---
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}
}
```