berkeley_gnm_sac_son

• Descrizione :

navigazione in ufficio

• Home page : https://sites.google.com/view/SACSoN-review

• Codice sorgente : tfds.robotics.rtx.BerkeleyGnmSacSon

• Versioni :

  • 0.1.0 (predefinito): versione iniziale.

• Dimensioni del download : Unknown size

• Dimensione del set di dati : 7.00 GiB

• Memorizzazione nella cache automatica ( documentazione ): No

• Divide :

• Struttura delle caratteristiche :

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': Text(shape=(), dtype=string),
    }),
    'steps': Dataset({
        'action': Tensor(shape=(2,), dtype=float64, description=Robot action, consists of 2x position),
        'action_angle': Tensor(shape=(3,), dtype=float64, description=Robot action, consists of 2x position, 1x yaw),
        'discount': Scalar(shape=(), dtype=float64, 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({
            'image': Image(shape=(120, 160, 3), dtype=uint8, description=Main camera RGB observation.),
            'position': Tensor(shape=(2,), dtype=float64, description=Robot position),
            'state': Tensor(shape=(3,), dtype=float64, description=Robot state, consists of [2x position, 1x yaw]),
            'yaw': Tensor(shape=(1,), dtype=float64, description=Robot yaw),
        }),
        'reward': Scalar(shape=(), dtype=float64, description=Reward if provided, 1 on final step for demos.),
    }),
})

• Documentazione delle funzionalità :

• Chiavi supervisionate (vedi il documento as_supervised ): None

• Figura ( tfds.show_examples ): non supportato.

• Esempi ( tfds.as_dataframe ):

• Citazione :

@article{hirose2023sacson,
  title={SACSoN: Scalable Autonomous Data Collection for Social Navigation},
  author={Hirose, Noriaki and Shah, Dhruv and Sridhar, Ajay and Levine, Sergey},
  journal={arXiv preprint arXiv:2306.01874},
  year={2023}
}