spoc_robot

• Description:

• Homepage: https://spoc-robot.github.io/

• Source code: tfds.robotics.rtx.SpocRobot

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 771.61 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'train'	212,043
'val'	21,108

• Feature structure:

FeaturesDict({
    'episode_metadata': FeaturesDict({
        'file_path': string,
        'task_target_split': string,
        'task_type': string,
    }),
    'steps': Dataset({
        'action': Tensor(shape=(9,), dtype=float32),
        'discount': Scalar(shape=(), dtype=float32),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'language_instruction': string,
        'observation': FeaturesDict({
            'an_object_is_in_hand': Scalar(shape=(), dtype=bool),
            'house_index': Scalar(shape=(), dtype=int64),
            'hypothetical_task_success': Scalar(shape=(), dtype=bool),
            'image': Image(shape=(224, 384, 3), dtype=uint8),
            'image_manipulation': Image(shape=(224, 384, 3), dtype=uint8),
            'last_action_is_random': Scalar(shape=(), dtype=bool),
            'last_action_str': string,
            'last_action_success': Scalar(shape=(), dtype=bool),
            'last_agent_location': Tensor(shape=(6,), dtype=float32),
            'manip_object_bbox': Tensor(shape=(10,), dtype=float32),
            'minimum_l2_target_distance': Scalar(shape=(), dtype=float32),
            'minimum_visible_target_alignment': Scalar(shape=(), dtype=float32),
            'nav_object_bbox': Tensor(shape=(10,), dtype=float32),
            'relative_arm_location_metadata': Tensor(shape=(4,), dtype=float32),
            'room_current_seen': Scalar(shape=(), dtype=bool),
            'rooms_seen': Scalar(shape=(), dtype=int64),
            'visible_target_4m_count': Scalar(shape=(), dtype=int64),
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
episode_metadata	FeaturesDict
episode_metadata/file_path	Tensor		string
episode_metadata/task_target_split	Tensor		string
episode_metadata/task_type	Tensor		string
steps	Dataset
steps/action	Tensor	(9,)	float32
steps/discount	Scalar		float32
steps/is_first	Tensor		bool
steps/is_last	Tensor		bool
steps/is_terminal	Tensor		bool
steps/language_instruction	Tensor		string
steps/observation	FeaturesDict
steps/observation/an_object_is_in_hand	Scalar		bool
steps/observation/house_index	Scalar		int64
steps/observation/hypothetical_task_success	Scalar		bool
steps/observation/image	Image	(224, 384, 3)	uint8
steps/observation/image_manipulation	Image	(224, 384, 3)	uint8
steps/observation/last_action_is_random	Scalar		bool
steps/observation/last_action_str	Tensor		string
steps/observation/last_action_success	Scalar		bool
steps/observation/last_agent_location	Tensor	(6,)	float32
steps/observation/manip_object_bbox	Tensor	(10,)	float32
steps/observation/minimum_l2_target_distance	Scalar		float32
steps/observation/minimum_visible_target_alignment	Scalar		float32
steps/observation/nav_object_bbox	Tensor	(10,)	float32
steps/observation/relative_arm_location_metadata	Tensor	(4,)	float32
steps/observation/room_current_seen	Scalar		bool
steps/observation/rooms_seen	Scalar		int64
steps/observation/visible_target_4m_count	Scalar		int64
steps/reward	Scalar		float32

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@article{spoc2023,
    author    = {Kiana Ehsani, Tanmay Gupta, Rose Hendrix, Jordi Salvador, Luca Weihs, Kuo-Hao Zeng, Kunal Pratap Singh, Yejin Kim, Winson Han, Alvaro Herrasti, Ranjay Krishna, Dustin Schwenk, Eli VanderBilt, Aniruddha Kembhavi},
    title     = {Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World},
    journal   = {arXiv},
    year      = {2023},
    eprint    = {2312.02976},
}