nyu_franka_play_dataset_converted_externally_to_rlds

• Description:

Franka interacting with toy kitchens

• Homepage: https://play-to-policy.github.io/

• Source code: tfds.robotics.rtx.NyuFrankaPlayDatasetConvertedExternallyToRlds

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 5.18 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'train'	365
'val'	91

• Feature structure:

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    }),
    'steps': Dataset({
        'action': Tensor(shape=(15,), dtype=float32, description=Robot action, consists of [7x joint velocities, 3x EE delta xyz, 3x EE delta rpy, 1x gripper position, 1x terminate episode].),
        '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({
            'depth': Tensor(shape=(128, 128, 1), dtype=int32, description=Right camera depth observation.),
            'depth_additional_view': Tensor(shape=(128, 128, 1), dtype=int32, description=Left camera depth observation.),
            'image': Image(shape=(128, 128, 3), dtype=uint8, description=Right camera RGB observation.),
            'image_additional_view': Image(shape=(128, 128, 3), dtype=uint8, description=Left camera RGB observation.),
            'state': Tensor(shape=(13,), dtype=float32, description=Robot state, consists of [7x robot joint angles, 3x EE xyz, 3x EE rpy.),
        }),
        '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	(15,)	float32	Robot action, consists of [7x joint velocities, 3x EE delta xyz, 3x EE delta rpy, 1x gripper position, 1x terminate episode].
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/depth	Tensor	(128, 128, 1)	int32	Right camera depth observation.
steps/observation/depth_additional_view	Tensor	(128, 128, 1)	int32	Left camera depth observation.
steps/observation/image	Image	(128, 128, 3)	uint8	Right camera RGB observation.
steps/observation/image_additional_view	Image	(128, 128, 3)	uint8	Left camera RGB observation.
steps/observation/state	Tensor	(13,)	float32	Robot state, consists of [7x robot joint angles, 3x EE xyz, 3x EE rpy.
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:

@article{cui2022play,
  title   = {From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data},
  author  = {Cui, Zichen Jeff and Wang, Yibin and Shafiullah, Nur Muhammad Mahi and Pinto, Lerrel},
  journal = {arXiv preprint arXiv:2210.10047},
  year    = {2022}
}