---
license: mit
task_categories:
- robotics
tags:
- pick-and-place
- manipulation
- reinforcement-learning
---

This is the official repository for the training dataset of the paper: [Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter](https://huggingface.co/papers/2503.09423).

We study the task of language-conditioned pick and place in clutter, where a robot should grasp a target object in open clutter and move it to a specified place. This dataset supports the A$^2$ action prior alignment method, which integrates foundation priors from vision, language, and action to enable effective policies.

Project Page: https://xukechun.github.io/papers/A2
Code: https://github.com/xukechun/Action-Prior-Alignment

Please download the file and unzip it in the `data` folder.

### Sample Usage

The following snippets from the [GitHub repository](https://github.com/xukechun/Action-Prior-Alignment) demonstrate how to use this dataset for data collection, training, and evaluation.

#### Data Collection
- For pick data
```bash
bash scripts/data_collection/collect_data_grasp.sh
```
- For place data
```bash
bash scripts/data_collection/collect_data_place.sh
```

#### Training
- Unified training for pick and place
```bash
bash scripts/train/train_clutter_gp_unified.sh
```
- Adaptation for place
```bash
bash scripts/train/train_clutter_gp_adaptive.sh
```

#### Evaluation
To test the pre-trained model, simply change the location of `--model_path`:

- Pick
```bash
bash scripts/test/test_grasp.sh
```
- Place
```bash
bash scripts/test/test_place.sh
```
- Pick and place
```bash
bash scripts/test/test_pickplace.sh
```

### Citation

If you find this work useful, please consider citing:

```bibtex
@article{xu2025efficient,
  title={Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter},
  author={Xu, Kechun and Xia, Xunlong and Wang, Kaixuan and Yang, Yifei and Mao, Yunxuan and Deng, Bing and Xiong, Rong and Wang, Yue},
  journal={arXiv preprint arXiv:2503.09423},
  year={2025}
}
```