• Description:

Franka tablesetting tasks

Split Examples
'train' 240
  • Feature structure:
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    'steps': Dataset({
        'action': Tensor(shape=(7,), dtype=float32),
        'discount': Scalar(shape=(), dtype=float32),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'language_embedding': Tensor(shape=(512,), dtype=float32),
        'language_instruction': Text(shape=(), dtype=string),
        'observation': FeaturesDict({
            'image': Image(shape=(128, 128, 3), dtype=uint8),
            'state': Tensor(shape=(8,), dtype=float32),
            'state_ee': Tensor(shape=(16,), dtype=float32),
            'state_gripper': Tensor(shape=(1,), dtype=float32),
            'state_joint': Tensor(shape=(7,), dtype=float32),
            'wrist_image': Image(shape=(128, 128, 3), dtype=uint8),
        'reward': Scalar(shape=(), dtype=float32),
  • Feature documentation:
Feature Class Shape Dtype Description
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 ee relative pos, 3x ee relative rotation, 1x gripper action].
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
steps/language_instruction Text string Language Instruction.
steps/observation FeaturesDict
steps/observation/image Image (128, 128, 3) uint8 Main camera RGB observation.
steps/observation/state Tensor (8,) float32 Default robot state, consists of [3x robot ee pos, 3x ee quat, 1x gripper state].
steps/observation/state_ee Tensor (16,) float32 End-effector state, represented as 4x4 homogeneous transformation matrix of ee pose.
steps/observation/state_gripper Tensor (1,) float32 Robot gripper opening width. Ranges between ~0 (closed) to ~0.077 (open)
steps/observation/state_joint Tensor (7,) float32 Robot 7-dof joint information (not used in original SAILOR dataset).
steps/observation/wrist_image Image (128, 128, 3) uint8 Wrist camera RGB observation.
steps/reward Scalar float32 True on last step of the episode.
  • Citation:
      title={Learning and Retrieval from Prior Data for Skill-based Imitation Learning},
      author={Soroush Nasiriany and Tian Gao and Ajay Mandlekar and Yuke Zhu},
      booktitle={Conference on Robot Learning (CoRL)},