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leju_robot_moving_parts_g
π Overview
This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.
Robot Type: leju_robot
| Codebase Version: v2.1
End-Effector Type: five_finger_hand
π Scene Types
This dataset covers the following scene types:
home
π€ Atomic Actions
This dataset includes the following atomic actions:
graspplacepick
π Dataset Statistics
| Metric | Value |
|---|---|
| Total Episodes | 157 |
| Total Frames | 225345 |
| Total Tasks | 1 |
| Total Videos | 471 |
| Total Chunks | 1 |
| Chunk Size | 1000 |
| FPS | 30 |
| Dataset Size | 13.8GB |
π₯ Authors
Contributors
This dataset is contributed by:
- RoboCOIN - RoboCOIN Team
π Links
- π Homepage: https://flagopen.github.io/RoboCOIN/
- π Paper: https://arxiv.org/abs/2511.17441
- π» Repository: https://github.com/FlagOpen/RoboCOIN
- π Project Page: https://flagopen.github.io/RoboCOIN/
- π Issues: https://github.com/FlagOpen/RoboCOIN/issues
- π License: apache-2.0
π·οΈ Dataset Tags
RoboCOINLeRobot
π― Task Descriptions
Primary Tasks
take the parts from the cabinet and place them on the table.
Sub-Tasks
This dataset includes 11 distinct subtasks:
- End
- Grasp the white part with left gripper
- Grasp the white part with right gripper
- Insert the small component into the corresponding slot on the workbench.
- Move the small component to the workbench.
- Move to the table behind body
- null
- Pick up the small component from the shelf.
- Place the white part on the table with left gripper
- Place the white part on the table with right gripper
- Return to the initial position at the workbench.
π₯ Camera Views
This dataset includes 3 camera views.
π·οΈ 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
π Data Splits
The dataset is organized into the following splits:
- Training: Episodes 0:156
π 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.camera_head_rgb: video
- FPS: 30
- Codec: av1- observation.images.camera_left_wrist_rgb: video
- FPS: 30
- Codec: av1- observation.images.camera_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
Meta Information
The complete dataset metadata is available in meta/info.json:
{"codebase_version": "v2.1", "robot_type": "leju_robot", "total_episodes": 157, "total_frames": 225345, "total_tasks": 1, "total_videos": 471, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": {"train": "0:156"}, "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.camera_head_rgb": {"dtype": "video", "shape": [480, 848, 3], "names": ["height", "width", "channels"], "info": {"video.height": 480, "video.width": 848, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "video.fps": 30, "video.channels": 3, "has_audio": false}}, "observation.images.camera_left_wrist_rgb": {"dtype": "video", "shape": [480, 848, 3], "names": ["height", "width", "channels"], "info": {"video.height": 480, "video.width": 848, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "video.fps": 30, "video.channels": 3, "has_audio": false}}, "observation.images.camera_right_wrist_rgb": {"dtype": "video", "shape": [480, 848, 3], "names": ["height", "width", "channels"], "info": {"video.height": 480, "video.width": 848, "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": [118], "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_arm_joint_7_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_arm_joint_7_rad", "left_leg_joint_1_rad", "left_leg_joint_2_rad", "left_leg_joint_3_rad", "left_leg_joint_4_rad", "left_leg_joint_5_rad", "left_leg_joint_6_rad", "right_leg_joint_1_rad", "right_leg_joint_2_rad", "right_leg_joint_3_rad", "right_leg_joint_4_rad", "right_leg_joint_5_rad", "right_leg_joint_6_rad", "left_hand_joint_1_rad", "left_hand_joint_2_rad", "left_hand_joint_3_rad", "left_hand_joint_4_rad", "left_hand_joint_5_rad", "left_hand_joint_6_rad", "right_hand_joint_1_rad", "right_hand_joint_2_rad", "right_hand_joint_3_rad", "right_hand_joint_4_rad", "right_hand_joint_5_rad", "right_hand_joint_6_rad", "head_joint_1_rad", "head_joint_2_rad", "left_arm_joint_1_vel_rad_s", "left_arm_joint_2_vel_rad_s", "left_arm_joint_3_vel_rad_s", "left_arm_joint_4_vel_rad_s", "left_arm_joint_5_vel_rad_s", "left_arm_joint_6_vel_rad_s", "left_arm_joint_7_vel_rad_s", "right_arm_joint_1_vel_rad_s", "right_arm_joint_2_vel_rad_s", "right_arm_joint_3_vel_rad_s", "right_arm_joint_4_vel_rad_s", "right_arm_joint_5_vel_rad_s", "right_arm_joint_6_vel_rad_s", "right_arm_joint_7_vel_rad_s", "left_arm_joint_1_eff_nm", "left_arm_joint_2_eff_nm", "left_arm_joint_3_eff_nm", "left_arm_joint_4_eff_nm", "left_arm_joint_5_eff_nm", "left_arm_joint_6_eff_nm", "left_arm_joint_7_eff_nm", "right_arm_joint_1_eff_nm", "right_arm_joint_2_eff_nm", "right_arm_joint_3_eff_nm", "right_arm_joint_4_eff_nm", "right_arm_joint_5_eff_nm", "right_arm_joint_6_eff_nm", "right_arm_joint_7_eff_nm", "left_leg_joint_1_vel_rad_s", "left_leg_joint_2_vel_rad_s", "left_leg_joint_3_vel_rad_s", "left_leg_joint_4_vel_rad_s", "left_leg_joint_5_vel_rad_s", "left_leg_joint_6_vel_rad_s", "right_leg_joint_1_vel_rad_s", "right_leg_joint_2_vel_rad_s", "right_leg_joint_3_vel_rad_s", "right_leg_joint_4_vel_rad_s", "right_leg_joint_5_vel_rad_s", "right_leg_joint_6_vel_rad_s", "left_leg_joint_1_eff_nm", "left_leg_joint_2_eff_nm", "left_leg_joint_3_eff_nm", "left_leg_joint_4_eff_nm", "left_leg_joint_5_eff_nm", "left_leg_joint_6_eff_nm", "right_leg_joint_1_eff_nm", "right_leg_joint_2_eff_nm", "right_leg_joint_3_eff_nm", "right_leg_joint_4_eff_nm", "right_leg_joint_5_eff_nm", "right_leg_joint_6_eff_nm", "head_joint_1_vel_rad_s", "head_joint_2_vel_rad_s", 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"left_leg_joint_4_rad", "left_leg_joint_5_rad", "left_leg_joint_6_rad", "right_leg_joint_1_rad", "right_leg_joint_2_rad", "right_leg_joint_3_rad", "right_leg_joint_4_rad", "right_leg_joint_5_rad", "right_leg_joint_6_rad", "left_hand_joint_1_rad", "left_hand_joint_2_rad", "left_hand_joint_3_rad", "left_hand_joint_4_rad", "left_hand_joint_5_rad", "left_hand_joint_6_rad", "right_hand_joint_1_rad", "right_hand_joint_2_rad", "right_hand_joint_3_rad", "right_hand_joint_4_rad", "right_hand_joint_5_rad", "right_hand_joint_6_rad", "head_joint_1_rad", "head_joint_2_rad", "left_arm_joint_1_vel_rad_s", "left_arm_joint_2_vel_rad_s", "left_arm_joint_3_vel_rad_s", "left_arm_joint_4_vel_rad_s", "left_arm_joint_5_vel_rad_s", "left_arm_joint_6_vel_rad_s", "left_arm_joint_7_vel_rad_s", "right_arm_joint_1_vel_rad_s", "right_arm_joint_2_vel_rad_s", "right_arm_joint_3_vel_rad_s", "right_arm_joint_4_vel_rad_s", "right_arm_joint_5_vel_rad_s", "right_arm_joint_6_vel_rad_s", "right_arm_joint_7_vel_rad_s"]}, "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]}}}
Directory Structure
The dataset is organized as follows (showing leaf directories with first 5 files only):
leju_robot_moving_parts_g_qced_hardlink/
βββ annotations/
β βββ eef_acc_mag_annotation.jsonl
β βββ eef_direction_annotation.jsonl
β βββ eef_velocity_annotation.jsonl
β βββ gripper_activity_annotation.jsonl
β βββ gripper_mode_annotation.jsonl
β βββ (...)
βββ data/
β βββ chunk-000/
β βββ episode_000000.parquet
β βββ episode_000001.parquet
β βββ episode_000002.parquet
β βββ episode_000003.parquet
β βββ episode_000004.parquet
β βββ (...)
βββ meta/
β βββ episodes.jsonl
β βββ episodes_stats.jsonl
β βββ info.json
β βββ tasks.jsonl
βββ videos/
βββ chunk-000/
βββ observation.images.camera_head_rgb/
β βββ episode_000000.mp4
β βββ episode_000001.mp4
β βββ episode_000002.mp4
β βββ episode_000003.mp4
β βββ episode_000004.mp4
β βββ (...)
βββ observation.images.camera_left_wrist_rgb/
β βββ episode_000000.mp4
β βββ episode_000001.mp4
β βββ episode_000002.mp4
β βββ episode_000003.mp4
β βββ episode_000004.mp4
β βββ (...)
βββ observation.images.camera_right_wrist_rgb/
βββ episode_000000.mp4
βββ episode_000001.mp4
βββ episode_000002.mp4
βββ episode_000003.mp4
βββ episode_000004.mp4
βββ (...)
π 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.
π License
This dataset is released under the apache-2.0 license.
Please refer to the LICENSE file for full license terms and conditions.
π 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
π Version Information
Version History
- v1.0.0 (2025-11): Initial release
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