| --- |
| license: mit |
| library_name: pytorch |
| pipeline_tag: robotics |
| tags: |
| - diffusion |
| - inverse-kinematics |
| - intrinsic-dimension |
| - robotics |
| - franka |
| - ur5 |
| --- |
| |
| # Exploring the Intrinsic Geometry of Diffusion Models with Constrained Inverse Kinematics |
|
|
| Models and data for the CoRL 2026 paper by Miguel Angel Rogel Garcia\*, Phone Thiha Kyaw\* and Jonathan Kelly (\*equal contribution). |
| An earlier version appeared at the RSS 2026 Workshop on Diffusion for Robot Learning. |
| |
| [Paper](https://arxiv.org/abs/2606.26408) · [Project page](https://papers.starslab.ca/diffusion-ik-geometry/) · [Code](https://github.com/utiasSTARS/ConstraintIK) |
| |
| ## Files |
| |
| | Path | Contents | |
| |---|---| |
| | `checkpoints/ur5.pt` | UR5 model used throughout the paper | |
| | `checkpoints/franka.pt` | Franka model used throughout the paper | |
| | `checkpoints/size_sweep/{robot}/{constraint}/n040000.pt` | 14 single-family models trained on N = 40,000 configurations (training-set size ablation, App. C) | |
| | `data/ground_truth_ur5.pt`, `data/ground_truth_franka.pt` | Evaluation targets, 50 per constraint family, each with its set of IK solutions | |
| | `data/train_ur5.pt`, `data/train_franka.pt` | Training sets of the two paper models | |
| |
| Each paper model is a conditional DDPM (25.6M parameters, sigmoid schedule, T = 100) trained for 500k steps on all seven constraint families of one robot. |
| The single-family models use a cosine schedule and 100k steps. |
| A checkpoint stores the model and EMA weights with the normalizers of its training set. |
| |
| ## Usage |
| |
| ```bash |
| git clone https://github.com/utiasSTARS/ConstraintIK.git && cd ConstraintIK |
| pip install -e . |
| python scripts/download.py # paper models and evaluation targets |
| python scripts/download.py --training # also the training sets |
| python scripts/download.py --size_sweep # also the 14 single-family models |
| ``` |
| |
| ```python |
| from constraint_ik.checkpoint import load_checkpoint |
| ik = load_checkpoint("checkpoints/franka.pt", "cuda") |
| ``` |
| |
| ## Citation |
| |
| ```bibtex |
| @inproceedings{rogelgarcia2026intrinsic, |
| title = {Exploring the Intrinsic Geometry of Diffusion Models with Constrained Inverse Kinematics}, |
| author = {Rogel Garcia, Miguel Angel and Kyaw, Phone Thiha and Kelly, Jonathan}, |
| booktitle = {Conference on Robot Learning (CoRL)}, |
| year = {2026}, |
| url = {https://arxiv.org/abs/2606.26408} |
| } |
| ``` |
| |
