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license: cc-by-4.0
task_categories:
- robotics
tags:
- LeRobot
- Robotic manipulation
pretty_name: BridgeData V2 Scripted Demos
size_categories:
- 100K<n<1M
---
## BridgeData V2 Scripted Demos
Scripted demonstrations in [BridgeData V2](https://rail-berkeley.github.io/bridgedata/).
Ported from raw *scripted_6_18* data at full resolution to LeRobotDataset v3.0 format (0.01 TiB | 0.1k inodes).
<div align="center" style="margin: 16px 0;">
<video controls autoplay loop muted playsinline style="max-width: 100%; border-radius: 10px;">
<source src="https://huggingface.co/datasets/jnogga/bridge_data_v2_scripted/resolve/main/bridge_example_episode.mp4" type="video/mp4">
Your browser does not support the video tag.
</video>
</div>
For the teleoperated trajectories with language annotation, see [jnogga/bridge_data_v2_teleop](https://huggingface.co/datasets/jnogga/bridge_data_v2_teleop).
## Dataset Structure
Note that the available cameras vary between episodes. Missing camera perspectives are padded, and the corresponding *_available* sample fields serve as a mask.
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v3.0",
"robot_type": "widow_x",
"fps": 5,
"data_files_size_in_mb": 100.0,
"video_files_size_in_mb": 200.0,
"chunks_size": 1000,
"total_episodes": 9701,
"total_frames": 456260,
"total_tasks": 9701,
"splits": {
"train": "0:9701"
},
"data_path": "data/chunk-{chunk_index:03d}/file_{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file_{file_index:03d}.mp4",
"features": {
"action.cartesian": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
],
"fps": 5
},
"action.gripper_position": {
"dtype": "float32",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.cartesian": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
],
"fps": 5
},
"observation.gripper_position": {
"dtype": "float32",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.eef_transform": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
],
"fps": 5
},
"observation.joint_position": {
"dtype": "float32",
"shape": [
6
],
"names": [
"joint_0",
"joint_1",
"joint_2",
"joint_3",
"joint_4",
"joint_5"
],
"fps": 5
},
"observation.joint_velocity": {
"dtype": "float32",
"shape": [
6
],
"names": [
"joint_0",
"joint_1",
"joint_2",
"joint_3",
"joint_4",
"joint_5"
],
"fps": 5
},
"frame_index": {
"dtype": "int64",
"shape": [
1
],
"names": null,
"fps": 5
},
"timestamp": {
"dtype": "float32",
"shape": [
1
],
"names": null,
"fps": 5
},
"index": {
"dtype": "int64",
"shape": [
1
],
"names": null,
"fps": 5
},
"task_index": {
"dtype": "int64",
"shape": [
1
],
"names": null,
"fps": 5
},
"episode_index": {
"dtype": "int64",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.images.camera_0_available": {
"dtype": "bool",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.images.camera_1_available": {
"dtype": "bool",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.images.camera_2_available": {
"dtype": "bool",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.images.camera_3_available": {
"dtype": "bool",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.images.camera_4_available": {
"dtype": "bool",
"shape": [
1
],
"names": null,
"fps": 5
},
"observation.images.camera_0": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "h264",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 5,
"video.channels": 3,
"has_audio": false
},
"fps": 5
},
"observation.images.camera_1": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "h264",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 5,
"video.channels": 3,
"has_audio": false
},
"fps": 5
},
"observation.images.camera_2": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "h264",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 5,
"video.channels": 3,
"has_audio": false
},
"fps": 5
},
"observation.images.camera_3": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "h264",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 5,
"video.channels": 3,
"has_audio": false
},
"fps": 5
},
"observation.images.camera_4": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "h264",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 5,
"video.channels": 3,
"has_audio": false
},
"fps": 5
}
}
}
```
## Getting started
```py
# pip install lerobot
from lerobot.datasets.lerobot_dataset import LeRobotDataset
dataset = LeRobotDataset("jnogga/bridge_data_v2_scripted")
```
See [bridge_example.ipynb](bridge_example.ipynb) for a more detailed example.
## Citation
All credit goes to the original authors of BridgeData V2. If you find their work helpful, please cite
**BibTeX:**
```bibtex
@inproceedings{walke2023bridgedata,
title={BridgeData V2: A Dataset for Robot Learning at Scale},
author={Walke, Homer and Black, Kevin and Lee, Abraham and Kim, Moo Jin and Du, Max and Zheng, Chongyi and Zhao, Tony and Hansen-Estruch, Philippe and Vuong, Quan and He, Andre and Myers, Vivek and Fang, Kuan and Finn, Chelsea and Levine, Sergey},
booktitle={Conference on Robot Learning (CoRL)},
year={2023}
}
``` |