nyu_door_opening_surprising_effectiveness

  • Description:

Hello robot opening cabinets, microwaves etc

Split Examples
'test' 49
'train' 435
  • Feature structure:
FeaturesDict({
    'steps': Dataset({
        'action': FeaturesDict({
            'gripper_closedness_action': Tensor(shape=(1,), dtype=float32),
            'rotation_delta': Tensor(shape=(3,), dtype=float32, description=Angular velocity around x, y and z axis.),
            'terminate_episode': float32,
            'world_vector': Tensor(shape=(3,), dtype=float32, description=Velocity in XYZ.),
        }),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'observation': FeaturesDict({
            'image': Image(shape=(720, 960, 3), dtype=uint8),
            'natural_language_embedding': Tensor(shape=(512,), dtype=float32),
            'natural_language_instruction': string,
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
steps Dataset
steps/action FeaturesDict
steps/action/gripper_closedness_action Tensor (1,) float32
steps/action/rotation_delta Tensor (3,) float32 Angular velocity around x, y and z axis.
steps/action/terminate_episode Tensor float32
steps/action/world_vector Tensor (3,) float32 Velocity in XYZ.
steps/is_first Tensor bool
steps/is_last Tensor bool
steps/is_terminal Tensor bool
steps/observation FeaturesDict
steps/observation/image Image (720, 960, 3) uint8
steps/observation/natural_language_embedding Tensor (512,) float32
steps/observation/natural_language_instruction Tensor string
steps/reward Scalar float32
  • Citation:
@misc{pari2021surprising,
    title={The Surprising Effectiveness of Representation Learning for Visual Imitation},
    author={Jyothish Pari and Nur Muhammad Shafiullah and Sridhar Pandian Arunachalam and Lerrel Pinto},
    year={2021},
    eprint={2112.01511},
    archivePrefix={arXiv},
    primaryClass={cs.RO}
}