Hugging Face's logo

Datasets:
RoboCOIN
/
Cobot_Magic_desktop_organization

Tasks:
Robotics
Modalities:
Tabular
Time-series
Video
Formats:
parquet
Languages:
English
Chinese
Size:
1M - 10M
ArXiv:
Tags:
RoboCOIN
LeRobot
Libraries:
Datasets
Dask
License:
Dataset card Data Studio Files
xet
Community

You need to agree to share your contact information to access this dataset

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

By accessing this dataset, you agree to cite the associated paper in your research/publications—see the "Citation" section for details. You agree to not use the dataset to conduct experiments that cause harm to human subjects.

Log in or Sign Up to review the conditions and access this dataset content.

Cobot_Magic_desktop_organization

📋 Overview

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

Robot Type: agilex_cobot_decoupled_magic | Codebase Version: v2.1 End-Effector Type: two_finger_gripper

🏠 Scene Types

This dataset covers the following scene types:

  • home
  • office

🤖 Atomic Actions

This dataset includes the following atomic actions:

  • grasp
  • pick
  • place

📊 Dataset Statistics

Metric Value
Total Episodes 1070
Total Frames 2026628
Total Tasks 6
Total Videos 3210
Total Chunks 2
Chunk Size 1000
FPS 30
Dataset Size 32.3GB

👥 Authors

Contributors

This dataset is contributed by:

🔗 Links

🏷️ Dataset Tags

  • RoboCOIN
  • LeRobot

🎯 Task Descriptions

Primary Tasks

put the banana on the plate, put the waste paper in the basket, place the water bottle upright near the plate, put the eraser in the pen holder, put the pen in the pen holder. put the bread on the plate, put the small pieces of paper in the basket, place thecoffee near the plate, put the pencil sharpener in the pen holder, put the rulerin the pen holder, put the pen in the pen holder. put the pear on the plate, put the waste paper in the basket, place the water bottleupright near the plate, put the knife in the pen holder, put the ruler in the penholder, put the pen in the pen holder. put the grape on a plate, put the plastic sheet in the basket, place the teacupneatly near the plate, put the scissor in the pen holder, put the ruler in the penholder, put the colored glue in the pen holder. put the manngo and banana on the fruit tray, put the paper ball in the garbage bin,straighten the water bottle, put the eraser and pen in the pen holder. pick up the green basket, put the cola inside the basket, and then put the basketdown.

Sub-Tasks

This dataset includes 108 distinct subtasks:

  1. Hand over the waste paper
  2. Place the red pencil sharpener into the pen holder
  3. place the silver glue into the pen holder
  4. Place the cola can in the basket with left gripper
  5. Place the waste paper in the basket with left gripper
  6. Place the eraser in pen holder with left gripper
  7. Grasp the waste paper with right gripper
  8. Place the pear in the plate
  9. Static
  10. Hand over the plastic
  11. Grasp the bottle with left gripper
  12. pick up the ruler
  13. Place the black pen in pen holder with left gripper
  14. Grasp the banana with left gripper
  15. Pick up the banana
  16. Hand over the banana
  17. Pick up the pen with right arm
  18. Place the cola can in the basket with right gripper
  19. Hand over the grapes
  20. Place the basket on the table with right gripper
  21. Pick up the red pencil sharpener
  22. Stand the bottle with left gripper
  23. Pick up the waste paper
  24. Grasp the blue pen with left gripper
  25. pick up the yellow knife
  26. Place the eraser into the pen holder
  27. Place the black pen in pen holder with right gripper
  28. Place the gray pen in pen holder with right gripper
  29. Place the gray pen in pen holder with left gripper
  30. Place the milk in the basket with right gripper
  31. pick up the red glue
  32. Hand over the yellow glue
  33. Hand over the bottle
  34. Place the plastic in the basket
  35. Pick up the grapes
  36. pick up the pink scissors
  37. pick up the silver glue
  38. Abnormal
  39. Place the blue pen in pen holder with right gripper
  40. Place the blue pen in pen holder with left gripper
  41. Place the yellow pen in pen holder with right gripper
  42. Grasp the cola can with right gripper
  43. Grasp the mango with left gripper
  44. Grasp the black pen with left gripper
  45. Grasp the blue pen with right gripper
  46. Grasp the eraser with right gripper
  47. Pick up the plastic
  48. Place the waste paper in the basket with right gripper
  49. Grasp the cola can with left gripper
  50. Place the cola can on the table with left gripper
  51. Pick up the eraser
  52. Grasp the waste paper with left gripper
  53. Grasp the yellow pen with right gripper
  54. Place the pink scissors into the pen holder
  55. Lift the basket with left gripper
  56. Pick up the bottle with the right arm
  57. Hand over the bread
  58. Place the grapes in the plate
  59. transfer the pen to the left arm
  60. transfer the bottle to the left arm
  61. Hand over the red glue
  62. End
  63. Hand over the yellow knife
  64. Hand over the ruler
  65. Place the blue scissors into the pen holder
  66. Place the yellow pen in pen holder with left gripper
  67. Hand over the blue knife
  68. Place the pen into the pen holder
  69. Pick up the pear
  70. transfer the pen to the right arm
  71. Place the blue knife into the pen holder
  72. Place the mango in the plate with left gripper
  73. pick up the yellow glue
  74. Hand over the pear
  75. Place the blue pencil sharpener into the pen holder
  76. Grasp the black pen with right gripper
  77. Hand over the pink scissors
  78. Pick up the bottle with the left arm
  79. Grasp the gray pen with right gripper
  80. Grasp the eraser with left gripper
  81. Place the eraser in pen holder with right gripper
  82. Grasp the basket with left gripper
  83. Pick up the pen with left arm
  84. Pick up the blue pencil sharpener
  85. pick up the bread
  86. Hand over the pen
  87. Place the milk in the basket with left gripper
  88. place the red glue into the pen holder
  89. Place the banana in the plate with left gripper
  90. Hand the basket to the right gripper with the left gripper
  91. place the bread in the plate
  92. Grasp the yellow pen with left gripper
  93. Hand over the blue scissors
  94. place the yellow glue into the pen holder
  95. pick up the blue knife
  96. Place the cola can on the table with right gripper
  97. Place the bottle
  98. Grasp the gray pen with left gripper
  99. Place the ruler into the pen holder
  100. pick up the blue scissors
  101. Grasp the milk with right gripper
  102. Place the banana in the plate
  103. Grasp the milk with left gripper
  104. Place the basket on the table with left gripper
  105. Hand over the silver glue
  106. Place the waste paper in the basket
  107. place the yellow knife into the pen holder
  108. null

🎥 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 0:1069

📁 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 2 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:

{"codebase_version": "v2.1", "robot_type": "agilex_cobot_decoupled_magic", "total_episodes": 1070, "total_frames": 2026628, "total_tasks": 6, "total_videos": 3210, "total_chunks": 2, "chunks_size": 1000, "fps": 30, "splits": {"train": "0:1069"}, "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_desktop_organization_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
│   │   └── (...)
│   └── chunk-001/
│       ├── episode_001000.parquet
│       ├── episode_001001.parquet
│       ├── episode_001002.parquet
│       ├── episode_001003.parquet
│       ├── episode_001004.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
    │       └── (...)
    └── chunk-001/
        ├── observation.images.cam_high_rgb/
        │   ├── episode_001000.mp4
        │   ├── episode_001001.mp4
        │   ├── episode_001002.mp4
        │   ├── episode_001003.mp4
        │   ├── episode_001004.mp4
        │   └── (...)
        ├── observation.images.cam_left_wrist_rgb/
        │   ├── episode_001000.mp4
        │   ├── episode_001001.mp4
        │   ├── episode_001002.mp4
        │   ├── episode_001003.mp4
        │   ├── episode_001004.mp4
        │   └── (...)
        └── observation.images.cam_right_wrist_rgb/
            ├── episode_001000.mp4
            ├── episode_001001.mp4
            ├── episode_001002.mp4
            ├── episode_001003.mp4
            ├── episode_001004.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:

@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:

📌 Version Information

Version History

  • v1.0.0 (2025-11): Initial release
Downloads last month
2,102

Collection including RoboCOIN/Cobot_Magic_desktop_organization