- 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:
Split | Examples |
---|---|
'train' |
276 |
- 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:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_metadata | FeaturesDict | |||
episode_metadata/file_path | Tensor | string | ||
steps | Dataset | |||
steps/action | Tensor | (16,) | float32 | |
steps/discount | Scalar | float32 | ||
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/language_instruction | Tensor | string | ||
steps/observation | FeaturesDict | |||
steps/observation/cam_high | Image | (480, 640, 3) | uint8 | |
steps/observation/cam_left_wrist | Image | (480, 640, 3) | uint8 | |
steps/observation/cam_right_wrist | Image | (480, 640, 3) | uint8 | |
steps/observation/state | Tensor | (14,) | float32 | |
steps/reward | Scalar | float32 |
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},}