columbia_cairlab_pusht_real

• Description:

UR5 planar pushing tasks

• Homepage: https://github.com/columbia-ai-robotics/diffusion_policy

• Source code: tfds.robotics.rtx.ColumbiaCairlabPushtReal

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 2.80 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'test'	14
'train'	122

• Feature structure:

FeaturesDict({
    'steps': Dataset({
        'action': FeaturesDict({
            'gripper_closedness_action': float32,
            'rotation_delta': Tensor(shape=(3,), dtype=float32, description=Delta change in roll, pitch, yaw.),
            'terminate_episode': float32,
            'world_vector': Tensor(shape=(3,), dtype=float32, description=Delta change in XYZ.),
        }),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'observation': FeaturesDict({
            'image': Image(shape=(240, 320, 3), dtype=uint8),
            'natural_language_embedding': Tensor(shape=(512,), dtype=float32),
            'natural_language_instruction': string,
            'robot_state': Tensor(shape=(2,), dtype=float32, description=Robot end effector XY state),
            'wrist_image': Image(shape=(240, 320, 3), dtype=uint8),
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
steps	Dataset
steps/action	FeaturesDict
steps/action/gripper_closedness_action	Tensor		float32	1 if close gripper, -1 if open gripper, 0 if no change.
steps/action/rotation_delta	Tensor	(3,)	float32	Delta change in roll, pitch, yaw.
steps/action/terminate_episode	Tensor		float32
steps/action/world_vector	Tensor	(3,)	float32	Delta change in XYZ.
steps/is_first	Tensor		bool
steps/is_last	Tensor		bool
steps/is_terminal	Tensor		bool
steps/observation	FeaturesDict
steps/observation/image	Image	(240, 320, 3)	uint8
steps/observation/natural_language_embedding	Tensor	(512,)	float32
steps/observation/natural_language_instruction	Tensor		string
steps/observation/robot_state	Tensor	(2,)	float32	Robot end effector XY state
steps/observation/wrist_image	Image	(240, 320, 3)	uint8
steps/reward	Scalar		float32

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@inproceedings{chi2023diffusionpolicy,
    title={Diffusion Policy: Visuomotor Policy Learning via Action Diffusion},
    author={Chi, Cheng and Feng, Siyuan and Du, Yilun and Xu, Zhenjia and Cousineau, Eric and Burchfiel, Benjamin and Song, Shuran},
    booktitle={Proceedings of Robotics: Science and Systems (RSS)},
    year={2023}
}