- Description:
xArm short-horizon table-top tasks
Homepage: https://rot-robot.github.io/
Source code:
tfds.robotics.rtx.NyuRotDatasetConvertedExternallyToRlds
Versions:
0.1.0
(default): Initial release.
Download size:
Unknown size
Dataset size:
5.33 MiB
Auto-cached (documentation): Yes
Splits:
Split | Examples |
---|---|
'train' |
14 |
- Feature structure:
FeaturesDict({
'episode_metadata': FeaturesDict({
'file_path': Text(shape=(), dtype=string),
}),
'steps': Dataset({
'action': Tensor(shape=(7,), dtype=float32, description=Robot action, consists of [3x robot end effector delta positions, 3x robot end effector rotations (roll, pitch, yaw),1x gripper open/close (0-open, 1-closed)].),
'discount': Scalar(shape=(), dtype=float32, description=Discount if provided, default to 1.),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'language_embedding': Tensor(shape=(512,), dtype=float32, description=Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5),
'language_instruction': Text(shape=(), dtype=string),
'observation': FeaturesDict({
'image': Image(shape=(84, 84, 3), dtype=uint8, description=Main camera RGB observation.),
'state': Tensor(shape=(7,), dtype=float32, description=Robot state, consists of [3x robot end effector positions, 3x robot end effector rotations (roll, pitch, yaw),1x gripper open/close (0-open, 1-closed)].),
}),
'reward': Scalar(shape=(), dtype=float32, description=Reward if provided, 1 on final step for demos.),
}),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
episode_metadata | FeaturesDict | |||
episode_metadata/file_path | Text | string | Path to the original data file. | |
steps | Dataset | |||
steps/action | Tensor | (7,) | float32 | Robot action, consists of [3x robot end effector delta positions, 3x robot end effector rotations (roll, pitch, yaw),1x gripper open/close (0-open, 1-closed)]. |
steps/discount | Scalar | float32 | Discount if provided, default to 1. | |
steps/is_first | Tensor | bool | ||
steps/is_last | Tensor | bool | ||
steps/is_terminal | Tensor | bool | ||
steps/language_embedding | Tensor | (512,) | float32 | Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5 |
steps/language_instruction | Text | string | Language Instruction. | |
steps/observation | FeaturesDict | |||
steps/observation/image | Image | (84, 84, 3) | uint8 | Main camera RGB observation. |
steps/observation/state | Tensor | (7,) | float32 | Robot state, consists of [3x robot end effector positions, 3x robot end effector rotations (roll, pitch, yaw),1x gripper open/close (0-open, 1-closed)]. |
steps/reward | Scalar | float32 | Reward if provided, 1 on final step for demos. |
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- Citation:
@inproceedings{haldar2023watch,
title={Watch and match: Supercharging imitation with regularized optimal transport},
author={Haldar, Siddhant and Mathur, Vaibhav and Yarats, Denis and Pinto, Lerrel},
booktitle={Conference on Robot Learning},
pages={32--43},
year={2023},
organization={PMLR}
}