dlr_edan_shared_control_converted_externally_to_rlds

• Description:

wheelchair with arm performing shelf pick tasks

• Homepage: https://ieeexplore.ieee.org/document/9341156

• Source code: tfds.robotics.rtx.DlrEdanSharedControlConvertedExternallyToRlds

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 3.09 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'train'	104

• 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 EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class].),
        '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=(360, 640, 3), dtype=uint8, description=Main camera RGB observation.),
            'state': Tensor(shape=(7,), dtype=float32, description=Robot state, consists of [3x robot EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class].),
        }),
        '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 EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class].
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	Pour into the mug.
steps/observation	FeaturesDict
steps/observation/image	Image	(360, 640, 3)	uint8	Main camera RGB observation.
steps/observation/state	Tensor	(7,)	float32	Robot state, consists of [3x robot EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class].
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{vogel_edan_2020,
    title = {EDAN - an EMG-Controlled Daily Assistant to Help People with Physical Disabilities},
    language = {en},
    booktitle = {2020 {IEEE}/{RSJ} {International} {Conference} on {Intelligent} {Robots} and {Systems} ({IROS})},
    author = {Vogel, Jörn and Hagengruber, Annette and Iskandar, Maged and Quere, Gabriel and Leipscher, Ulrike and Bustamante, Samuel and Dietrich, Alexander and Hoeppner, Hannes and Leidner, Daniel and Albu-Schäffer, Alin},
    year = {2020}
}
@inproceedings{quere_shared_2020,
    address = {Paris, France},
    title = {Shared {Control} {Templates} for {Assistive} {Robotics} },
    language = {en},
    booktitle = {2020 {IEEE} {International} {Conference} on {Robotics} and {Automation} ({ICRA})},
    author = {Quere, Gabriel and Hagengruber, Annette and Iskandar, Maged and Bustamante, Samuel and Leidner, Daniel and Stulp, Freek and Vogel, Joern},
    year = {2020},
    pages = {7},
}