Tass0sm / mp_baselines_fork

Implement various MP methods.

Motion Planning Baselines in PyTorch

This library implements various Motion Planning methods.

NOTE: mp_baslines is under heavy development and highly experimental.

Installation

Simply activate your conda/Python environment and run

pip install -e .

Examples

python examples/pointmass_dense_2d_CHOMP.py
python examples/pointmass_dense_2d_GPMP.py
python examples/pointmass_grid_circles_2d_Stoch-GPMP.py
python examples/pointmass_grid_circles_2d_STOMP.py
python examples/pointmass_grid_circles_2d_MPPI.py
python examples/pointmass_dense_2d_RRT_multiprocess.py

Contact

If you have any questions or find any bugs, please let us know:

• An Le, [e-mail]
• Joao Carvalho, [e-mail]

Citation

If you found this repository useful, please consider citing these references:

@inproceedings{le2023accelerating,
  title={Accelerating Motion Planning via Optimal Transport},
  author={Le, An T. and Chalvatzaki, Georgia and Biess, Armin and Peters, Jan},
  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
  year={2023}
}

@article{carvalho2023motion,
  title={Motion planning diffusion: Learning and planning of robot motions with diffusion models},
  author={Carvalho, Joao and Le, An T and Baierl, Mark and Koert, Dorothea and Peters, Jan},
  journal={arXiv preprint arXiv:2308.01557},
  year={2023}
}