berkeley_fanuc_manipulation

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    }),
    'steps': Dataset({
        'action': Tensor(shape=(6,), dtype=float32, description=Robot action, consists of [dx, dy, dz] and [droll, dpitch, dyaw]),
        '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({
            'end_effector_state': Tensor(shape=(7,), dtype=float32, description=Robot gripper end effector state, consists of [x, y, z] and 4x quaternion),
            'image': Image(shape=(224, 224, 3), dtype=uint8, description=Main camera RGB observation.),
            'state': Tensor(shape=(13,), dtype=float32, description=Robot joints state, consists of [6x robot joint angles, 1x gripper open status, 6x robot joint velocities].),
            'wrist_image': Image(shape=(224, 224, 3), dtype=uint8, description=Wrist camera RGB observation.),
        }),
        'reward': Scalar(shape=(), dtype=float32, description=Reward if provided, 1 on final step for demos.),
    }),
})

@article{fanuc_manipulation2023,
  title={Fanuc Manipulation: A Dataset for Learning-based Manipulation with FANUC Mate 200iD Robot},
  author={Zhu, Xinghao and Tian, Ran and Xu, Chenfeng and Ding, Mingyu and Zhan, Wei and Tomizuka, Masayoshi},
  year={2023},
}