Movement Primitive Diffusion Demonstration Data

Training data for the experiments described in the paper "Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects".

Movement Primitive Diffusion (MPD) is a diffusion-based imitation learning method for high-quality robotic motion generation that focuses on gentle manipulation of deformable objects.

@article{Scheikl2024MPD, author={Scheikl, Paul Maria and Schreiber, Nicolas and Haas, Christoph and Freymuth, Niklas and Neumann, Gerhard and Lioutikov, Rudolf and Mathis-Ullrich, Franziska}, title={Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects}, journal={IEEE Robotics and Automation Letters}, year={2024}, volume={9}, number={6}, pages={5338-5345}, doi={10.1109/LRA.2024.3382529}, }