---
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}
}
```