<br />

- **Description**:

xArm picking and placing objects with distractors

- **Homepage** : <https://owmcorl.github.io>

- **Source code** :
  [`tfds.robotics.rtx.UcsdPickAndPlaceDatasetConvertedExternallyToRlds`](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** : `3.53 GiB`

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

- **Splits**:

| Split | Examples |
|---|---|
| `'train'` | 1,355 |

- **Feature structure**:

    FeaturesDict({
        'episode_metadata': FeaturesDict({
            'disclaimer': Text(shape=(), dtype=string),
            'file_path': Text(shape=(), dtype=string),
            'n_transitions': Scalar(shape=(), dtype=int32, description=Number of transitions in the episode.),
            'success': Scalar(shape=(), dtype=bool, description=True if the last state of an episode is a success state, False otherwise.),
            'success_labeled_by': Text(shape=(), dtype=string),
        }),
        'steps': Dataset({
            'action': Tensor(shape=(4,), dtype=float32, description=Robot action, consists of [3x gripper velocities,1x gripper open/close torque].),
            'discount': Scalar(shape=(), dtype=float32, 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=(224, 224, 3), dtype=uint8, description=Camera RGB observation.),
                'state': Tensor(shape=(7,), dtype=float32, description=Robot state, consists of [3x gripper position,3x gripper orientation, 1x finger distance].),
            }),
            '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/disclaimer | Text |   | string | Disclaimer about the particular episode. |
| episode_metadata/file_path | Text |   | string | Path to the original data file. |
| episode_metadata/n_transitions | Scalar |   | int32 | Number of transitions in the episode. |
| episode_metadata/success | Scalar |   | bool | True if the last state of an episode is a success state, False otherwise. |
| episode_metadata/success_labeled_by | Text |   | string | Who labeled success (and thereby reward) of the episode. Can be one of: \[human, classifier\]. |
| steps | Dataset |   |   |   |
| steps/action | Tensor | (4,) | float32 | Robot action, consists of \[3x gripper velocities,1x gripper open/close torque\]. |
| steps/discount | Scalar |   | float32 | Discount if provided, default to 1. |
| 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 | (224, 224, 3) | uint8 | Camera RGB observation. |
| steps/observation/state | Tensor | (7,) | float32 | Robot state, consists of \[3x gripper position,3x gripper orientation, 1x finger distance\]. |
| 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/ucsd_pick_and_place_dataset_converted_externally_to_rlds_ab2a6588fa78078a9a9dfb686153bc451a4a22fc7d756b63447d8c1ef9dbe3ec.frame" class="framebox inherit-locale " allow="clipboard-write https://" allowfullscreen is-upgraded></iframe>

- **Citation**:

    @preprint{Feng2023Finetuning,
        title={Finetuning Offline World Models in the Real World},
        author={Yunhai Feng, Nicklas Hansen, Ziyan Xiong, Chandramouli Rajagopalan, Xiaolong Wang},
        year={2023}
    }