dlr_sara_pour_converted_externally_to_rlds

  • Description:

pouring liquid from a bottle into a mug

Split Examples
'train' 100
  • 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=(480, 640, 3), dtype=uint8, description=Main camera RGB observation.),
            'state': Tensor(shape=(6,), 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 (480, 640, 3) uint8 Main camera RGB observation.
steps/observation/state Tensor (6,) 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.
  • Citation:
@inproceedings{padalkar2023guiding,
  title={Guiding Reinforcement Learning with Shared Control Templates},
  author={Padalkar, Abhishek and Quere, Gabriel and Steinmetz, Franz and Raffin, Antonin and Nieuwenhuisen, Matthias and Silv{\'e}rio, Jo{\~a}o and Stulp, Freek},
  booktitle={40th IEEE International Conference on Robotics and Automation, ICRA 2023},
  year={2023},
  organization={IEEE}
}