austin_sirius_dataset_converted_externally_to_rlds

  • Keterangan :

Tugas manipulasi meja Franka

Membelah Contoh
'train' 559
  • Struktur fitur :
FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    }),
    'steps': Dataset({
        'action': Tensor(shape=(7,), dtype=float32, description=Robot action, consists of [3x ee relative pos, 3x ee relative rotation, 1x gripper action].),
        'action_mode': Tensor(shape=(1,), dtype=float32, description=Type of interaction. -1: initial human demonstration. 1: intervention. 0: autonomuos robot execution (includes pre-intervention class)),
        'discount': Scalar(shape=(), dtype=float32, description=Discount if provided, default to 1.),
        'intv_label': Tensor(shape=(1,), dtype=float32, description=Same as action_modes, except 15 timesteps preceding intervention are labeled as -10.),
        '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({
            'image': Image(shape=(84, 84, 3), dtype=uint8, description=Main camera RGB observation.),
            'state': Tensor(shape=(8,), dtype=float32, description=Default robot state, consists of [7x robot joint state, 1x gripper state].),
            'state_ee': Tensor(shape=(16,), dtype=float32, description=End-effector state, represented as 4x4 homogeneous transformation matrix of ee pose.),
            'state_gripper': Tensor(shape=(1,), dtype=float32, description=Robot gripper opening width. Ranges between ~0 (closed) to ~0.077 (open)),
            'state_joint': Tensor(shape=(7,), dtype=float32, description=Robot 7-dof joint information.),
            'wrist_image': Image(shape=(84, 84, 3), dtype=uint8, description=Wrist camera RGB observation.),
        }),
        '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 (7,) float32 Aksi robot, terdiri dari [3x ee pos relatif, 3x ee rotasi relatif, 1x aksi gripper].
langkah/mode_aksi Tensor (1,) float32 Jenis interaksi. -1: demonstrasi awal manusia. 1: intervensi. 0: eksekusi robot autonomuos (termasuk kelas pra-intervensi)
langkah/diskon Skalar float32 Diskon jika disediakan, defaultnya adalah 1.
langkah/intv_label Tensor (1,) float32 Sama seperti action_modes, kecuali 15 langkah waktu sebelum intervensi diberi label -10.
langkah/adalah_pertama Tensor bodoh
langkah/adalah_terakhir Tensor bodoh
langkah/is_terminal Tensor bodoh
langkah/bahasa_penyematan 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/gambar Gambar (84, 84, 3) uint8 Pengamatan RGB kamera utama.
langkah/pengamatan/keadaan Tensor (8,) float32 Status robot default, terdiri dari [7x status sambungan robot, 1x status gripper].
langkah/pengamatan/state_ee Tensor (16,) float32 Keadaan efektor akhir, direpresentasikan sebagai matriks transformasi homogen 4x4 dari pose ee.
langkah/pengamatan/state_gripper Tensor (1,) float32 Lebar bukaan gripper robot. Berkisar antara ~0 (tertutup) hingga ~0,077 (terbuka)
langkah/pengamatan/state_joint Tensor (7,) float32 Informasi gabungan Robot 7-dof.
langkah/pengamatan/wrist_image Gambar (84, 84, 3) uint8 Pengamatan RGB kamera pergelangan tangan.
langkah/hadiah Skalar float32 Hadiah jika diberikan, 1 pada langkah terakhir untuk demo.
  • Kutipan :
@inproceedings{liu2022robot,
    title = {Robot Learning on the Job: Human-in-the-Loop Autonomy and Learning During Deployment},
    author = {Huihan Liu and Soroush Nasiriany and Lance Zhang and Zhiyao Bao and Yuke Zhu},
    booktitle = {Robotics: Science and Systems (RSS)},
    year = {2023}
}