Galaxea_R1_Lite_classify_object_five

Dataset Description

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

Task Preview

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Overview

• Total Episodes: 195

• Total Frames: 160875

• FPS: 30

• Dataset Size: 8.91 GB

• Robot Name: Galaxea_R1_Lite

• End-Effector Type: two_finger_gripper

• Teleoperation Type: Due to some reasons, this dataset temporarily cannot provide the teleoperation type information.

• Sensors: cam_head_left_rgb, cam_head_right_rgb, cam_left_wrist_rgb, cam_right_wrist_rgb

• Camera Information: cam_head_left_rgb; cam_head_right_rgb; cam_left_wrist_rgb; cam_right_wrist_rgb

• Scene: commercial_convenience->supermarket

• Objects: brown_basket(unknown), yellow_basket(unknown), any_fruits(unknown), any_vegetables(unknown), any_snacks(unknown), any_bread(unknown)

• Task Description: place the food in the right basket with the right gripper, and place the non food items in the left basket with the left gripper.

Primary Task Instruction

place the food in the right basket with the right gripper, and place the non food items in the left basket with the left gripper.

Robot Configuration

• Robot Name: Galaxea_R1_Lite
• Codebase Version: v2.1
• End-Effector Type: two_finger_gripper
• Teleoperation Type: Due to some reasons, this dataset temporarily cannot provide the teleoperation type information.

Scene and Objects

Scene Type

commercial_convenience->supermarket

Objects

• brown_basket(unknown)
• yellow_basket(unknown)
• any_fruits(unknown)
• any_vegetables(unknown)
• any_snacks(unknown)
• any_bread(unknown)

Task Descriptions

• Standardized Task Description: place the food in the right basket with the right gripper, and place the non food items in the left basket with the left 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 58 distinct subtasks:

1. Grasp the rubiks cube and put it in the left basket (Index: 0)
2. Grasp the waffle and put it in the right basket (Index: 1)
3. Grasp the soft cleanser and put it in the left basket (Index: 2)
4. Grasp the back scratcher and put it in the left basket (Index: 3)
5. Grasp the apple and put it in the right basket (Index: 4)
6. End (Index: 5)
7. Grasp the white eraser and put it in the left basket (Index: 6)
8. Grasp the square chewing gum and put it in the right basket (Index: 7)
9. Grasp the power strip and put it in the left basket (Index: 8)
10. Grasp the cleaning agent and put it in the left basket (Index: 9)
11. Grasp the soda water and put it in the right basket (Index: 10)
12. Grasp the spoon and put it in the left basket (Index: 11)
13. Grasp the duck toys and put it in the left basket (Index: 12)
14. Grasp the triangle cake and put it in the right basket (Index: 13)
15. Grasp the compass and put it in the right basket (Index: 14)
16. Grasp the cookie and put it in the right basket (Index: 15)
17. Grasp the compass and put it in the left basket (Index: 16)
18. Grasp the orange and put it in the right basket (Index: 17)
19. Grasp the ballpoint pen and put it in the left basket (Index: 18)
20. Grasp the round bread and put it in the right basket (Index: 19)
21. Grasp the egg yolk pastry and put it in the right basket (Index: 20)
22. Grasp the lemon and put it in the right basket (Index: 21)
23. Grasp the soap and put it in the left basket (Index: 22)
24. Grasp the washing liquid and put it in the left basket (Index: 23)
25. Grasp the hard cleanser and put it in the left basket (Index: 24)
26. Grasp the milk and put it in the right basket (Index: 25)
27. Grasp the black marker and put it in the left basket (Index: 26)
28. Grasp the banana and put it in the right basket (Index: 27)
29. Grasp the black glass cup and put it in the left basket (Index: 28)
30. Grasp the brush and put it in the left basket (Index: 29)
31. Grasp the bath ball and put it in the left basket (Index: 30)
32. Grasp the blue towel and put it in the left basket (Index: 31)
33. Grasp the tea cup and put it in the left basket (Index: 32)
34. Grasp the peeler and put it in the left basket (Index: 33)
35. Grasp the brown towel and put it in the left basket (Index: 34)
36. Grasp the peach and put it in the right basket (Index: 35)
37. Abnormal (Index: 36)
38. Grasp the chocolate and put it in the right basket (Index: 37)
39. Grasp the grey towel and put it in the left basket (Index: 38)
40. Grasp the canned cola and put it in the right basket (Index: 39)
41. Grasp the tape and put it in the left basket (Index: 40)
42. Grasp the bread slice and put it in the right basket (Index: 41)
43. Grasp the tin and put it in the right basket (Index: 42)
44. Grasp the soap and put it in the right basket (Index: 43)
45. Grasp the glasses case and put it in the left basket (Index: 44)
46. Grasp the yellow duck and put it in the right basket (Index: 45)
47. Grasp the peach doll and put it in the right basket (Index: 46)
48. Grasp the blue cup and put it in the left basket (Index: 47)
49. Grasp the pen container and put it in the left basket (Index: 48)
50. Grasp the red duck and put it in the left basket (Index: 49)
51. Grasp the lime and put it in the right basket (Index: 50)
52. Grasp the long bread and put it in the right basket (Index: 51)
53. Grasp the yogurt and put it in the right basket (Index: 52)
54. Grasp the potato chips and put it in the right basket (Index: 53)
55. Grasp the can and put it in the right basket (Index: 54)
56. Grasp the ad milk and put it in the right basket (Index: 55)
57. Grasp the blue marker and put it in the left basket (Index: 56)
58. null (Index: 57)

Atomic Actions

• grasp
• pick
• place

Hardware and Sensors

Sensors

• cam_head_left_rgb

• cam_head_right_rgb

• cam_left_wrist_rgb

• cam_right_wrist_rgb

Camera Information

• cam_head_left_rgb: dtype=video, shape=720x1280x3, resolution=1280x720, codec=av1, pix_fmt=yuv420p

• cam_head_right_rgb: dtype=video, shape=720x1280x3, resolution=1280x720, codec=av1, pix_fmt=yuv420p

• cam_left_wrist_rgb: dtype=video, shape=720x1280x3, resolution=1280x720, codec=av1, pix_fmt=yuv420p

• cam_right_wrist_rgb: dtype=video, shape=720x1280x3, resolution=1280x720, codec=av1, pix_fmt=yuv420p

Coordinate System

• Definition: right-hand-frame

Dimensions & Units

• Joint Rotation: radian
• End-Effector Rotation: end_rotation_dim
• End-Effector Translation: end_translation_dim

Dataset Statistics

Metric	Value
Total Episodes	195
Total Frames	160875
Total Tasks	58
Total Videos	780
Total Chunks	1
Chunk Size	1000
FPS	30
State Dimensions	14
Action Dimensions	14
Camera Views	4
Dataset Size	8.91 GB

Data Splits

The dataset is organized into the following splits:

• Training: Episodes 0:194

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_left_wrist_rgb/episode_{id}.mp{id}
• Chunking: Data is organized into 1 chunk(s) of size 1000

Data Structure (Tree)

Galaxea_R1_Lite_classify_object_five_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
|       `-- ... (183 more entries)
|-- meta
|   |-- episodes.jsonl
|   |-- episodes_stats.jsonl
|   |-- info.json
|   `-- tasks.jsonl
|-- videos
|   `-- chunk-000
|       |-- observation.images.cam_head_left_rgb
|       |-- observation.images.cam_head_right_rgb
|       |-- observation.images.cam_left_wrist_rgb
|       `-- observation.images.cam_right_wrist_rgb
|-- info.yaml
`-- README.md

Camera Views

This dataset includes 4 camera views: cam_head_left_rgb, cam_head_right_rgb, cam_left_wrist_rgb, cam_right_wrist_rgb.

Features (Full YAML)

observation.images.cam_head_left_rgb:
  dtype: video
  shape:
  - 720
  - 1280
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 720
    video.width: 1280
    video.codec: av1
    video.pix_fmt: yuv420p
    video.is_depth_map: false
    video.fps: 30
    video.channels: 3
    has_audio: false
observation.images.cam_head_right_rgb:
  dtype: video
  shape:
  - 720
  - 1280
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 720
    video.width: 1280
    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:
  - 720
  - 1280
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 720
    video.width: 1280
    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:
  - 720
  - 1280
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 720
    video.width: 1280
    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:
  - 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
  - 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
  - left_gripper_open
  - 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
  - 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
  - left_gripper_open
  - 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
  shape:
  - 5
  dtype: int32
scene_annotation:
  names: null
  shape:
  - 1
  dtype: int32
eef_sim_pose_state:
  names:
  - left_eef_pos_x
  - left_eef_pos_y
  - left_eef_pos_z
  - left_eef_rot_x
  - left_eef_rot_y
  - left_eef_rot_z
  - right_eef_pos_x
  - right_eef_pos_y
  - right_eef_pos_z
  - right_eef_rot_x
  - right_eef_rot_y
  - right_eef_rot_z
  shape:
  - 12
  dtype: float32
eef_sim_pose_action:
  names:
  - left_eef_pos_x
  - left_eef_pos_y
  - left_eef_pos_z
  - left_eef_rot_x
  - left_eef_rot_y
  - left_eef_rot_z
  - right_eef_pos_x
  - right_eef_pos_y
  - right_eef_pos_z
  - right_eef_rot_x
  - right_eef_rot_y
  - right_eef_rot_z
  shape:
  - 12
  dtype: float32
eef_direction_state:
  names:
  - left_eef_direction
  - right_eef_direction
  shape:
  - 2
  dtype: int32
eef_direction_action:
  names:
  - left_eef_direction
  - right_eef_direction
  shape:
  - 2
  dtype: int32
eef_velocity_state:
  names:
  - left_eef_velocity
  - right_eef_velocity
  shape:
  - 2
  dtype: int32
eef_velocity_action:
  names:
  - left_eef_velocity
  - right_eef_velocity
  shape:
  - 2
  dtype: int32
eef_acc_mag_state:
  names:
  - left_eef_acc_mag
  - right_eef_acc_mag
  shape:
  - 2
  dtype: int32
eef_acc_mag_action:
  names:
  - left_eef_acc_mag
  - right_eef_acc_mag
  shape:
  - 2
  dtype: int32
gripper_open_scale_state:
  names:
  - left_gripper_open_scale
  - right_gripper_open_scale
  shape:
  - 2
  dtype: float32
gripper_open_scale_action:
  names:
  - left_gripper_open_scale
  - right_gripper_open_scale
  shape:
  - 2
  dtype: float32
gripper_mode_state:
  names:
  - left_gripper_mode
  - right_gripper_mode
  shape:
  - 2
  dtype: int32
gripper_mode_action:
  names:
  - left_gripper_mode
  - right_gripper_mode
  shape:
  - 2
  dtype: int32
gripper_activity_state:
  names:
  - left_gripper_activity
  - right_gripper_activity
  shape:
  - 2
  dtype: int32
gripper_activity_action:
  names:
  - left_gripper_activity
  - right_gripper_activity
  shape:
  - 2
  dtype: int32

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/
• Paper: https://arxiv.org/abs/2511.17441
• Repository: 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:

@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