iamlab_cmu_pickup_insert_converted_externally_to_rlds

• Description:

Franka picking objects and insertion tasks

• Homepage: https://openreview.net/forum?id=WuBv9-IGDUA

• Source code: tfds.robotics.rtx.IamlabCmuPickupInsertConvertedExternallyToRlds

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 50.29 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'train'	631

• Feature structure:

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    }),
    'steps': Dataset({
        'action': Tensor(shape=(8,), dtype=float32, description=Robot action, consists of [3x end-effector position, 4x end-effector quaternion, 1x gripper open/close].),
        '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=(20,), dtype=float32, description=Robot state, consists of [7x robot joint angles, 1x gripper status, 6x joint torques, 6x end-effector force].),
            'wrist_image': Image(shape=(240, 320, 3), dtype=uint8, description=Wrist camera RGB observation.),
        }),
        '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	(8,)	float32	Robot action, consists of [3x end-effector position, 4x end-effector quaternion, 1x gripper open/close].
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	(360, 640, 3)	uint8	Main camera RGB observation.
steps/observation/state	Tensor	(20,)	float32	Robot state, consists of [7x robot joint angles, 1x gripper status, 6x joint torques, 6x end-effector force].
steps/observation/wrist_image	Image	(240, 320, 3)	uint8	Wrist camera RGB observation.
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{
saxena2023multiresolution,
title={Multi-Resolution Sensing for Real-Time Control with Vision-Language Models},
author={Saumya Saxena and Mohit Sharma and Oliver Kroemer},
booktitle={7th Annual Conference on Robot Learning},
year={2023},
url={https://openreview.net/forum?id=WuBv9-IGDUA}
}