Galaxea_R1_Lite_storage_object_gray_plate

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: 102

• Total Frames: 20357

• FPS: 30

• Dataset Size: 786.26 MB

• 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: household->living_room

• Objects: gray_plate(unknown), banana(unknown), bathing_in_flowers(unknown), blue_cup(unknown), blue_pot(unknown), toast_slices(unknown), brown_towel(unknown), can(unknown), coke(unknown), potato_chips(unknown), chocolate(unknown), compass(unknown), block_pillar(unknown), egg_beater(unknown), eraser(unknown), chewing_gum(unknown), mentholatum_facial_cleanser(unknown), green_lemon(unknown), peach(unknown), power_strip(unknown), round_bread(unknown), mentholatum_facial_cleanser(unknown), square_building_blocks(unknown), tape(unknown), cake(unknown), duck(unknown), ambrosial_yogurt(unknown)

• Task Description: use a gripper to pick the target object and place on the gray plate.

Primary Task Instruction

use a gripper to pick the target object and place on the gray plate.

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

household->living_room

Objects

• gray_plate(unknown)
• banana(unknown)
• bathing_in_flowers(unknown)
• blue_cup(unknown)
• blue_pot(unknown)
• toast_slices(unknown)
• brown_towel(unknown)
• can(unknown)
• coke(unknown)
• potato_chips(unknown)
• chocolate(unknown)
• compass(unknown)
• block_pillar(unknown)
• egg_beater(unknown)
• eraser(unknown)
• chewing_gum(unknown)
• mentholatum_facial_cleanser(unknown)
• green_lemon(unknown)
• peach(unknown)
• power_strip(unknown)
• round_bread(unknown)
• mentholatum_facial_cleanser(unknown)
• square_building_blocks(unknown)
• tape(unknown)
• cake(unknown)
• duck(unknown)
• ambrosial_yogurt(unknown)

Task Descriptions

• Standardized Task Description: use a gripper to pick the target object and place on the gray plate.

• 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 92 distinct subtasks:

1. Place the tape on the gray plate with the left gripper (Index: 0)
2. Grasp the blue pot with the left gripper (Index: 1)
3. Grasp the plugboard with the left gripper (Index: 2)
4. Grasp the potato chips with the right gripper (Index: 3)
5. Grasp the banana with the left gripper (Index: 4)
6. Place the round wooden block on the gray plate with the left gripper (Index: 5)
7. Place the peach on the gray plate with the left gripper (Index: 6)
8. Grasp the compasses with the right gripper (Index: 7)
9. Place the square chewing gum on the gray plate with the right gripper (Index: 8)
10. Place the compasses on the gray plate with the right gripper (Index: 9)
11. Place the potato chips on the gray plate with the right gripper (Index: 10)
12. Grasp the duck toy with the left gripper (Index: 11)
13. Place the green lemon on the gray plate with the right gripper (Index: 12)
14. Grasp the blue cup with the left gripper (Index: 13)
15. Place the square wooden block on the gray plate with the left gripper (Index: 14)
16. Grasp the soft facial cleanser with the left gripper (Index: 15)
17. Place the blue cup on the gray plate with the left gripper (Index: 16)
18. Grasp the square chewing gum with the left gripper (Index: 17)
19. Grasp the chocolate cake with the right gripper (Index: 18)
20. Grasp the shower sphere with the left gripper (Index: 19)
21. Place the blackboard erasure on the gray plate with the right gripper (Index: 20)
22. Grasp the plugboard with the right gripper (Index: 21)
23. Grasp the yogurt with the right gripper (Index: 22)
24. Grasp the brown towel with the left gripper (Index: 23)
25. Place the round bread on the gray plate with the right gripper (Index: 24)
26. Grasp the hard facial cleanser with the left gripper (Index: 25)
27. Place the shower sphere on the gray plate with the left gripper (Index: 26)
28. Grasp the chocolate with the right gripper (Index: 27)
29. Place the soft facial cleanser on the gray plate with the left gripper (Index: 28)
30. Grasp the peach with the right gripper (Index: 29)
31. Grasp the brown towel with the right gripper (Index: 30)
32. Place the shower sphere on the gray plate with the right gripper (Index: 31)
33. Grasp the back scratcher with the left gripper (Index: 32)
34. Place the square wooden block on the gray plate with the right gripper (Index: 33)
35. Place the blackboard erasure on the gray plate with the left gripper (Index: 34)
36. Place the yogurt on the gray plate with the right gripper (Index: 35)
37. Grasp the peach with the left gripper (Index: 36)
38. Place the coke on the gray plate with the left gripper (Index: 37)
39. Place the chocolate cake on the gray plate with the right gripper (Index: 38)
40. Place the banana on the gray plate with the left gripper (Index: 39)
41. Grasp the green lemon with the right gripper (Index: 40)
42. Grasp the bread slice with the right gripper (Index: 41)
43. Place the bread slice on the gray plate with the right gripper (Index: 42)
44. Place the brown towel on the gray plate with the right gripper (Index: 43)
45. Grasp the potato chips with the left gripper (Index: 44)
46. Grasp the duck toy with the right gripper (Index: 45)
47. End (Index: 46)
48. Grasp the blackboard erasure with the left gripper (Index: 47)
49. Grasp the coke with the left gripper (Index: 48)
50. Place the plugboard on the gray plate with the right gripper (Index: 49)
51. Place the round bread on the gray plate with the left gripper (Index: 50)
52. Grasp the round wooden block with the left gripper (Index: 51)
53. Grasp the compasses with the left gripper (Index: 52)
54. Place the round wooden block on the gray plate with the right gripper (Index: 53)
55. Place the blue pot on the gray plate with the left gripper (Index: 54)
56. Grasp the blue pot with the right gripper (Index: 55)
57. Grasp the round bread with the right gripper (Index: 56)
58. Grasp the chocolate cake with the left gripper (Index: 57)
59. Place the brown towel on the gray plate with the left gripper (Index: 58)
60. Place the blue pot on the gray plate with the right gripper (Index: 59)
61. Place the compasses on the gray plate with the left gripper (Index: 60)
62. Place the coke on the gray plate with the right gripper (Index: 61)
63. Grasp the tin with the right gripper (Index: 62)
64. Place the square chewing gum on the gray plate with the left gripper (Index: 63)
65. Place the back scratcher on the gray plate with the left gripper (Index: 64)
66. Grasp the tape with the right gripper (Index: 65)
67. Place the tin on the gray plate with the right gripper (Index: 66)
68. Grasp the coke with the right gripper (Index: 67)
69. Grasp the tape with the left gripper (Index: 68)
70. Grasp the square chewing gum with the right gripper (Index: 69)
71. Place the tape on the gray plate with the right gripper (Index: 70)
72. Place the hard facial cleanser on the gray plate with the left gripper (Index: 71)
73. Grasp the shower sphere with the right gripper (Index: 72)
74. Place the duck toy on the gray plate with the right gripper (Index: 73)
75. Grasp the bread slice with the left gripper (Index: 74)
76. Place the chocolate on the gray plate with the right gripper (Index: 75)
77. Grasp the blackboard erasure with the right gripper (Index: 76)
78. Place the banana on the gray plate with the right gripper (Index: 77)
79. Place the peach on the gray plate with the right gripper (Index: 78)
80. Grasp the round bread with the left gripper (Index: 79)
81. Grasp the square wooden block with the left gripper (Index: 80)
82. Grasp the blue cup with the right gripper (Index: 81)
83. Place the chocolate cake on the gray plate with the left gripper (Index: 82)
84. Place the duck toy on the gray plate with the left gripper (Index: 83)
85. Grasp the square wooden block with the right gripper (Index: 84)
86. Place the plugboard on the gray plate with the left gripper (Index: 85)
87. Place the bread slice on the gray plate with the left gripper (Index: 86)
88. Grasp the round wooden block with the right gripper (Index: 87)
89. Place the potato chips on the gray plate with the left gripper (Index: 88)
90. Grasp the banana with the right gripper (Index: 89)
91. Place the blue cup on the gray plate with the right gripper (Index: 90)
92. null (Index: 91)

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	102
Total Frames	20357
Total Tasks	92
Total Videos	408
Total Chunks	1
Chunk Size	1000
FPS	30
State Dimensions	14
Action Dimensions	14
Camera Views	4
Dataset Size	786.26 MB

Data Splits

The dataset is organized into the following splits:

• Training: Episodes 0:101

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_storage_object_gray_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
|       `-- ... (90 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