nyu_franka_play_dataset_converted_externally_to_rlds

  • Keterangan :

Franka berinteraksi dengan dapur mainan

Membelah Contoh
'train' 365
'val' 91
  • Struktur fitur :
FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    }),
    'steps': Dataset({
        'action': Tensor(shape=(15,), dtype=float32, description=Robot action, consists of [7x joint velocities, 3x EE delta xyz, 3x EE delta rpy, 1x gripper position, 1x terminate episode].),
        '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({
            'depth': Tensor(shape=(128, 128, 1), dtype=int32, description=Right camera depth observation.),
            'depth_additional_view': Tensor(shape=(128, 128, 1), dtype=int32, description=Left camera depth observation.),
            'image': Image(shape=(128, 128, 3), dtype=uint8, description=Right camera RGB observation.),
            'image_additional_view': Image(shape=(128, 128, 3), dtype=uint8, description=Left camera RGB observation.),
            'state': Tensor(shape=(13,), dtype=float32, description=Robot state, consists of [7x robot joint angles, 3x EE xyz, 3x EE rpy.),
        }),
        'reward': Scalar(shape=(), dtype=float32, description=Reward if provided, 1 on final step for demos.),
    }),
})
  • Dokumentasi fitur :
Fitur Kelas Membentuk Tipe D Keterangan
FiturDict
episode_metadata FiturDict
episode_metadata/file_path Teks rangkaian Jalur ke file data asli.
tangga Kumpulan data
langkah/tindakan Tensor (15,) float32 Aksi robot, terdiri dari [7x kecepatan sendi, 3x EE delta xyz, 3x EE delta rpy, 1x posisi gripper, 1x episode penghentian].
langkah/diskon Skalar float32 Diskon jika disediakan, defaultnya adalah 1.
langkah/adalah_pertama Tensor bodoh
langkah/adalah_terakhir Tensor bodoh
langkah/is_terminal Tensor bodoh
langkah/bahasa_embedding Tensor (512,) float32 Penyematan bahasa Kona. Lihat https://tfhub.dev/google/universal-sentence-encoder-large/5
langkah/bahasa_instruksi Teks rangkaian Instruksi Bahasa.
langkah/pengamatan FiturDict
langkah/pengamatan/kedalaman Tensor (128, 128, 1) int32 Pengamatan kedalaman kamera kanan.
langkah/pengamatan/kedalaman_tambahan_tampilan Tensor (128, 128, 1) int32 Pengamatan kedalaman kamera kiri.
langkah/pengamatan/gambar Gambar (128, 128, 3) uint8 Pengamatan RGB kamera kanan.
langkah/pengamatan/gambar_tambahan_tampilan Gambar (128, 128, 3) uint8 Pengamatan RGB kamera kiri.
langkah/pengamatan/keadaan Tensor (13,) float32 Keadaan robot, terdiri dari [7x sudut sambungan robot, 3x EE xyz, 3x EE rpy.
langkah/hadiah Skalar float32 Hadiah jika diberikan, 1 pada langkah terakhir untuk demo.
  • Kutipan :
@article{cui2022play,
  title   = {From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data},
  author  = {Cui, Zichen Jeff and Wang, Yibin and Shafiullah, Nur Muhammad Mahi and Pinto, Lerrel},
  journal = {arXiv preprint arXiv:2210.10047},
  year    = {2022}
}