nyu_pintu_pembukaan_keefektifan_mengejutkan

  • Keterangan :

Halo robot pembuka lemari, microwave, dll

Membelah Contoh
'test' 49
'train' 435
  • Struktur fitur :
FeaturesDict({
    'steps': Dataset({
        'action': FeaturesDict({
            'gripper_closedness_action': Tensor(shape=(1,), dtype=float32),
            'rotation_delta': Tensor(shape=(3,), dtype=float32, description=Angular velocity around x, y and z axis.),
            'terminate_episode': float32,
            'world_vector': Tensor(shape=(3,), dtype=float32, description=Velocity in XYZ.),
        }),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'observation': FeaturesDict({
            'image': Image(shape=(720, 960, 3), dtype=uint8),
            'natural_language_embedding': Tensor(shape=(512,), dtype=float32),
            'natural_language_instruction': string,
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})
  • Dokumentasi fitur :
Fitur Kelas Membentuk Tipe D Keterangan
FiturDict
tangga Kumpulan data
langkah/tindakan FiturDict
langkah/tindakan/gripper_closedness_action Tensor (1,) float32
langkah/tindakan/rotasi_delta Tensor (3,) float32 Kecepatan sudut di sekitar sumbu x, y dan z.
langkah/tindakan/terminate_episode Tensor float32
langkah/tindakan/world_vector Tensor (3,) float32 Kecepatan dalam XYZ.
langkah/adalah_pertama Tensor bodoh
langkah/adalah_terakhir Tensor bodoh
langkah/is_terminal Tensor bodoh
langkah/pengamatan FiturDict
langkah/pengamatan/gambar Gambar (720, 960, 3) uint8
langkah/pengamatan/penyematan_bahasa_alami Tensor (512,) float32
langkah/pengamatan/instruksi_bahasa_alami Tensor rangkaian
langkah/hadiah Skalar float32
  • Kutipan :
@misc{pari2021surprising,
    title={The Surprising Effectiveness of Representation Learning for Visual Imitation},
    author={Jyothish Pari and Nur Muhammad Shafiullah and Sridhar Pandian Arunachalam and Lerrel Pinto},
    year={2021},
    eprint={2112.01511},
    archivePrefix={arXiv},
    primaryClass={cs.RO}
}