aloha_mobile

• Description:

Real dataset. Imitating mobile manipulation tasks that are bimanual and require whole-body control. 50 demonstrations for each task.

• Homepage: https://mobile-aloha.github.io

• Source code: tfds.robotics.rtx.AlohaMobile

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 47.42 GiB

• Auto-cached (documentation): No

• Splits:

• Feature structure:

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': string,
    }),
    'steps': Dataset({
        'action': Tensor(shape=(16,), dtype=float32),
        'discount': Scalar(shape=(), dtype=float32),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'language_instruction': string,
        'observation': FeaturesDict({
            'cam_high': Image(shape=(480, 640, 3), dtype=uint8),
            'cam_left_wrist': Image(shape=(480, 640, 3), dtype=uint8),
            'cam_right_wrist': Image(shape=(480, 640, 3), dtype=uint8),
            'state': Tensor(shape=(14,), dtype=float32),
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})

• Feature documentation:

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@inproceedings{fu2024mobile,author = {Fu, Zipeng and Zhao, Tony Z. and Finn, Chelsea},title = {Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation},booktitle = {arXiv},year = {2024},}