toto

• Description:

Franka scooping and pouring tasks

• Homepage: https://toto-benchmark.org/

• Source code: tfds.robotics.rtx.Toto

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: Unknown size

• Auto-cached (documentation): Unknown

• Splits:

Split	Examples

• Feature structure:

FeaturesDict({
    'steps': Dataset({
        'action': FeaturesDict({
            'open_gripper': bool,
            'rotation_delta': Tensor(shape=(3,), dtype=float32),
            'terminate_episode': float32,
            'world_vector': Tensor(shape=(3,), dtype=float32),
        }),
        'is_first': bool,
        'is_last': bool,
        'is_terminal': bool,
        'observation': FeaturesDict({
            'image': Image(shape=(480, 640, 3), dtype=uint8),
            'natural_language_embedding': Tensor(shape=(512,), dtype=float32),
            'natural_language_instruction': string,
            'state': Tensor(shape=(7,), dtype=float32, description=numpy array of shape (7,). Contains the robot joint states (as absolute joint angles) at each timestep),
        }),
        'reward': Scalar(shape=(), dtype=float32),
    }),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
steps	Dataset
steps/action	FeaturesDict
steps/action/open_gripper	Tensor		bool
steps/action/rotation_delta	Tensor	(3,)	float32
steps/action/terminate_episode	Tensor		float32
steps/action/world_vector	Tensor	(3,)	float32
steps/is_first	Tensor		bool
steps/is_last	Tensor		bool
steps/is_terminal	Tensor		bool
steps/observation	FeaturesDict
steps/observation/image	Image	(480, 640, 3)	uint8
steps/observation/natural_language_embedding	Tensor	(512,)	float32
steps/observation/natural_language_instruction	Tensor		string
steps/observation/state	Tensor	(7,)	float32	numpy array of shape (7,). Contains the robot joint states (as absolute joint angles) at each timestep
steps/reward	Scalar		float32

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe): Missing.

• Citation:

@inproceedings{zhou2023train,
  author={Zhou, Gaoyue and Dean, Victoria and Srirama, Mohan Kumar and Rajeswaran, Aravind and Pari, Jyothish and Hatch, Kyle and Jain, Aryan and Yu, Tianhe and Abbeel, Pieter and Pinto, Lerrel and Finn, Chelsea and Gupta, Abhinav},
  booktitle={2023 IEEE International Conference on Robotics and Automation (ICRA)},
  title={Train Offline, Test Online: A Real Robot Learning Benchmark},
  year={2023},
 }