berkeley_autolab_ur5

  • Description:

UR5 performing cloth manipulation, pick place etc tasks

Split Examples
'test' 104
'train' 896
  • 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({
            'hand_image': Image(shape=(480, 640, 3), dtype=uint8),
            'image': Image(shape=(480, 640, 3), dtype=uint8),
            'image_with_depth': Image(shape=(480, 640, 1), dtype=float32),
            'natural_language_embedding': Tensor(shape=(512,), dtype=float32),
            'natural_language_instruction': string,
            'robot_state': Tensor(shape=(15,), dtype=float32, description=Explanation of the robot state can be found at https://sites.google.com/corp/view/berkeley-ur5),
        }),
        '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/hand_image Image (480, 640, 3) uint8
steps/observation/image Image (480, 640, 3) uint8
steps/observation/image_with_depth Image (480, 640, 1) float32
steps/observation/natural_language_embedding Tensor (512,) float32
steps/observation/natural_language_instruction Tensor string
steps/observation/robot_state Tensor (15,) float32 Explanation of the robot state can be found at https://sites.google.com/corp/view/berkeley-ur5
steps/reward Scalar float32
  • Citation:
@misc{BerkeleyUR5Website,
  title = {Berkeley {UR5} Demonstration Dataset},
  author = {Lawrence Yunliang Chen and Simeon Adebola and Ken Goldberg},
  howpublished = {https://sites.google.com/view/berkeley-ur5/home},
}