CCDP

CCDP Internal Repository

This repository contains the codebase for the paper CCDP. The code was developed by the CCDP team during A. Razmjoo's internship at HRI (Oct. 2024 – Mar. 2025).

If you encounter any issues or need clarification, please contact A. Razmjoo directly or reach out to other team members.

Repository Structure

This repository is organized around the cleaned door-manipulation pipeline and the assets it depends on.

• Main Codes/: Cleaned and structured door pipeline used for the paper results.
  • door_cleaned.ipynb: Jupyter notebook version of the door example.
  • door_pipeline_clean.py: Scripted pipeline with a main() entrypoint for data generation, training, and sampling.
  • door_config.py: Centralized configuration, paths, and defaults.
  • door_models.py: Model blocks, datasets, and diffusion helpers.
• models/: Pretrained checkpoints and cached datasets (*.pth, *.pkl, *.pt).
• xml/: Mujoco environment definitions and mesh assets used by the door task.
• ccdp.yml: Conda environment specification.
• requirements.txt: Pip dependencies if you are not using conda.

Third-Party Assets

This repository includes third-party MuJoCo models and assets. See THIRD_PARTY_NOTICES.md for required attributions and license texts.

Usage

To use this repository, follow these steps:

1. Install the required dependencies:

   conda env create -f ccdp.yml

   Or, with pip:

   pip install -r requirements.txt

2. Download the pretrained models and cached demos (required for the demos and to reproduce results):

   python download_models.py

3. Run the notebook:
   • Notebook:

     jupyter notebook "Main Codes/door_cleaned.ipynb"

The scripted pipeline caches generated demos and checkpoints in models/.

Citation

If you find this work useful, please cite:

@inproceedings{Razmjoo25IROS,
	author={Razmjoo, A. and Calinon, S. and Gienger, M. and Zhang, F.},
	title={{CCDP}: Composition of Conditional Diffusion Policies with Guided Sampling},
	booktitle={Proc.\ {IEEE/RSJ} Intl Conf.\ on Intelligent Robots and Systems ({IROS})},
	pages={20036--20043},
	year={2025}
}