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45
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[ 7, 10, 10, 10, 10 ]
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[ 0, 1 ]
[ 0, 1 ]
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[ 0, 2 ]
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[ 0.04430423304438591, 0.2043861746788025, -0.10361164063215256, 0.25230348110198975, -0.8559610247612, -0.7669360637664795, 0.44068077206611633, -0.25235435366630554, 0.20161645114421844, -1.696583867073059, -0.4870142340660095, 2.3578546047210693 ]
End of preview. Expand in Data Studio

leju_robot_moving_parts_g

πŸ“‹ 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

🏠 Scene Types

This dataset covers the following scene types:

  • home

πŸ€– Atomic Actions

This dataset includes the following atomic actions:

  • grasp
  • place
  • pick

πŸ“Š 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

πŸ‘₯ Authors

Contributors

This dataset is contributed by:

πŸ”— Links

🏷️ Dataset Tags

  • RoboCOIN
  • LeRobot

🎯 Task Descriptions

Primary Tasks

take the parts from the cabinet and place them on the table.

Sub-Tasks

This dataset includes 11 distinct subtasks:

  1. End
  2. Grasp the white part with left gripper
  3. Grasp the white part with right gripper
  4. Insert the small component into the corresponding slot on the workbench.
  5. Move the small component to the workbench.
  6. Move to the table behind body
  7. null
  8. Pick up the small component from the shelf.
  9. Place the white part on the table with left gripper
  10. Place the white part on the table with right gripper
  11. Return to the initial position at the workbench.

πŸŽ₯ 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

πŸ“‚ Data Splits

The dataset is organized into the following splits:

  • Training: Episodes 0:156

πŸ“ 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", "head_joint_1_eff_nm", "head_joint_2_eff_nm", "left_eef_pos_x_m", "left_eef_pos_y_m", "left_eef_pos_z_m", "right_eef_pos_x_m", "right_eef_pos_y_m", "right_eef_pos_z_m", "left_eef_rot_euler_x_rad", "left_eef_rot_euler_y_rad", "left_eef_rot_euler_z_rad", "right_eef_rot_euler_x_rad", "right_eef_rot_euler_y_rad", "right_eef_rot_euler_z_rad", "imu_accel_x_m_s2", "imu_accel_y_m_s2", "imu_accel_z_m_s2", "imu_gyro_x_rad_s", "imu_gyro_y_rad_s", "imu_gyro_z_rad_s", "imu_quat_x", "imu_quat_y", "imu_quat_z", "imu_quat_w"]}, "action": {"dtype": "float32", "shape": [54], "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"]}, "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/
β”œβ”€β”€ annotations/
β”‚   β”œβ”€β”€ eef_acc_mag_annotation.jsonl
β”‚   β”œβ”€β”€ eef_direction_annotation.jsonl
β”‚   β”œβ”€β”€ eef_velocity_annotation.jsonl
β”‚   β”œβ”€β”€ gripper_activity_annotation.jsonl
β”‚   β”œβ”€β”€ gripper_mode_annotation.jsonl
β”‚   └── (...)
β”œβ”€β”€ data/
β”‚   └── chunk-000/
β”‚       β”œβ”€β”€ episode_000000.parquet
β”‚       β”œβ”€β”€ episode_000001.parquet
β”‚       β”œβ”€β”€ episode_000002.parquet
β”‚       β”œβ”€β”€ episode_000003.parquet
β”‚       β”œβ”€β”€ episode_000004.parquet
β”‚       └── (...)
β”œβ”€β”€ meta/
β”‚   β”œβ”€β”€ episodes.jsonl
β”‚   β”œβ”€β”€ episodes_stats.jsonl
β”‚   β”œβ”€β”€ info.json
β”‚   └── tasks.jsonl
└── videos/
    └── chunk-000/
        β”œβ”€β”€ observation.images.camera_head_rgb/
        β”‚   β”œβ”€β”€ episode_000000.mp4
        β”‚   β”œβ”€β”€ episode_000001.mp4
        β”‚   β”œβ”€β”€ episode_000002.mp4
        β”‚   β”œβ”€β”€ episode_000003.mp4
        β”‚   β”œβ”€β”€ episode_000004.mp4
        β”‚   └── (...)
        β”œβ”€β”€ observation.images.camera_left_wrist_rgb/
        β”‚   β”œβ”€β”€ episode_000000.mp4
        β”‚   β”œβ”€β”€ episode_000001.mp4
        β”‚   β”œβ”€β”€ episode_000002.mp4
        β”‚   β”œβ”€β”€ episode_000003.mp4
        β”‚   β”œβ”€β”€ episode_000004.mp4
        β”‚   └── (...)
        └── observation.images.camera_right_wrist_rgb/
            β”œβ”€β”€ episode_000000.mp4
            β”œβ”€β”€ episode_000001.mp4
            β”œβ”€β”€ episode_000002.mp4
            β”œβ”€β”€ episode_000003.mp4
            β”œβ”€β”€ episode_000004.mp4
            └── (...)

πŸ“ž 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.

πŸ“„ License

This dataset is released under the apache-2.0 license.

Please refer to the LICENSE file for full license terms and conditions.

πŸ“š 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}
    }

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  • v1.0.0 (2025-11): Initial release
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