robo_set

• Description:

Real dataset of a single robot arm demonstrating 12 non-trivial manipulation skills across 38 tasks, 7500 trajectories.

• Homepage: https://robopen.github.io/

• Source code: tfds.robotics.rtx.RoboSet

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 179.42 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'train'	18,250

• Feature structure:

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': string,
        'trial_id': string,
    }),
    'steps': Dataset({
        'action': Tensor(shape=(8,), dtype=float32),
        'discount': Scalar(shape=(), dtype=float32),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'language_instruction': string,
        'observation': FeaturesDict({
            'image_left': Image(shape=(240, 424, 3), dtype=uint8),
            'image_right': Image(shape=(240, 424, 3), dtype=uint8),
            'image_top': Image(shape=(240, 424, 3), dtype=uint8),
            'image_wrist': Image(shape=(240, 424, 3), dtype=uint8),
            'state': Tensor(shape=(8,), dtype=float32),
            'state_velocity': Tensor(shape=(8,), dtype=float32),
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
episode_metadata	FeaturesDict
episode_metadata/file_path	Tensor		string
episode_metadata/trial_id	Tensor		string
steps	Dataset
steps/action	Tensor	(8,)	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/image_left	Image	(240, 424, 3)	uint8
steps/observation/image_right	Image	(240, 424, 3)	uint8
steps/observation/image_top	Image	(240, 424, 3)	uint8
steps/observation/image_wrist	Image	(240, 424, 3)	uint8
steps/observation/state	Tensor	(8,)	float32
steps/observation/state_velocity	Tensor	(8,)	float32
steps/reward	Scalar		float32

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@misc{bharadhwaj2023roboagent, title={RoboAgent: Generalization and Efficiency in Robot Manipulation via Semantic Augmentations and Action Chunking}, author={Homanga Bharadhwaj and Jay Vakil and Mohit Sharma and Abhinav Gupta and Shubham Tulsiani and Vikash Kumar},  year={2023}, eprint={2309.01918}, archivePrefix={arXiv}, primaryClass={cs.RO} }