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license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- TeleXperience
- DualArxR5a
- teleoperation
- dual-arm
- wipe-table
- living-room
configs:
- config_name: default
data_files: data/*/*.parquet
---
This dataset was created using [LeRobot](https://github.com/huggingface/lerobot).
<a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=io-intelligence/WipeTable_DualArxR5a_TeleXperience">
<img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/>
<img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl-dark.svg"/>
</a>
## Dataset Description
73 real-robot teleoperation episodes for **“Wipe the table.”** on a **DualArxR5a** dual-arm robot. Format: [LeRobot](https://github.com/huggingface/lerobot) **v3.0** (30 Hz parquet + H.264 videos).
Collected with **[TeleXperience](https://io-ai.tech/en/telexperience/)**, IO-AI’s product for real-robot teleoperation and data collection.
- **Task / language prompt:** `Wipe the table.`
- **Robot:** DualArxR5a (bimanual, parallel-jaw grippers)
- **Frames:** 629523 at 30 Hz
- **Cameras:** `camera_high` (overhead), `camera_low` (lower scene), `camera_left_wrist`, `camera_right_wrist`
- **Action / state:** 14-D, same names and order: `left_joint1–6`, `right_joint1–6`, `right_gripper`, `left_gripper` (grippers in `[0, 1]`)
- **Homepage:** https://io-ai.tech/en/telexperience/
- **Paper:** none
- **License:** apache-2.0
## Dataset Structure
[meta/info.json](meta/info.json):
```json
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float64",
"names": [
"left_joint1",
"left_joint2",
"left_joint3",
"left_joint4",
"left_joint5",
"left_joint6",
"right_joint1",
"right_joint2",
"right_joint3",
"right_joint4",
"right_joint5",
"right_joint6",
"right_gripper",
"left_gripper"
],
"shape": [
14
]
},
"episode_index": {
"dtype": "int64",
"shape": [
1
]
},
"frame_index": {
"dtype": "int64",
"shape": [
1
]
},
"index": {
"dtype": "int64",
"shape": [
1
]
},
"observation.images.camera_high": {
"dtype": "video",
"info": {
"has_audio": false,
"video.channels": 3,
"video.codec": "h264",
"video.fps": 30,
"video.height": 480,
"video.is_depth_map": false,
"video.pix_fmt": "yuv420p",
"video.width": 640
},
"names": [
"height",
"width",
"channels"
],
"shape": [
480,
640,
3
]
},
"observation.images.camera_left_wrist": {
"dtype": "video",
"info": {
"has_audio": false,
"video.channels": 3,
"video.codec": "h264",
"video.fps": 30,
"video.height": 480,
"video.is_depth_map": false,
"video.pix_fmt": "yuv420p",
"video.width": 640
},
"names": [
"height",
"width",
"channels"
],
"shape": [
480,
640,
3
]
},
"observation.images.camera_low": {
"dtype": "video",
"info": {
"has_audio": false,
"video.channels": 3,
"video.codec": "h264",
"video.fps": 30,
"video.height": 480,
"video.is_depth_map": false,
"video.pix_fmt": "yuv420p",
"video.width": 640
},
"names": [
"height",
"width",
"channels"
],
"shape": [
480,
640,
3
]
},
"observation.images.camera_right_wrist": {
"dtype": "video",
"info": {
"has_audio": false,
"video.channels": 3,
"video.codec": "h264",
"video.fps": 30,
"video.height": 480,
"video.is_depth_map": false,
"video.pix_fmt": "yuv420p",
"video.width": 640
},
"names": [
"height",
"width",
"channels"
],
"shape": [
480,
640,
3
]
},
"observation.state": {
"dtype": "float64",
"names": [
"left_joint1",
"left_joint2",
"left_joint3",
"left_joint4",
"left_joint5",
"left_joint6",
"right_joint1",
"right_joint2",
"right_joint3",
"right_joint4",
"right_joint5",
"right_joint6",
"right_gripper",
"left_gripper"
],
"shape": [
14
]
},
"task_index": {
"dtype": "int64",
"shape": [
1
]
},
"timestamp": {
"dtype": "float32",
"shape": [
1
]
}
},
"total_episodes": 73,
"total_frames": 629523,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
"robot_type": "DualArxR5a",
"splits": {
"train": "0:73"
}
}
```
## How to load
```python
from lerobot.datasets import LeRobotDataset
dataset = LeRobotDataset(
repo_id="io-intelligence/WipeTable_DualArxR5a_TeleXperience",
)
print(dataset)
frame = dataset[0]
```
Local path (before upload):
```python
dataset = LeRobotDataset(
repo_id="io-intelligence/WipeTable_DualArxR5a_TeleXperience",
root="/path/to/livingroom_wipe_table_livingroom_wipe_table_DualArxR5a",
download_videos=False,
video_backend="pyav",
)
```
## Citation
**BibTeX:** none
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