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Final Dataset card

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@@ -12,7 +12,7 @@ tags:
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  license: openmdw-1.0
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  ---
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- # Bridge LeRobot v3
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  ## Dataset Summary
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  This LeRobot v3 conversion preserves the dataset for workflows that use the LeRobot data loader and Hugging Face Hub-native robotics dataset conventions. The conversion changes the storage layout: frame-level tabular data is stored in Apache Parquet shards, visual observations are stored as MP4 videos, and metadata records the schema, feature statistics, task IDs, episode boundaries, and path templates.
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  ### Dataset Sources
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  - Repository: https://huggingface.co/datasets/nvidia/bridge_lerobot_v3
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  - BridgeData V2 paper: https://arxiv.org/abs/2308.12952
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  - LeRobotDataset v3.0 documentation: https://huggingface.co/docs/lerobot/lerobot-dataset-v3
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- ## Uses
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-
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- ### Direct Use
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  This dataset is intended for research and development in:
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  This dataset is not intended to be used as the sole validation source for safety-critical robot deployment. Policies trained on this data should be evaluated in the target environment, with appropriate robot safety controls, before any physical deployment.
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- ## Dataset Structure
 
 
 
 
 
 
 
 
 
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  The repository follows the LeRobotDataset v3.0 layout:
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  `-- file-*.mp4
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  ```
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- ### Repository Metadata
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  The following values are taken from the repository's `meta/info.json`.
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  The upstream BridgeData V2 project describes the source data as collected on a WidowX 250 6DOF robot arm at 5 Hz. The converted repository does not populate `robot_type` in `meta/info.json`.
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  ### Features
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  The following feature schema is declared in `meta/info.json`.
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  This repository converts Bridge data into LeRobotDataset v3.0. In v3, multiple episodes can be concatenated into larger Parquet and MP4 shard files, while metadata is used to recover per-episode boundaries and feature statistics. This layout reduces file-system pressure and supports Hub-native loading and streaming workflows.
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- ## Bias, Risks, and Limitations
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  - The dataset reflects the embodiment, control frequency, camera setup, task distribution, and environments of the source BridgeData V2 collection.
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  - The upstream data is concentrated around tabletop and toy-kitchen manipulation tasks; policies trained only on this dataset may not generalize to other robots, objects, lighting, homes, labs, or industrial settings.
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  - The repository metadata reports a converted package with fewer episodes than the full upstream BridgeData V2 trajectory count.
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  - This dataset should not be used as the sole basis for validating safe real-world robot behavior.
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- ## Personal and Sensitive Information
 
 
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- BridgeData V2 is robot manipulation data collected in controlled robotics environments. It is not intended to contain personal or sensitive information. Because the source uses real camera imagery, users should still inspect samples for their own release, redistribution, or downstream demo requirements.
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  ## Citation
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  license: openmdw-1.0
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  ---
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+ # BridgeData2 LeRobot v3
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  ## Dataset Summary
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  This LeRobot v3 conversion preserves the dataset for workflows that use the LeRobot data loader and Hugging Face Hub-native robotics dataset conventions. The conversion changes the storage layout: frame-level tabular data is stored in Apache Parquet shards, visual observations are stored as MP4 videos, and metadata records the schema, feature statistics, task IDs, episode boundaries, and path templates.
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+ This dataset is ready for commercial or non-commercial uses.
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+
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+ ## Dataset Owner(s)
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+
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+ NVIDIA Corporation
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+
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+ ## Dataset Creation Date
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+ 2026-05-26
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+ ## Version:
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+ v1.0 <br>
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+ ## License/Terms of Use
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+ This dataset is released under the [OpenMDW1.1](https://openmdw.ai/)
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+
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  ### Dataset Sources
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  - Repository: https://huggingface.co/datasets/nvidia/bridge_lerobot_v3
 
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  - BridgeData V2 paper: https://arxiv.org/abs/2308.12952
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  - LeRobotDataset v3.0 documentation: https://huggingface.co/docs/lerobot/lerobot-dataset-v3
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+ ## Intended Use
 
 
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  This dataset is intended for research and development in:
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  This dataset is not intended to be used as the sole validation source for safety-critical robot deployment. Policies trained on this data should be evaluated in the target environment, with appropriate robot safety controls, before any physical deployment.
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+ ## Dataset Characterization
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+ **Data Collection Method**
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+
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+ [Not Applicable]
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+ **Labeling Method**
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+
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+ [Not Applicable]
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+ ## Dataset Format
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  The repository follows the LeRobotDataset v3.0 layout:
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  `-- file-*.mp4
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  ```
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+ ### Dataset Quantification
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  The following values are taken from the repository's `meta/info.json`.
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  The upstream BridgeData V2 project describes the source data as collected on a WidowX 250 6DOF robot arm at 5 Hz. The converted repository does not populate `robot_type` in `meta/info.json`.
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+ Total Data Storage: 90 GB
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+
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  ### Features
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  The following feature schema is declared in `meta/info.json`.
 
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  This repository converts Bridge data into LeRobotDataset v3.0. In v3, multiple episodes can be concatenated into larger Parquet and MP4 shard files, while metadata is used to recover per-episode boundaries and feature statistics. This layout reduces file-system pressure and supports Hub-native loading and streaming workflows.
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+ ## Risks, and Limitations
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  - The dataset reflects the embodiment, control frequency, camera setup, task distribution, and environments of the source BridgeData V2 collection.
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  - The upstream data is concentrated around tabletop and toy-kitchen manipulation tasks; policies trained only on this dataset may not generalize to other robots, objects, lighting, homes, labs, or industrial settings.
 
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  - The repository metadata reports a converted package with fewer episodes than the full upstream BridgeData V2 trajectory count.
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  - This dataset should not be used as the sole basis for validating safe real-world robot behavior.
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+ ## Ethical Considerations
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+ NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. Developers should work with their internal developer teams to ensure this dataset meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
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+ Please report model quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
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  ## Citation
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