<br />

- **Description**:

wheelchair with arm performing shelf pick tasks

- **Homepage** :
  <https://ieeexplore.ieee.org/document/9341156>

- **Source code** :
  [`tfds.robotics.rtx.DlrEdanSharedControlConvertedExternallyToRlds`](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** : `3.09 GiB`

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

- **Splits**:

| Split | Examples |
|---|---|
| `'train'` | 104 |

- **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 robot EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class].),
            '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=(360, 640, 3), dtype=uint8, description=Main camera RGB observation.),
                'state': Tensor(shape=(7,), dtype=float32, description=Robot state, consists of [3x robot EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class].),
            }),
            '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 \[3x robot EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class\]. |
| 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 | Pour into the mug. |
| steps/observation | FeaturesDict |   |   |   |
| steps/observation/image | Image | (360, 640, 3) | uint8 | Main camera RGB observation. |
| steps/observation/state | Tensor | (7,) | float32 | Robot state, consists of \[3x robot EEF position, 3x robot EEF orientation yaw/pitch/roll calculated with scipy Rotation.as_euler(="zxy") Class\]. |
| 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/dlr_edan_shared_control_converted_externally_to_rlds_ceedfb062acfde138a0f8fb8ef8a39658da15c4c3ae9aaef8a879b39c115bee4.frame" class="framebox inherit-locale " allow="clipboard-write https://" allowfullscreen is-upgraded></iframe>

- **Citation**:

    @inproceedings{vogel_edan_2020,
        title = {EDAN - an EMG-Controlled Daily Assistant to Help People with Physical Disabilities},
        language = {en},
        booktitle = {2020 {IEEE}/{RSJ} {International} {Conference} on {Intelligent} {Robots} and {Systems} ({IROS})},
        author = {Vogel, Jörn and Hagengruber, Annette and Iskandar, Maged and Quere, Gabriel and Leipscher, Ulrike and Bustamante, Samuel and Dietrich, Alexander and Hoeppner, Hannes and Leidner, Daniel and Albu-Schäffer, Alin},
        year = {2020}
    }
    @inproceedings{quere_shared_2020,
        address = {Paris, France},
        title = {Shared {Control} {Templates} for {Assistive} {Robotics} },
        language = {en},
        booktitle = {2020 {IEEE} {International} {Conference} on {Robotics} and {Automation} ({ICRA})},
        author = {Quere, Gabriel and Hagengruber, Annette and Iskandar, Maged and Bustamante, Samuel and Leidner, Daniel and Stulp, Freek and Vogel, Joern},
        year = {2020},
        pages = {7},
    }