<br />

- **Description**:

Franka tabletop manipulation tasks

- **Homepage** :
  <https://ut-austin-rpl.github.io/sirius/>

- **Source code** :
  [`tfds.robotics.rtx.AustinSiriusDatasetConvertedExternallyToRlds`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/robotics/rtx/rtx.py)

- **Versions**:

  - **`0.1.0`** (default): Initial release.
- **Download size** : `Unknown size`

- **Dataset size** : `6.55 GiB`

- **Auto-cached**
  ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):
  No

- **Splits**:

| Split | Examples |
|---|---|
| `'train'` | 559 |

- **Feature structure**:

    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.),
        }),
    })

- **Feature documentation**:

| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
|   | FeaturesDict |   |   |   |
| episode_metadata | FeaturesDict |   |   |   |
| episode_metadata/file_path | Text |   | string | Path to the original data file. |
| steps | Dataset |   |   |   |
| steps/action | Tensor | (7,) | float32 | Robot action, consists of \[3x ee relative pos, 3x ee relative rotation, 1x gripper action\]. |
| steps/action_mode | Tensor | (1,) | float32 | Type of interaction. -1: initial human demonstration. 1: intervention. 0: autonomuos robot execution (includes pre-intervention class) |
| steps/discount | Scalar |   | float32 | Discount if provided, default to 1. |
| steps/intv_label | Tensor | (1,) | float32 | Same as action_modes, except 15 timesteps preceding intervention are labeled as -10. |
| steps/is_first | Tensor |   | bool |   |
| steps/is_last | Tensor |   | bool |   |
| steps/is_terminal | Tensor |   | bool |   |
| steps/language_embedding | Tensor | (512,) | float32 | Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5 |
| steps/language_instruction | Text |   | string | Language Instruction. |
| steps/observation | FeaturesDict |   |   |   |
| steps/observation/image | Image | (84, 84, 3) | uint8 | Main camera RGB observation. |
| steps/observation/state | Tensor | (8,) | float32 | Default robot state, consists of \[7x robot joint state, 1x gripper state\]. |
| steps/observation/state_ee | Tensor | (16,) | float32 | End-effector state, represented as 4x4 homogeneous transformation matrix of ee pose. |
| steps/observation/state_gripper | Tensor | (1,) | float32 | Robot gripper opening width. Ranges between \~0 (closed) to \~0.077 (open) |
| steps/observation/state_joint | Tensor | (7,) | float32 | Robot 7-dof joint information. |
| steps/observation/wrist_image | Image | (84, 84, 3) | uint8 | Wrist camera RGB observation. |
| steps/reward | Scalar |   | float32 | Reward if provided, 1 on final step for demos. |

- **Supervised keys** (See
  [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
  `None`

- **Figure**
  ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):
  Not supported.

- **Examples**
  ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):

<iframe src="https:///frame/datasets/catalog/austin_sirius_dataset_converted_externally_to_rlds_f992f88291f5863c5cde62b9ce9133bc40ebd9aaaff4ffe5fb9e43faa06ddffa.frame" class="framebox inherit-locale " allow="clipboard-write https://" allowfullscreen is-upgraded></iframe>

- **Citation**:

    @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}
    }