---
title: Agilex_Split_Aloha_storage_plate
canonical_url: "https://www.modelscope.cn/datasets/RoboCOIN/Agilex_Split_Aloha_storage_plate"
md_url: "https://www.modelscope.cn/datasets/RoboCOIN/Agilex_Split_Aloha_storage_plate.md"
repository: RoboCOIN/Agilex_Split_Aloha_storage_plate
last_updated: 2026-06-23
license: apache-2.0
storage_size: "903 MB"
downloads: 32031
stars: 0
---

# Agilex_Split_Aloha_storage_plate

> Agilex_Split_Aloha_storage_plate - RoboCOIN 在 ModelScope 开源的数据集。AgilexSplitAlohastorageplate

RoboCOIN/Agilex_Split_Aloha_storage_plate 是 ModelScope 魔搭社区上的数据集，存储大小 903 MB，采用 apache-2.0 许可。

- **Repository**: RoboCOIN/Agilex_Split_Aloha_storage_plate
- **License**: apache-2.0
- **Storage size**: 903 MB
- **Downloads**: 32031
- **Stars**: 0
- **Last updated**: 2026-06-23

Source: https://www.modelscope.cn/datasets/RoboCOIN/Agilex_Split_Aloha_storage_plate

---

# Agilex_Split_Aloha_storage_plate

## Dataset Description

This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.

## Task Preview

<video src="videos/chunk-000/observation.images.cam_high_rgb/episode_000000.mp4" controls width="640"></video>

[View Video Directly](videos/chunk-000/observation.images.cam_high_rgb/episode_000000.mp4)

### Overview

- **Total Episodes:** 84
- **Total Frames:** 57019
- **FPS:** 50
- **Dataset Size:** 903.43 MB
- **Robot Name:** `Agilex_Split_Aloha`
- **End-Effector Type:** `two_finger_end_effector`
- **Teleoperation Type:** `Due to some reasons, this dataset temporarily cannot provide the teleoperation type information.`
- **Sensors:** `cam_high_rgb`, 
`cam_left_wrist_rgb_rgb`, 
`cam_right_wrist_rgb_rgb`

- **Camera Information:** cam_high_rgb; 
cam_left_wrist_rgb_rgb; 
cam_right_wrist_rgb_rgb

- **Scene:** `home`
- **Objects:** `table(unknown)`, 
`rack(unknown)`, 
`tablecloth(unknown)`, 
`plate(unknown)`

- **Task Description:** Pick up the test tube with your left gripper, hand it to your right gripper, and then place it on the test tube rack with the right gripper.


### Primary Task Instruction
> Pick up the test tube with your left gripper, hand it to your right gripper, and then place it on the test tube rack with the right gripper.

### Robot Configuration

- **Robot Name:** `Agilex_Split_Aloha`
- **Codebase Version:** `v2.1`
- **End-Effector Type:** `two_finger_end_effector`
- **Teleoperation Type:** `Due to some reasons, this dataset temporarily cannot provide the teleoperation type information.`

## Scene and Objects

### Scene Type
- `home`

### Objects
- `table(unknown)`
- `rack(unknown)`
- `tablecloth(unknown)`
- `plate(unknown)`


## Task Descriptions

- **Standardized Task Description:** `Pick up the test tube with your left gripper, hand it to your right gripper, and then place it on the test tube rack with the right gripper.`
- **Operation Type:** `Due to some reasons, this dataset temporarily cannot provide the operation type information.`

- **Environment Type:** `Due to some reasons, this dataset temporarily cannot provide the environment type information.`

### Sub-Tasks
This dataset includes 15 distinct subtasks:

1. **Left pick up the white plate.** (Index: 0)
2. **Left pick up the gray plate.** (Index: 1)
3. **Place the plate on the rack.** (Index: 2)
4. **Right place it at the front of the shelf.** (Index: 3)
5. **Right receive the plate.** (Index: 4)
6. **Pick up the plate from the table.** (Index: 5)
7. **Left lift the plate.** (Index: 6)
8. **end.** (Index: 7)
9. **Left pick up the blue plate.** (Index: 8)
10. **Left pick up the yellow plate.** (Index: 9)
11. **pass the plate.** (Index: 10)
12. **Right place it at the back of the shelf.** (Index: 11)
13. **Left pick up the pink plate.** (Index: 12)
14. **Left pick up the green plate.** (Index: 13)
15. **null.** (Index: 14)


### Atomic Actions
- `grasp`
- `pick`
- `place`


## Hardware and Sensors


### Sensors

- `cam_high_rgb`

- `cam_left_wrist_rgb_rgb`

- `cam_right_wrist_rgb_rgb`




### Camera Information


- `cam_high_rgb`: dtype=video, shape=480x640x3, resolution=640x480, codec=av1, pix_fmt=yuv420p

- `cam_left_wrist_rgb_rgb`: dtype=video, shape=480x640x3, resolution=640x480, codec=av1, pix_fmt=yuv420p

- `cam_right_wrist_rgb_rgb`: dtype=video, shape=480x640x3, resolution=640x480, codec=av1, pix_fmt=yuv420p




### Coordinate System
- **Definition:** `right-hand-frame`


### Dimensions & Units
- **Joint Rotation:** `radian`






## Dataset Statistics

| Metric | Value |
|--------|-------|
| **Total Episodes** | 84 |
| **Total Frames** | 57019 |
| **Total Tasks** | 15 |
| **Total Videos** | 252 |
| **Total Chunks** | 1 |
| **Chunk Size** | 1000 |
| **FPS** | 50 |
| **State Dimensions** | 14 |
| **Action Dimensions** | 14 |
| **Camera Views** | 3 |
| **Dataset Size** | 903.43 MB |


## Data Splits

The dataset is organized into the following splits:

- **Training**: Episodes 0:83


## Dataset Structure

This dataset follows the LeRobot format and contains the following components:

### Data Files
- **Videos**: Compressed video files containing RGB camera observations
- **State Data**: Robot joint positions, velocities, and other state information
- **Action Data**: Robot action commands and trajectories
- **Metadata**: Episode metadata, timestamps, and annotations

### File Organization
- **Data Path Pattern**: `data/chunk-{id}/episode_{id}.parquet`
- **Video Path Pattern**: `videos/chunk-{id}/observation.images.cam_high_rgb/episode_{id}.mp{id}`
- **Chunking**: Data is organized into 1 chunk(s)
of size 1000

### Data Structure (Tree)

```
Cobot_Magic_storage_plate_qced_hardlink/
|-- annotations
|   |-- eef_acc_mag_annotation.jsonl
|   |-- eef_direction_annotation.jsonl
|   |-- eef_velocity_annotation.jsonl
|   |-- gripper_activity_annotation.jsonl
|   |-- gripper_mode_annotation.jsonl
|   |-- scene_annotations.jsonl
|   `-- subtask_annotations.jsonl
|-- data
|   `-- chunk-000
|       |-- episode_000000.parquet
|       |-- episode_000001.parquet
|       |-- episode_000002.parquet
|       |-- episode_000003.parquet
|       |-- episode_000004.parquet
|       |-- episode_000005.parquet
|       |-- episode_000006.parquet
|       |-- episode_000007.parquet
|       |-- episode_000008.parquet
|       |-- episode_000009.parquet
|       |-- episode_000010.parquet
|       `-- episode_000011.parquet
|       `-- ... (72 more entries)
|-- meta
|   |-- episodes.jsonl
|   |-- episodes_stats.jsonl
|   |-- info.json
|   `-- tasks.jsonl
|-- videos
|   `-- chunk-000
|       |-- observation.images.cam_high_rgb
|       |-- observation.images.cam_left_wrist_rgb_rgb
|       `-- observation.images.cam_right_wrist_rgb_rgb
`-- README.md
```

## Camera Views






This dataset includes 3 camera views: `cam_high_rgb`, `cam_left_wrist_rgb_rgb`, `cam_right_wrist_rgb_rgb`.


## Features (Full YAML)

```yaml
observation.images.cam_high_rgb:
  dtype: video
  shape:
  - 480
  - 640
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 480
    video.width: 640
    video.codec: av1
    video.pix_fmt: yuv420p
    video.is_depth_map: false
    video.fps: 50
    video.channels: 3
    has_audio: false
observation.images.cam_left_wrist_rgb_rgb:
  dtype: video
  shape:
  - 480
  - 640
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 480
    video.width: 640
    video.codec: av1
    video.pix_fmt: yuv420p
    video.is_depth_map: false
    video.fps: 50
    video.channels: 3
    has_audio: false
observation.images.cam_right_wrist_rgb_rgb:
  dtype: video
  shape:
  - 480
  - 640
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 480
    video.width: 640
    video.codec: av1
    video.pix_fmt: yuv420p
    video.is_depth_map: false
    video.fps: 50
    video.channels: 3
    has_audio: false
observation.state:
  dtype: float32
  shape:
  - 14
  names:
  - left_arm_joint_1_rad
  - left_arm_joint_2_rad
  - left_arm_joint_3_rad
  - left_arm_joint_4_rad
  - left_arm_joint_5_rad
  - left_arm_joint_6_rad
  - left_gripper_open
  - right_arm_joint_1_rad
  - right_arm_joint_2_rad
  - right_arm_joint_3_rad
  - right_arm_joint_4_rad
  - right_arm_joint_5_rad
  - right_arm_joint_6_rad
  - right_gripper_open
action:
  dtype: float32
  shape:
  - 14
  names:
  - left_arm_joint_1_rad
  - left_arm_joint_2_rad
  - left_arm_joint_3_rad
  - left_arm_joint_4_rad
  - left_arm_joint_5_rad
  - left_arm_joint_6_rad
  - left_gripper_open
  - right_arm_joint_1_rad
  - right_arm_joint_2_rad
  - right_arm_joint_3_rad
  - right_arm_joint_4_rad
  - right_arm_joint_5_rad
  - right_arm_joint_6_rad
  - right_gripper_open
timestamp:
  dtype: float32
  shape:
  - 1
  names: null
frame_index:
  dtype: int64
  shape:
  - 1
  names: null
episode_index:
  dtype: int64
  shape:
  - 1
  names: null
index:
  dtype: int64
  shape:
  - 1
  names: null
task_index:
  dtype: int64
  shape:
  - 1
  names: null
subtask_annotation:
  names: null
  dtype: int32
  shape:
  - 5
scene_annotation:
  names: null
  dtype: int32
  shape:
  - 1
eef_sim_pose_state:
  names:
  - left_eef_pos_x
  - left_eef_pos_y
  - left_eef_pos_z
  - left_eef_ori_x
  - left_eef_ori_y
  - left_eef_ori_z
  - right_eef_pos_x
  - right_eef_pos_y
  - right_eef_pos_z
  - right_eef_ori_x
  - right_eef_ori_y
  - right_eef_ori_z
  dtype: float32
  shape:
  - 12
eef_sim_pose_action:
  names:
  - left_eef_pos_x
  - left_eef_pos_y
  - left_eef_pos_z
  - left_eef_ori_x
  - left_eef_ori_y
  - left_eef_ori_z
  - right_eef_pos_x
  - right_eef_pos_y
  - right_eef_pos_z
  - right_eef_ori_x
  - right_eef_ori_y
  - right_eef_ori_z
  dtype: float32
  shape:
  - 12
eef_direction_state:
  names:
  - left_eef_direction
  - right_eef_direction
  dtype: int32
  shape:
  - 2
eef_direction_action:
  names:
  - left_eef_direction
  - right_eef_direction
  dtype: int32
  shape:
  - 2
eef_velocity_state:
  names:
  - left_eef_velocity
  - right_eef_velocity
  dtype: int32
  shape:
  - 2
eef_velocity_action:
  names:
  - left_eef_velocity
  - right_eef_velocity
  dtype: int32
  shape:
  - 2
eef_acc_mag_state:
  names:
  - left_eef_acc_mag
  - right_eef_acc_mag
  dtype: int32
  shape:
  - 2
eef_acc_mag_action:
  names:
  - left_eef_acc_mag
  - right_eef_acc_mag
  dtype: int32
  shape:
  - 2
gripper_open_scale_state:
  names:
  - left_gripper_open_scale
  - right_gripper_open_scale
  dtype: float32
  shape:
  - 2
gripper_open_scale_action:
  names:
  - left_gripper_open_scale
  - right_gripper_open_scale
  dtype: float32
  shape:
  - 2
gripper_mode_state:
  names:
  - left_gripper_mode
  - right_gripper_mode
  dtype: int32
  shape:
  - 2
gripper_mode_action:
  names:
  - left_gripper_mode
  - right_gripper_mode
  dtype: int32
  shape:
  - 2
gripper_activity_state:
  names:
  - left_gripper_activity
  - right_gripper_activity
  dtype: int32
  shape:
  - 2

```

## Available Annotations

This dataset includes rich annotations to support diverse learning approaches:

- `eef_acc_mag_annotation.jsonl`
- `eef_direction_annotation.jsonl`
- `eef_velocity_annotation.jsonl`
- `gripper_activity_annotation.jsonl`
- `gripper_mode_annotation.jsonl`
- `scene_annotations.jsonl`
- `subtask_annotations.jsonl`


## Dataset Tags

- `RoboCOIN`
- `LeRobot`


## Authors

### Contributors
This dataset is contributed by:-RoboCOIN Team at Beijing Academy of Artificial Intelligence (BAAI)

### Annotators
No annotator information available.

## Links

- **Homepage:** [https://flagopen.github.io/RoboCOIN/](https://flagopen.github.io/RoboCOIN/)
- **Paper:** [https://arxiv.org/abs/2511.17441](https://arxiv.org/abs/2511.17441)
- **Repository:** [https://github.com/FlagOpen/RoboCOIN](https://github.com/FlagOpen/RoboCOIN)
## Contact and Support

For questions, issues, or feedback regarding this dataset, please contact us.
### Support
For technical support, please open an issue on our GitHub repository.

## License

apache-2.0

## Citation

If you use this dataset in your research, please cite:

```bibtex
@article{robocoin,
  title={RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation},
  author={Shihan Wu, Xuecheng Liu, Shaoxuan Xie, Pengwei Wang, Xinghang Li, Bowen Yang, Zhe Li, Kai Zhu, Hongyu Wu, Yiheng Liu, Zhaoye Long, Yue Wang, Chong Liu, Dihan Wang, Ziqiang Ni, Xiang Yang, You Liu, Ruoxuan Feng, Runtian Xu, Lei Zhang, Denghang Huang, Chenghao Jin, Anlan Yin, Xinlong Wang, Zhenguo Sun, Junkai Zhao, Mengfei Du, Mingyu Cao, Xiansheng Chen, Hongyang Cheng, Xiaojie Zhang, Yankai Fu, Ning Chen, Cheng Chi, Sixiang Chen, Huaihai Lyu, Xiaoshuai Hao, Yequan Wang, Bo Lei, Dong Liu, Xi Yang, Yance Jiao, Tengfei Pan, Yunyan Zhang, Songjing Wang, Ziqian Zhang, Xu Liu, Ji Zhang, Caowei Meng, Zhizheng Zhang, Jiyang Gao, Song Wang, Xiaokun Leng, Zhiqiang Xie, Zhenzhen Zhou, Peng Huang, Wu Yang, Yandong Guo, Yichao Zhu, Suibing Zheng, Hao Cheng, Xinmin Ding, Yang Yue, Huanqian Wang, Chi Chen, Jingrui Pang, YuXi Qian, Haoran Geng, Lianli Gao, Haiyuan Li, Bin Fang, Gao Huang, Yaodong Yang, Hao Dong, He Wang, Hang Zhao, Yadong Mu, Di Hu, Hao Zhao, Tiejun Huang, Shanghang Zhang, Yonghua Lin, Zhongyuan Wang and Guocai Yao},
  journal={arXiv preprint arXiv:2511.17441},
  url = {https://arxiv.org/abs/2511.17441},
  year={2025},
  }

```

### Additional References

If you use this dataset, please also consider citing:
LeRobot Framework: https://github.com/huggingface/lerobot


## Version Information

Initial Release
