Cobot_Magic_food_packaging

# Cobot_Magic_food_packaging

## 📋 Overview

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

**Robot Type:** `Cobot_Magic`
| **Codebase Version:** `v2.1`
**End-Effector Type:** `two_finger_gripper`

## 🏠 Scene Types

This dataset covers the following scene types:
- `kitchen`

## 🤖 Atomic Actions

This dataset includes the following atomic actions:
- `grasp`
- `pull`
- `place`
- `pick`

## 📊 Dataset Statistics

| Metric | Value |
|--------|-------|
| **Total Episodes** | 842 |
| **Total Frames** | 1492934 |
| **Total Tasks** | 2 |
| **Total Videos** | 2526 |
| **Total Chunks** | 1 |
| **Chunk Size** | 1000 |
| **FPS** | 30 |
| **Dataset Size** | 25.2GB |

## 👥 Authors

### Contributors
This dataset is contributed by:
- [RoboCOIN](https://flagopen.github.io/RoboCOIN/) - RoboCOIN Team

## 🔗 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)
- **🌐 Project Page:** [https://flagopen.github.io/RoboCOIN/](https://flagopen.github.io/RoboCOIN/)
- **🐛 Issues:** [https://github.com/FlagOpen/RoboCOIN/issues](https://github.com/FlagOpen/RoboCOIN/issues)
- **📜 License:** apache-2.0

## 🏷️ Dataset Tags

- `RoboCOIN`
- `LeRobot`

## 🎯 Task Descriptions

### Primary Tasks
Put the items on the table into a bag.
Put the items on the table into a bag.

### Sub-Tasks
This dataset includes 49 distinct subtasks:

1. **Abnormal**
2. **Discard it.**
3. **End**
4. **Grab the banana with your right hand.**
5. **Grab the bread with your right hand.**
6. **Grab the cucumber with your right hand.**
7. **Grab the lemon with your right hand.**
8. **Grab the lunch bag with your left hand.**
9. **Grab the lunch bag with your right hand.**
10. **Grab the lunch box with your left hand.**
11. **Grab the lunch box with your right hand.**
12. **Grab the pear with your right hand.**
13. **Grasp the banana with the right gripper**
14. **Grasp the box with the right gripper**
15. **Grasp the cucumber with the right gripper**
16. **Grasp the lemon with the right gripper**
17. **Grasp the package with the left gripper**
18. **Grasp the pear with the right gripper**
19. **Hold the package and Pick up the banana**
20. **Hold the package and Pick up the box**
21. **Hold the package and Pick up the bread**
22. **Hold the package and Pick up the cucumber**
23. **Hold the package and Pick up the pear**
24. **Lift the lunch box with your left hand.**
25. **Move the lunch bag to the left.**
26. **Move the lunch bag to the right.**
27. **null**
28. **Pick up the banana**
29. **Pick up the box**
30. **Pick up the bread**
31. **Pick up the cucumber**
32. **Pick up the pear**
33. **Place it into the bag with your right hand.**
34. **Place the banana into the package**
35. **Place the banana into the package with the right gripper**
36. **Place the box into the package**
37. **Place the box into the package with the right gripper**
38. **Place the bread into the package**
39. **Place the cucumber into the package**
40. **Place the cucumber into the package with the right gripper**
41. **Place the lemon into the package with the right gripper**
42. **Place the pear into the package**
43. **Place the pear into the package with the right gripper**
44. **Pull the zipper with your right hand.**
45. **Secure the lunch bag with your left hand.**
46. **Stand the lunch bag upright with your left hand.**
47. **Stand the lunch bag upright with your right hand.**
48. **Take the lunch box with your right hand.**
49. **zip up the zipper to close the bag**

## 🎥 Camera Views

This dataset includes 3 camera views.

## 🏷️ Available Annotations

This dataset includes rich annotations to support diverse learning approaches:

### Subtask Annotations
- **Subtask Segmentation**: Fine-grained subtask segmentation and labeling
### Scene Annotations
- **Scene-level Descriptions**: Semantic scene classifications and descriptions
### End-Effector Annotations
- **Direction**: Movement direction classifications for robot end-effectors
- **Velocity**: Velocity magnitude categorizations during manipulation
- **Acceleration**: Acceleration magnitude classifications for motion analysis

### Gripper Annotations
- **Gripper Mode**: Open/close state annotations for gripper control
- **Gripper Activity**: Activity state classifications (active/inactive)

### Additional Features
- **End-Effector Simulation Pose**: 6D pose information for end-effectors in simulation space
- Available for both state and action
- **Gripper Opening Scale**: Continuous gripper opening measurements
- Available for both state and action

## 📂 Data Splits

The dataset is organized into the following splits:

- **Training**: Episodes 0:841

## 📁 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-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
- **Video Path Pattern**: `videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`
- **Chunking**: Data is organized into 1 chunk(s)
of size 1000

### Features Schema

The dataset includes the following features:

#### Visual Observations
- **observation.images.cam_high_rgb**: video
- FPS: 30
- Codec: av1- **observation.images.cam_left_wrist_rgb**: video
- FPS: 30
- Codec: av1- **observation.images.cam_right_wrist_rgb**: video
- FPS: 30
- Codec: av1

#### State and Action- **observation.state**: float32- **action**: float32

#### Temporal Information
- **timestamp**: float32
- **frame_index**: int64
- **episode_index**: int64
- **index**: int64
- **task_index**: int64

#### Annotations
- **subtask_annotation**: int32
- **scene_annotation**: int32

#### Motion Features
- **eef_sim_pose_state**: float32
- Dimensions: 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
- **eef_sim_pose_action**: float32
- Dimensions: 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
- **eef_direction_state**: int32
- Dimensions: left_eef_direction, right_eef_direction
- **eef_direction_action**: int32
- Dimensions: left_eef_direction, right_eef_direction
- **eef_velocity_state**: int32
- Dimensions: left_eef_velocity, right_eef_velocity
- **eef_velocity_action**: int32
- Dimensions: left_eef_velocity, right_eef_velocity
- **eef_acc_mag_state**: int32
- Dimensions: left_eef_acc_mag, right_eef_acc_mag
- **eef_acc_mag_action**: int32
- Dimensions: left_eef_acc_mag, right_eef_acc_mag

#### Gripper Features
- **gripper_open_scale_state**: float32
- Dimensions: left_gripper_open_scale, right_gripper_open_scale
- **gripper_open_scale_action**: float32
- Dimensions: left_gripper_open_scale, right_gripper_open_scale
- **gripper_mode_state**: int32
- Dimensions: left_gripper_mode, right_gripper_mode
- **gripper_mode_action**: int32
- Dimensions: left_gripper_mode, right_gripper_mode
- **gripper_activity_state**: int32
- Dimensions: left_gripper_activity, right_gripper_activity

### Meta Information

The complete dataset metadata is available in [meta/info.json](meta/info.json):

```json
{"codebase_version": "v2.1", "robot_type": "agilex_cobot_decoupled_magic", "total_episodes": 842, "total_frames": 1492934, "total_tasks": 2, "total_videos": 2526, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": {"train": "0:841"}, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": {"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": 30, "video.channels": 3, "has_audio": false}}, "observation.images.cam_left_wrist_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": 30, "video.channels": 3, "has_audio": false}}, "observation.images.cam_right_wrist_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": 30, "video.channels": 3, "has_audio": false}}, "observation.state": {"dtype": "float32", "shape": [26], "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", "left_eef_pos_x_m", "left_eef_pos_y_m", "left_eef_pos_z_m", "left_eef_rot_euler_x_rad", "left_eef_rot_euler_y_rad", "left_eef_rot_euler_z_rad", "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", "right_eef_pos_x_m", "right_eef_pos_y_m", "right_eef_pos_z_m", "right_eef_rot_euler_x_rad", "right_eef_rot_euler_y_rad", "right_eef_rot_euler_z_rad"]}, "action": {"dtype": "float32", "shape": [26], "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", "left_eef_pos_x_m", "left_eef_pos_y_m", "left_eef_pos_z_m", "left_eef_rot_euler_x_rad", "left_eef_rot_euler_y_rad", "left_eef_rot_euler_z_rad", "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", "right_eef_pos_x_m", "right_eef_pos_y_m", "right_eef_pos_z_m", "right_eef_rot_euler_x_rad", "right_eef_rot_euler_y_rad", "right_eef_rot_euler_z_rad"]}, "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]}}}
```

### Directory Structure

The dataset is organized as follows (showing leaf directories with first 5 files only):

```
Cobot_Magic_food_packaging_qced_hardlink/
├── annotations/
│ ├── eef_acc_mag_annotation.jsonl
│ ├── eef_direction_annotation.jsonl
│ ├── eef_velocity_annotation.jsonl
│ ├── gripper_activity_annotation.jsonl
│ ├── gripper_mode_annotation.jsonl
│ └── (...)
├── data/
│ └── chunk-000/
│ ├── episode_000000.parquet
│ ├── episode_000001.parquet
│ ├── episode_000002.parquet
│ ├── episode_000003.parquet
│ ├── episode_000004.parquet
│ └── (...)
├── meta/
│ ├── episodes.jsonl
│ ├── episodes_stats.jsonl
│ ├── info.json
│ └── tasks.jsonl
└── videos/
└── chunk-000/
├── observation.images.cam_high_rgb/
│ ├── episode_000000.mp4
│ ├── episode_000001.mp4
│ ├── episode_000002.mp4
│ ├── episode_000003.mp4
│ ├── episode_000004.mp4
│ └── (...)
├── observation.images.cam_left_wrist_rgb/
│ ├── episode_000000.mp4
│ ├── episode_000001.mp4
│ ├── episode_000002.mp4
│ ├── episode_000003.mp4
│ ├── episode_000004.mp4
│ └── (...)
└── observation.images.cam_right_wrist_rgb/
├── episode_000000.mp4
├── episode_000001.mp4
├── episode_000002.mp4
├── episode_000003.mp4
├── episode_000004.mp4
└── (...)
```

## 📞 Contact and Support

For questions, issues, or feedback regarding this dataset, please contact:
- **Email:** None
For questions, issues, or feedback regarding this dataset, please contact us.
### Support
For technical support, please open an issue on our GitHub repository.

## 📄 License

This dataset is released under the **apache-2.0** license.

Please refer to the LICENSE file for full license terms and conditions.

## 📚 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

## Version History
- v1.0.0 (2025-11): Initial release