Galaxea_R1_Lite_classify_object_green_tablecloth

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: 224

• Total Frames: 251221

• FPS: 30

• Dataset Size: 25.62 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), green_table_cloths(unknown)

• Task Description: on the green table,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

on the green table,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)
• green_table_cloths(unknown)

Task Descriptions

• Standardized Task Description: on the green table,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 158 distinct subtasks:

1. Grasp the round bread and put it in the right basket (Index: 0)
2. Grasp the can and put it in the right basket (Index: 1)
3. Pick up the compass and put it in the left basket (Index: 2)
4. Grasp the soft cleanser and put it in the left basket (Index: 3)
5. Pick up the orange and put it in the right basket (Index: 4)
6. Pick up the round chewing gum and put it in the right basket (Index: 5)
7. Grasp the playing cards and put it in the left basket (Index: 6)
8. Grasp the purple garbage bag and put it in the left basket (Index: 7)
9. Place the back scratcher in the center of the table (Index: 8)
10. Place the eggplant in the center of the table (Index: 9)
11. Pick up the square chewing gum and put it in the right basket (Index: 10)
12. Pick up the washing liquid and put it in the left basket (Index: 11)
13. Grasp the red pot and put it in the left basket (Index: 12)
14. Grasp the grape and put it in the right basket (Index: 13)
15. Pick up the tape and put it in the left basket (Index: 14)
16. Pick up the shampoo and put it in the left basket (Index: 15)
17. Pick up the playing cards and put it in the left basket (Index: 16)
18. Place the orange in the center of the table (Index: 17)
19. Grasp the eggplant and put it in the right basket (Index: 18)
20. Pick up the banana and put it in the right basket (Index: 19)
21. Grasp the washing liquid and put it in the left basket (Index: 20)
22. Grasp the shampoo and put it in the left basket (Index: 21)
23. Place the pink bowl in the center of the table (Index: 22)
24. Place the compass in the center of the table (Index: 23)
25. Place the peach in the center of the table (Index: 24)
26. Place the banana in the center of the table (Index: 25)
27. Place the tape in the center of the table (Index: 26)
28. Pick up the round bread and put it in the left basket (Index: 27)
29. Pick up the tea cup and put it in the left basket (Index: 28)
30. Pick up the round bread and put it in the right basket (Index: 29)
31. Grasp the banana and put it in the right basket (Index: 30)
32. Grasp the pear and put it in the right basket (Index: 31)
33. Place the lemon and put it in the center of the table (Index: 32)
34. Grasp the compass and put it in the right basket (Index: 33)
35. Pick up the can and put it in the right basket (Index: 34)
36. Place the red pot in the center of the table (Index: 35)
37. Pick up the yellow marker and put it in the left basket (Index: 36)
38. Grasp the yellow cake and put it in the right basket (Index: 37)
39. Grasp the long bread and put it in the right basket (Index: 38)
40. Grasp the canned cola and put it in the right basket (Index: 39)
41. Grasp the glasses case and put it in the left basket (Index: 40)
42. Pick up the lime and put it in the right basket (Index: 41)
43. Pick up the pear and put it in the right basket (Index: 42)
44. Grasp the green chewing gum and put it in the right basket (Index: 43)
45. Pick up the croissant and put it in the right basket (Index: 44)
46. Pick up the chinese cabbage and put it in the right basket (Index: 45)
47. Place the fruit fudge in the center of the table (Index: 46)
48. Grasp the white eraser and put it in the left basket (Index: 47)
49. Place the yellow marker in the center of the table (Index: 48)
50. Place the round chewing gum in the center of the table (Index: 49)
51. Pick up the canned cola and put it in the right basket (Index: 50)
52. Pick up the red pot and put it in the left basket (Index: 51)
53. Place the green lemon in the center of the table (Index: 52)
54. Grasp the pink marker and put it in the left basket (Index: 53)
55. Place the washing liquid in the center of the table (Index: 54)
56. Abnormal (Index: 55)
57. Grasp the peach and put it in the right basket (Index: 56)
58. Grasp the soap and put it in the left basket (Index: 57)
59. Place the Red Bull in the center of the table (Index: 58)
60. Place the mango in the center of the table (Index: 59)
61. Grasp the fruit fudge and put it in the right basket (Index: 60)
62. Grasp the bath ball and put it in the left basket (Index: 61)
63. Grasp the red bull and put it in the right basket (Index: 62)
64. Pick up the lemon and put it in the right basket (Index: 63)
65. Grasp the chinese cabbage and put it in the right basket (Index: 64)
66. Grasp the pink pot and put it in the left basket (Index: 65)
67. Grasp the croissant and put it in the right basket (Index: 66)
68. Grasp the soda water and put it in the right basket (Index: 67)
69. Pick up the egg yolk pastry and put it in the right basket (Index: 68)
70. Grasp the spoon and put it in the left basket (Index: 69)
71. Grasp the blue cup and put it in the left basket (Index: 70)
72. Place the blue towel in the center of the table (Index: 71)
73. Place the yellow cake in the center of the table (Index: 72)
74. Place the grey cup in the center of the table (Index: 73)
75. Grasp the tape and put it in the left basket (Index: 74)
76. Place the square chewing gum in the center of the table (Index: 75)
77. Pick up the milk and put it in the right basket (Index: 76)
78. Grasp the back scratcher and put it in the right basket (Index: 77)
79. Grasp the yogurt and put it in the right basket (Index: 78)
80. Pick up the yellow cake and put it in the right basket (Index: 79)
81. Pick up the blue bowl and put it in the left basket (Index: 80)
82. Grasp the lemon and put it in the right basket (Index: 81)
83. Grasp the back scratcher and put it in the left basket (Index: 82)
84. Grasp the orange and put it in the right basket (Index: 83)
85. Pick up the soda water and put it in the right basket (Index: 84)
86. Grasp the red pot and put it in the right basket (Index: 85)
87. Grasp the milk and put it in the right basket (Index: 86)
88. Pick up the blue cup and put it in the left basket (Index: 87)
89. Pick up the mango and put it in the right basket (Index: 88)
90. Place the pink marker in the center of the table (Index: 89)
91. Grasp the grey cup and put it in the left basket (Index: 90)
92. Pick up the long bread and put it in the right basket (Index: 91)
93. Pick up the soap and put it in the left basket (Index: 92)
94. Grasp the peach and put it in the left basket (Index: 93)
95. Pick up the pink pot and put it in the left basket (Index: 94)
96. Grasp the sausage and put it in the right basket (Index: 95)
97. Pick up the yogurt and put it in the right basket (Index: 96)
98. Place the bath ball in the center of the table (Index: 97)
99. Grasp the square chewing gum and put it in the right basket (Index: 98)
100. Grasp the ad milk and put it in the right basket (Index: 99)
101. Place the pink pot in the center of the table (Index: 100)
102. Grasp the compass and put it in the left basket (Index: 101)
103. Place the glasses case in the center of the table (Index: 102)
104. Place the gray towel in the center of the table (Index: 103)
105. Pick up the back scratcher and put it in the left basket (Index: 104)
106. Place the purple garbage bag in the center of the table (Index: 105)
107. Place the blue cup in the center of the table (Index: 106)
108. Pick up the blue towel and put it in the left basket (Index: 107)
109. Place the pear in the center of the table (Index: 108)
110. Place the soft cleanser in the center of the table (Index: 109)
111. Grasp the egg yolk pastry and put it in the right basket (Index: 110)
112. Pick up the spoon and put it in the left basket (Index: 111)
113. Place the sausage in the center of the table (Index: 112)
114. Place the green chewing gum in the center of the table (Index: 113)
115. Pick up the peach and put it in the right basket (Index: 114)
116. Place the can in the center of the table (Index: 115)
117. Grasp the mango and put it in the right basket (Index: 116)
118. Place the canned cola in the center of the table (Index: 117)
119. Pick up the gray towel and put it in the left basket (Index: 118)
120. Place the ad milk in the center of the table (Index: 119)
121. Pick up the sausage and put it in the right basket (Index: 120)
122. Grasp the hard cleanser and put it in the left basket (Index: 121)
123. Pick up the pink marker and put it in the left basket (Index: 122)
124. Grasp the detergent and put it in the left basket (Index: 123)
125. Pick up the pink bowl and put it in the left basket (Index: 124)
126. Grasp the Red Bull and put it in the right basket (Index: 125)
127. Pick up the ad milk and put it in the right basket (Index: 126)
128. Place the long bread in the center of the table (Index: 127)
129. Pick up the soft cleanser and put it in the left basket (Index: 128)
130. Place the croissant in the center of the table (Index: 129)
131. Grasp the lime and put it in the right basket (Index: 130)
132. Place the round bread in the center of the table (Index: 131)
133. Pick up the green chewing gum and put it in the right basket (Index: 132)
134. Grasp the pink bowl and put it in the left basket (Index: 133)
135. Place the playing cards in the center of the table (Index: 134)
136. Pick up the glasses case and put it in the left basket (Index: 135)
137. Pick up the fruit fudge and put it in the right basket (Index: 136)
138. Pick up the eggplant and put it in the right basket (Index: 137)
139. Place the white eraser in the center of the table (Index: 138)
140. Place the yogurt in the center of the table (Index: 139)
141. Pick up the detergent and put it in the left basket (Index: 140)
142. Grasp the blue towel and put it in the left basket (Index: 141)
143. Pick up the red bull and put it in the right basket (Index: 142)
144. Place the lime in the center of the table (Index: 143)
145. Grasp the mint candy and put it in the right basket (Index: 144)
146. Place the soap in the center of the table (Index: 145)
147. Grasp the red marker and put it in the left basket (Index: 146)
148. Pick up the purple garbage bag and put it in the left basket (Index: 147)
149. Place the detergent in the center of the table (Index: 148)
150. Pick up the bath ball and put it in the left basket (Index: 149)
151. Grasp the gray towel and put it in the left basket (Index: 150)
152. Grasp the yellow marker and put it in the left basket (Index: 151)
153. Grasp the pink towel and put it in the left basket (Index: 152)
154. End (Index: 153)
155. Place the shampoo in the center of the table (Index: 154)
156. Grasp the green lemon and put it in the right basket (Index: 155)
157. Grasp the round chewing gum and put it in the right basket (Index: 156)
158. null (Index: 157)

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=360x640x3, resolution=640x360, codec=av1, pix_fmt=yuv420p

• cam_right_wrist_rgb: dtype=video, shape=360x640x3, resolution=640x360, 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	224
Total Frames	251221
Total Tasks	158
Total Videos	896
Total Chunks	1
Chunk Size	1000
FPS	30
State Dimensions	14
Action Dimensions	14
Camera Views	4
Dataset Size	25.62 GB

Data Splits

The dataset is organized into the following splits:

• Training: Episodes 0:223

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_Galaxea_R1_Lite_classify_object_green_tablecloth_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
|       `-- ... (212 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:
  - 360
  - 640
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 360
    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:
  - 360
  - 640
  - 3
  names:
  - height
  - width
  - channels
  info:
    video.height: 360
    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:
  - 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