Agilex_Cobot_Magic_storage_object

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: 99

• Total Frames: 49237

• FPS: 30

• Dataset Size: 855.52 MB

• Robot Name: Agilex_Cobot_Magic

• End-Effector Type: two_finger_gripper

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

• Sensors: cam_head_rgb, cam_left_wrist_rgb, cam_right_wrist_rgb

• Camera Information: cam_head_rgb; cam_left_wrist_rgb; cam_right_wrist_rgb

• Scene: household->living_room

• Objects: white_table_cloths(unknown), table(unknown), apple(unknown), yellow_lemon(unknown), pomegranate(unknown), bread_dough(unknown), waffle(unknown), green_lemon(unknown), eggplant(unknown), chewing_gum(unknown), chocolate(unknown), mango(unknown), chewing_gum(unknown), mint_candy(unknown), mangosteen(unknown), orange(unknown), bread(unknown), banana(unknown), cake(unknown), beef_cheeseburger(unknown), bowl(unknown), pan(unknown), small_teapot(unknown), small_teacup(unknown), paper_ball(unknown), brown_square_towel(unknown), black_cylindrical_pen_holder(unknown), pink_long_towel(unknown), whiteboard_eraser(unknown), mentholatum_facial_cleanser(unknown), duck(unknown), compass(unknown), bowl(unknown), blue_long_towel(unknown), pearMint candy(unknown), mint_candy(unknown), triangular_bread(unknown), long_bread(unknown), chinese_cabbage(unknown), peach(unknown), can(unknown), bathing_in_flowers(unknown), wok(unknown), red_bull_canned_drink(unknown), eyeglass_case(unknown), coke (Slim Can)(unknown), wahaha_AD_calcium(unknown), brave_the_world_beer(unknown), brave_the_world_beer(unknown), shampoo(unknown), cleanser(unknown), sausage(unknown), french_fries(unknown), purple_trash_bag(unknown), red_date(unknown)

• Task Description: pick up an item with a gripper and place it in a random container on the table.

Primary Task Instruction

pick up an item with a gripper and place it in a random container on the table.

Robot Configuration

• Robot Name: Agilex_Cobot_Magic
• 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

• white_table_cloths(unknown)
• table(unknown)
• apple(unknown)
• yellow_lemon(unknown)
• pomegranate(unknown)
• bread_dough(unknown)
• waffle(unknown)
• green_lemon(unknown)
• eggplant(unknown)
• chewing_gum(unknown)
• chocolate(unknown)
• mango(unknown)
• chewing_gum(unknown)
• mint_candy(unknown)
• mangosteen(unknown)
• orange(unknown)
• bread(unknown)
• banana(unknown)
• cake(unknown)
• beef_cheeseburger(unknown)
• bowl(unknown)
• pan(unknown)
• small_teapot(unknown)
• small_teacup(unknown)
• paper_ball(unknown)
• brown_square_towel(unknown)
• black_cylindrical_pen_holder(unknown)
• pink_long_towel(unknown)
• whiteboard_eraser(unknown)
• mentholatum_facial_cleanser(unknown)
• duck(unknown)
• compass(unknown)
• bowl(unknown)
• blue_long_towel(unknown)
• pearMint candy(unknown)
• mint_candy(unknown)
• triangular_bread(unknown)
• long_bread(unknown)
• chinese_cabbage(unknown)
• peach(unknown)
• can(unknown)
• bathing_in_flowers(unknown)
• wok(unknown)
• red_bull_canned_drink(unknown)
• eyeglass_case(unknown)
• coke (Slim Can)(unknown)
• wahaha_AD_calcium(unknown)
• brave_the_world_beer(unknown)
• brave_the_world_beer(unknown)
• shampoo(unknown)
• cleanser(unknown)
• sausage(unknown)
• french_fries(unknown)
• purple_trash_bag(unknown)
• red_date(unknown)

Task Descriptions

• Standardized Task Description: pick up an item with a gripper and place it in a random container on the table.

• 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 141 distinct subtasks:

1. Grasp the pink towel with the right gripper (Index: 0)
2. Place the XX into the purple pot with the left gripper (Index: 1)
3. Grasp the yellow lemon with the right gripper (Index: 2)
4. Grasp the AD milk with the left gripper (Index: 3)
5. Place the plush banana into the pink bowl with the left gripper (Index: 4)
6. Place the beer into the purple pot with the right gripper (Index: 5)
7. Place the green lemon into the pink bowl with the right gripper (Index: 6)
8. Grasp the red bull with the right gripper (Index: 7)
9. Grasp the beer with the right gripper (Index: 8)
10. Place the hollow ring bread into the red pot with the left gripper (Index: 9)
11. Grasp the banana with the left gripper (Index: 10)
12. Place the yellow lemon into the pink bowl with the left gripper (Index: 11)
13. Place the yellow lemon into the blue bowl with the right gripper (Index: 12)
14. Grasp the pink laundry detergent with the left gripper (Index: 13)
15. Place the eggplant into the purple pot with the right gripper (Index: 14)
16. Grasp the apple with the right gripper (Index: 15)
17. Place the peach into the red pot with the left gripper (Index: 16)
18. Place the red bull into the blue bowl with the left gripper (Index: 17)
19. Place the blue garbage bag into the pen container with the right gripper (Index: 18)
20. Grasp the shampoo with the right gripper (Index: 19)
21. Place the plush banana into the pink bowl with the right gripper (Index: 20)
22. Place the banana into the red pot with the left gripper (Index: 21)
23. Place the apple into the red pot with the left gripper (Index: 22)
24. Place the round chewing gum into the pen container with the left gripper (Index: 23)
25. Place the beer into the pink pot with the left gripper (Index: 24)
26. Place the yellow cake into the pink bowl with the left gripper (Index: 25)
27. Place the tin into the red pot with the right gripper (Index: 26)
28. Place the blue garbage bag into the purple pot with the left gripper (Index: 27)
29. Place the croissant into the purple pot with the right gripper (Index: 28)
30. Place the shampoo into the blue bowl with the left gripper (Index: 29)
31. Grasp the yellow lemon with the left gripper (Index: 30)
32. Place the eyeglass case into the purple pot with the right gripper (Index: 31)
33. Grasp the white blackboard erasure with the left gripper (Index: 32)
34. Place the yogurt into the pink bowl with the right gripper (Index: 33)
35. Place the blue garbage bag into the pink pot with the right gripper (Index: 34)
36. Place the green lemon into the blue bowl with the left gripper (Index: 35)
37. Place the apple into the pink pot with the left gripper (Index: 36)
38. Grasp the eyeglass case with the right gripper (Index: 37)
39. Place the yellow cake into the blue bowl with the left gripper (Index: 38)
40. Place the red bull into the pen container with the right gripper (Index: 39)
41. Place the croissant into the pink bowl with the left gripper (Index: 40)
42. Grasp the shower sphere with the left gripper (Index: 41)
43. Grasp the yogurt with the right gripper (Index: 42)
44. Grasp the croissant with the left gripper (Index: 43)
45. Grasp the tin with the left gripper (Index: 44)
46. Grasp the long bread with the right gripper (Index: 45)
47. Grasp the hard facial cleanser with the left gripper (Index: 46)
48. Place the mango into the pink bowl with the left gripper (Index: 47)
49. Grasp the plush banana with the left gripper (Index: 48)
50. Place the pink laundry detergent into the pen container with the left gripper (Index: 49)
51. Place the soft facial cleanser into the pink bowl with the right gripper (Index: 50)
52. Grasp the peach with the right gripper (Index: 51)
53. Grasp the mango with the left gripper (Index: 52)
54. Place the round chewing gum into the pink pot with the left gripper (Index: 53)
55. Place the white blackboard erasure into the pink bowl with the left gripper (Index: 54)
56. Place the peach into the pink bowl with the left gripper (Index: 55)
57. Grasp the pear with the left gripper (Index: 56)
58. Place the tin into the pink pot with the left gripper (Index: 57)
59. Place the cleaning agent into the pen container with the left gripper (Index: 58)
60. Place the shampoo into the blue bowl with the right gripper (Index: 59)
61. Grasp the hollow ring bread with the right gripper (Index: 60)
62. Place the shower sphere into the pink bowl with the right gripper (Index: 61)
63. Place the pear into the purple pot with the left gripper (Index: 62)
64. Place the round chewing gum into the pen container with the right gripper (Index: 63)
65. Grasp the peach with the left gripper (Index: 64)
66. Grasp the long bread with the left gripper (Index: 65)
67. Grasp the eggplant with the right gripper (Index: 66)
68. Place the blue garbage bag into the pink bowl with the right gripper (Index: 67)
69. Place the croissant into the red pot with the left gripper (Index: 68)
70. Grasp the green lemon with the right gripper (Index: 69)
71. Place the beer into the blue bowl with the left gripper (Index: 70)
72. Place the shampoo into the purple pot with the right gripper (Index: 71)
73. Grasp the shampoo with the left gripper (Index: 72)
74. Place the pink towel into the red pot with the left gripper (Index: 73)
75. Place the peach into the purple pot with the right gripper (Index: 74)
76. End (Index: 75)
77. Place the mint candy into the pink bowl with the right gripper (Index: 76)
78. Place the eggplant into the pen container with the right gripper (Index: 77)
79. Grasp the beer with the left gripper (Index: 78)
80. Place the AD milk into the pen container with the left gripper (Index: 79)
81. Place the banana into the pink bowl with the left gripper (Index: 80)
82. **Grasp the tin with the right gripper ** (Index: 81)
83. Place the tin into the pink pot with the right gripper (Index: 82)
84. Place the AD milk into the pink pot with the left gripper (Index: 83)
85. Place the shower sphere into the purple pot with the right gripper (Index: 84)
86. Place the long bread into the red pot with the left gripper (Index: 85)
87. Grasp the yellow cake with the right gripper (Index: 86)
88. Grasp the croissant with the right gripper (Index: 87)
89. Grasp the red bull with the left gripper (Index: 88)
90. Place the peach into the pink bowl with the right gripper (Index: 89)
91. Place the tin into the pen container with the right gripper (Index: 90)
92. Place the long bread into the purple pot with the right gripper (Index: 91)
93. Place the orange into the pink pot with the left gripper (Index: 92)
94. Place the yellow cake into the blue bowl with the right gripper (Index: 93)
95. Grasp the pink towel with the left gripper (Index: 94)
96. Place the croissant into the pink bowl with the right gripper (Index: 95)
97. Place the hard facial cleanser into the pink bowl with the left gripper (Index: 96)
98. Place the round chewing gum into the red pot with the right gripper (Index: 97)
99. Grasp the blue garbage bag with the right gripper (Index: 98)
100. Grasp the tin with the right gripper (Index: 99)
101. Grasp the orange with the left gripper (Index: 100)
102. Grasp the blue garbage bag with the left gripper (Index: 101)
103. Place the shower sphere into the pink bowl with the left gripper (Index: 102)
104. Place the yogurt into the red pot with the right gripper (Index: 103)
105. Place the peach into the pink pot with the right gripper (Index: 104)
106. Grasp the hollow ring bread with the left gripper (Index: 105)
107. Grasp the apple with the left gripper (Index: 106)
108. Place the tin into the red pot with the left gripper (Index: 107)
109. Place the beer into the red pot with the left gripper (Index: 108)
110. Place the blue garbage bag into the pink bowl with the left gripper (Index: 109)
111. Place the mango into the purple pot with the right gripper (Index: 110)
112. Place the tin into the blue bowl with the left gripper (Index: 111)
113. Place the apple into the blue bowl with the left gripper (Index: 112)
114. Grasp the shower sphere with the right gripper (Index: 113)
115. Place the red bull into the pink bowl with the left gripper (Index: 114)
116. Grasp the yellow cake with the left gripper (Index: 115)
117. Grasp the round chewing gum with the right gripper (Index: 116)
118. Grasp the cleaning agent with the left gripper (Index: 117)
119. Place the coke into the pink pot with the left gripper (Index: 118)
120. Place the pink towelinto the pink bowl with the right gripper (Index: 119)
121. Grasp the round chewing gum with the left gripper (Index: 120)
122. Place the green lemon into the purple pot with the left gripper (Index: 121)
123. Place the hollow ring bread into the purple pot with the right gripper (Index: 122)
124. Place the peach into the purple pot with the left gripper (Index: 123)
125. Place the yellow cake into the pen container with the right gripper (Index: 124)
126. Place the apple into the pink pot with the right gripper (Index: 125)
127. Place the red bull into the pink pot with the right gripper (Index: 126)
128. Place the tin into the purple pot with the left gripper (Index: 127)
129. Place the yellow lemon into the pink bowl with the right gripper (Index: 128)
130. Grasp the mango with the right gripper (Index: 129)
131. Place the banana into the red pot with the right gripper (Index: 130)
132. Grasp the mint candy with the right gripper (Index: 131)
133. Place the apple into the pink bowl with the left gripper (Index: 132)
134. Grasp the soft facial cleanser with the right gripper (Index: 133)
135. Grasp the green lemon with the left gripper (Index: 134)
136. Place the red bull into the red pot with the left gripper (Index: 135)
137. Grasp the coke with the left gripper (Index: 136)
138. Place the cleaning agent into the pink bowl with the left gripper (Index: 137)
139. Grasp the banana with the right gripper (Index: 138)
140. Grasp the plush banana with the right gripper (Index: 139)
141. null (Index: 140)

Atomic Actions

• grasp
• lift
• lower

Hardware and Sensors

Sensors

• cam_head_rgb

• cam_left_wrist_rgb

• cam_right_wrist_rgb

Camera Information

• cam_head_rgb: dtype=video, shape=480x640x3, resolution=640x480, codec=av1, pix_fmt=yuv420p

• cam_left_wrist_rgb: dtype=video, shape=480x640x3, resolution=640x480, codec=av1, pix_fmt=yuv420p

• cam_right_wrist_rgb: dtype=video, shape=480x640x3, resolution=640x480, codec=av1, pix_fmt=yuv420p

Coordinate System

• Definition: right-hand-frame

Dimensions & Units

• Joint Rotation: radian
• End-Effector Rotation: radian
• End-Effector Translation: meter

Dataset Statistics

Metric	Value
Total Episodes	99
Total Frames	49237
Total Tasks	141
Total Videos	297
Total Chunks	1
Chunk Size	1000
FPS	30
State Dimensions	26
Action Dimensions	26
Camera Views	3
Dataset Size	855.52 MB

Data Splits

The dataset is organized into the following splits:

• Training: Episodes 0:98

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)

Agilex_Cobot_Magic_storage_object_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
|-- backup
|   |-- data
|   |   `-- chunk-000
|   `-- meta
|       |-- episodes.jsonl
|       |-- episodes_stats.jsonl
|       |-- info.json
|       `-- tasks.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
|       `-- ... (87 more entries)
|-- meta
|   |-- episodes.jsonl
|   |-- episodes_stats.jsonl
|   |-- info.json
|   `-- tasks.jsonl
|-- videos
|   `-- chunk-000
|       |-- observation.images.cam_head_rgb
|       |-- observation.images.cam_left_wrist_rgb
|       `-- observation.images.cam_right_wrist_rgb
|-- info.yaml
`-- README.md

Camera Views

This dataset includes 3 camera views: cam_head_rgb, cam_left_wrist_rgb, cam_right_wrist_rgb.

Features (Full YAML)

observation.images.cam_head_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
  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_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
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

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