Add dataset card for DADP

README.md

@@ -0,0 +1,42 @@
+---
+task_categories:
+- reinforcement-learning
+---
+
+This repository contains the datasets used in the paper [DADP: Domain Adaptive Diffusion Policy](https://huggingface.co/papers/2602.04037).
+
+[Project Page](https://outsider86.github.io/DomainAdaptiveDiffusionPolicy/) | [GitHub Repository](https://github.com/QinghangLiu/DADP_official)
+
+### Dataset Description
+
+DADP (Domain Adaptive Diffusion Policy) is a framework for learning domain-adaptive policies that can generalize to unseen transition dynamics. The datasets provided include trajectories for various locomotion and manipulation benchmarks:
+- **Locomotion:** Ant, Walker2d, HalfCheetah, Hopper.
+- **Manipulation:** Adroit (Door, Relocate).
+
+The manipulation datasets are sourced from the [ODRL (Off-Dynamics RL)](https://github.com/OffDynamicsRL/off-dynamics-rl) project and are noted to be smaller in size and near-random in quality compared to the locomotion environments.
+
+### Usage
+
+As per the official repository, these datasets are intended to be used with the [Minari](https://github.com/Farama-Foundation/Minari) framework. Once you have downloaded the datasets, extract and move them into your local Minari datasets directory (typically `~/.minari/datasets/`).
+
+The expected directory structure is:
+```text
+~/.minari/
+└── datasets/
+    ├── RandomAnt/
+    ├── RandomWalker2d/
+    ├── Adroit/
+    └── ...
+```
+
+For detailed instructions on training and evaluation, please refer to the [official GitHub README](https://github.com/QinghangLiu/DADP_official).
+
+### Citation
+```bibtex
+@article{liu2024dadp,
+  title={DADP: Domain Adaptive Diffusion Policy},
+  author={Liu, Qinghang and others},
+  journal={arXiv preprint arXiv:2602.04037},
+  year={2024}
+}
+```