RoboCOIN
Collection
RoboCOIN
•
408 items
•
Updated
•
2
Search is not available for this dataset
observation.state
listlengths 14
14
| action
listlengths 14
14
| timestamp
float32 0
85.7
| frame_index
int64 0
2.57k
| episode_index
int64 0
136
| index
int64 0
198k
| task_index
int64 0
0
| subtask_annotation
listlengths 5
5
| scene_annotation
listlengths 1
1
| eef_direction_state
listlengths 2
2
| eef_velocity_state
listlengths 2
2
| eef_acc_mag_state
listlengths 2
2
| eef_direction_action
listlengths 2
2
| eef_velocity_action
listlengths 2
2
| eef_acc_mag_action
listlengths 2
2
| eef_sim_pose_state
listlengths 12
12
| eef_sim_pose_action
listlengths 12
12
| gripper_mode_state
listlengths 2
2
| gripper_activity_state
listlengths 2
2
| gripper_mode_action
listlengths 2
2
| gripper_activity_action
listlengths 2
2
| gripper_open_scale_state
listlengths 2
2
| gripper_open_scale_action
listlengths 2
2
|
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in Data Studio
R1_Lite_wash_the_tableware
📋 Overview
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Robot Type: galaxea_r1_lite
| Codebase Version: v2.1
End-Effector Type: two_finger_gripper
🏠 Scene Types
This dataset covers the following scene types:
home
🤖 Atomic Actions
This dataset includes the following atomic actions:
grasppickplace
📊 Dataset Statistics
| Metric | Value |
|---|---|
| Total Episodes | 137 |
| Total Frames | 197672 |
| Total Tasks | 1 |
| Total Videos | 411 |
| Total Chunks | 1 |
| Chunk Size | 1000 |
| FPS | 30 |
| Dataset Size | 7.3GB |
👥 Authors
Contributors
This dataset is contributed by:
- RoboCOIN - RoboCOIN Team
🔗 Links
- 🏠 Homepage: https://flagopen.github.io/RoboCOIN/
- 📄 Paper: https://arxiv.org/abs/2511.17441
- 💻 Repository: https://github.com/FlagOpen/RoboCOIN
- 🌐 Project Page: https://flagopen.github.io/RoboCOIN/
- 🐛 Issues: https://github.com/FlagOpen/RoboCOIN/issues
- 📜 License: apache-2.0
🏷️ Dataset Tags
RoboCOINLeRobot
🎯 Task Descriptions
Primary Tasks
turn on faucet put tableware in sink rinse then back.
Sub-Tasks
This dataset includes 41 distinct subtasks:
- Grasp yellow bowl with right gripper
- Pick up the bowl
- Open the dispenser valve with right gripper
- End
- Rinse the chopsticks
- Put the chopsticks into the sink
- Place the chopsticks on the table
- Put a spoon back to the table from the sink
- Put a bowl back to the table from the sink
- Place pink bowl into the sink with right gripper
- Rinse the plate
- Wait for the water to rinse the bowl
- Place a chopstick into the sink with right gripper
- Put a bowl into the sink
- Rinse the bowl
- Place a chopstick on the bowl with right gripper
- Place the plate on the table
- Pour the water from the yellow bowl into the sink with right gripper
- Place the bowl on the table
- Pick up the chopsticks
- Put the chopsticks back to the table from the sink
- Put a spoon into the sink
- Pour the water from the pink bowl into the sink with right gripper
- Place the chopsticks on the bowl
- Abnormal
- Pick up the spoon
- Rinse the spoon
- Place yellow bowl on the table with right gripper
- Place yellow bowl into the sink with right gripper
- Place the spoon on the plate
- Put a plate back to the table from the sink
- Turn off the faucet
- Pick up the plate
- Place the spoon on the bowl
- Close the dispenser valve with right gripper
- Grasp a chopstick with right gripper
- Grasp pink bowl with right gripper
- Turn on the faucet
- Place pink bowl on the table with right gripper
- Put a plate into the sink
- 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 0:136
📁 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 1 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": "galaxea_r1_lite", "total_episodes": 137, "total_frames": 197672, "total_tasks": 1, "total_videos": 411, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": {"train": "0:136"}, "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": [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", "left_gripper_open", "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"]}, "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", "left_gripper_open", "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"]}, "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):
R1_Lite_wash_the_tableware_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
│ └── (...)
├── 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
└── (...)
📞 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:
- LeRobot Framework: https://github.com/huggingface/lerobot
📌 Version Information
Version History
- v1.0.0 (2025-11): Initial release
- Downloads last month
- 590
Size of downloaded dataset files:
39.3 MB
Size of the auto-converted Parquet files:
39.3 MB
Number of rows:
197,672