
D Büchler
Technische Universität Darmstadt Darmstadt, 2019
Modeling Variability of Musculoskeletal Systems with Heteroscedastic Gaussian Processes
D Büchler, R Calandra, J Peters
Neural Information Processing Systems Workshop on Neurorobotics, 2016
Optimale Trajektorien mit Reinforcement Learning
D Büchler
HAW Hamburg, 2012
Robot Learning for Muscular Systems
D Büchler
Technische Universität, 0
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