PUMA: Deep Metric Imitation Learning for Stable Motion Primitives

Code accompanying the paper: "Deep Metric Imitation Learning for Stable Motion Primitives" accepted at Advanced Intelligent Systems. For details, please refer to paper.

The current version of the paper can be cited using the following reference:

@article{PerezDattari2024AISY,
  author  = {P\'{e}rez-Dattari, Rodrigo AND Della Santina, Cosimo AND Kober, Jens},
  journal = {Advanced Intelligent Systems},
  title   = {PUMA: Deep Metric Imitation Learning for Stable Motion Primitives},
  year    = {2024},
  note    = {Accepted},
}

Teaser: Non-Euclidean and second-order learned motions

Installation

You can install the package using pip.

pip install -r requirements.txt

Usage

In the folder src run:

Training

  python train.py --params <params_file_name>

The parameter files required for the argument params_file_name can be found in the folder params.

Simulate learned 2D motion

  python simulate_ds.py

Hyperparameter Optimization

  python run_optuna.py --params <params_file_name>

Troubleshooting

If you run into problems of any kind, don't hesitate to open an issue on this repository.