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observation.state
listlengths
14
14
action
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timestamp
float32
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26.2
frame_index
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episode_index
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task_index
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subtask_annotation
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scene_annotation
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eef_direction_state
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eef_velocity_state
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eef_acc_mag_state
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eef_direction_action
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eef_sim_pose_state
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eef_sim_pose_action
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gripper_mode_state
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gripper_activity_state
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gripper_mode_action
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gripper_activity_action
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gripper_open_scale_state
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End of preview. Expand in Data Studio

Cobot_Magic_place_the_test_tube

πŸ“‹ Overview

This dataset uses an extended format based on LeRobot and is fully compatible with LeRobot.

Robot Type: agilex_cobot_decoupled_magic | Codebase Version: v2.1 End-Effector Type: two_finger_gripper

🏠 Scene Types

This dataset covers the following scene types:

  • home

πŸ€– Atomic Actions

This dataset includes the following atomic actions:

  • grasp
  • pick
  • place

πŸ“Š Dataset Statistics

Metric Value
Total Episodes 364
Total Frames 308346
Total Tasks 6
Total Videos 1092
Total Chunks 1
Chunk Size 1000
FPS 50
Dataset Size 6.0GB

πŸ‘₯ Authors

Contributors

This dataset is contributed by:

πŸ”— Links

🏷️ Dataset Tags

  • RoboCOIN
  • LeRobot

🎯 Task Descriptions

Primary Tasks

left gripper passes test tube to right gripper places on test tube holder. place the test tube on the test tube rack on the desk. place the test tube on the test tube rack on the green tablecloth. place the test tube on the test tube rack on the grey tablecloth. on cyan cloth pass tube from right to left gripper place on stand. on white cloth pass tube from right to left gripper place on stand.

Sub-Tasks

This dataset includes 13 distinct subtasks:

  1. Place the test tubes on the test tube rack with the right gripper
  2. Lift the test tube with the left hand.
  3. End
  4. Pass the test tube from the left gripper to the right gripper
  5. Pick up the test tubes from the table
  6. Place the test tubes on the rack
  7. Hand over the test tubes
  8. Grab the test tube with the left hand.
  9. Receive the test tube with the right hand.
  10. Pick up the test tube with the left gripper
  11. Insert it into the hole at the intersection of the 5th row from the top and the 5th column from the left with the right hand.
  12. abnormal
  13. null

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 0:363

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.cam_high_rgb: video
    • FPS: 50
    • Codec: av1- observation.images.cam_left_wrist_rgb_rgb: video
    • FPS: 50
    • Codec: av1- observation.images.cam_right_wrist_rgb_rgb: video
    • FPS: 50
    • 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": "agilex_cobot_decoupled_magic", "total_episodes": 364, "total_frames": 308346, "total_tasks": 6, "total_videos": 1092, "total_chunks": 1, "chunks_size": 1000, "fps": 50, "splits": {"train": "0:363"}, "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": [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": 50, "video.channels": 3, "has_audio": false}}, "observation.images.cam_left_wrist_rgb_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": 50, "video.channels": 3, "has_audio": false}}, "observation.images.cam_right_wrist_rgb_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": 50, "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):

Cobot_Magic_place_the_test_tube_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.cam_high_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.cam_left_wrist_rgb_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.cam_right_wrist_rgb_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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