berkeley_mvp_converted_externally_to_rlds

• Keterangan :

xArm melakukan 6 tugas manipulasi

• Beranda : https://arxiv.org/abs/2203.06173

• Kode sumber : tfds.robotics.rtx.BerkeleyMvpConvertedExternallyToRlds

• Versi :

  • 0.1.0 (default): Rilis awal.

• Ukuran unduhan : Unknown size

• Ukuran kumpulan data : 12.34 GiB

• Cache otomatis ( dokumentasi ): Tidak

• Perpecahan :

• Struktur fitur :

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    }),
    'steps': Dataset({
        'action': Tensor(shape=(8,), dtype=float32, description=Robot action, consists of [7 delta joint pos,1x gripper binary state].),
        '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({
            'gripper': Scalar(shape=(), dtype=bool, description=Binary gripper state (1 - closed, 0 - open)),
            'hand_image': Image(shape=(480, 640, 3), dtype=uint8, description=Hand camera RGB observation.),
            'joint_pos': Tensor(shape=(7,), dtype=float32, description=xArm joint positions (7 DoF).),
            'pose': Tensor(shape=(7,), dtype=float32, description=Gripper pose, robot frame, [3 position, 4 rotation]),
        }),
        'reward': Scalar(shape=(), dtype=float32, description=Reward if provided, 1 on final step for demos.),
    }),
})

• Dokumentasi fitur :

• Kunci yang diawasi (Lihat dokumen as_supervised ): None

• Gambar ( tfds.show_examples ): Tidak didukung.

• Contoh ( tfds.as_dataframe ):

• Kutipan :

@InProceedings{Radosavovic2022,
  title = {Real-World Robot Learning with Masked Visual Pre-training},
  author = {Ilija Radosavovic and Tete Xiao and Stephen James and Pieter Abbeel and Jitendra Malik and Trevor Darrell},
  booktitle = {CoRL},
  year = {2022}
}