File size: 3,274 Bytes
8f3caf5 821a9fa 8f3caf5 c4cd568 8f3caf5 9c7d15e 8f3caf5 c4cd568 8f3caf5 c4cd568 8f3caf5 c4cd568 8f3caf5 c4cd568 aa9ad59 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
license: mit
task_categories:
- robotics
---
# Dataset of Reactive Diffusion Policy
## Contents
- [Description](#description)
- [Structure](#structure)
- [Usage](#usage)
- [Tactile Dataset](#tactile-dataset)
## Description
This is the raw and postprocessed dataset used in the paper
[Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation](https://reactive-diffusion-policy.github.io).
- [Paper](https://arxiv.org/pdf/2503.02881)
- [Project Homepage](https://reactive-diffusion-policy.github.io)
- [GitHub Repository](https://github.com/xiaoxiaoxh/reactive_diffusion_policy)
- [Pretrained Models](https://huggingface.co/WendiChen/reactive_diffusion_policy_model)
## Structure
We offer two versions of the dataset:
one is the [full dataset](https://huggingface.co/datasets/WendiChen/reactive_diffusion_policy_dataset/tree/main/dataset_full) used to train the models in our paper,
and the other is a [mini dataset](https://huggingface.co/datasets/WendiChen/reactive_diffusion_policy_dataset/tree/main/dataset_mini) for easier examination.
Both versions include raw and postprocessed subsets of peeling, wiping and lifting.
Each raw subset is structured as follows:
```
subset_name
├── seq_01.pkl
├── seq_02.pkl
├── ...
```
> Note that we split the full raw lifting subset into 2 parts due to file size restrictions.
Each postprocessed subset is stored in [Zarr](https://zarr.dev) format, which is structured as follows:
```
├── action (25710, 4) float32
├── external_img (25710, 240, 320, 3) uint8
├── left_gripper1_img (25710, 240, 320, 3) uint8
├── left_gripper1_initial_marker (25710, 63, 2) float32
├── left_gripper1_marker_offset (25710, 63, 2) float32
├── left_gripper1_marker_offset_emb (25710, 15) float32
├── left_gripper2_img (25710, 240, 320, 3) uint8
├── left_gripper2_initial_marker (25710, 25, 2) float32
├── left_gripper2_marker_offset (25710, 25, 2) float32
├── left_gripper2_marker_offset_emb (25710, 15) float32
├── left_robot_gripper_force (25710, 1) float32
├── left_robot_gripper_width (25710, 1) float32
├── left_robot_tcp_pose (25710, 9) float32
├── left_robot_tcp_vel (25710, 6) float32
├── left_robot_tcp_wrench (25710, 6) float32
├── left_wrist_img (25710, 240, 320, 3) uint8
├── right_robot_gripper_force (25710, 1) float32
├── right_robot_gripper_width (25710, 1) float32
├── right_robot_tcp_pose (25710, 9) float32
├── right_robot_tcp_vel (25710, 6) float32
├── right_robot_tcp_wrench (25710, 6) float32
├── target (25710, 4) float32
└── timestamp (25710,) float32
```
## Usage
Follow the [README in our GitHub repo](https://github.com/xiaoxiaoxh/reactive_diffusion_policy)
to [postprocess the raw data](https://github.com/xiaoxiaoxh/reactive_diffusion_policy#data-postprocessing)
and [train the model](https://github.com/xiaoxiaoxh/reactive_diffusion_policy#-training).
## Tactile Dataset
We also provide the raw videos of the [tactile dataset](https://huggingface.co/datasets/WendiChen/reactive_diffusion_policy_dataset/tree/main/dataset_tactile_embedding) used for generate the PCA embedding in our paper. |