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数据格式

艾欧数据平台支持灵活的数据格式，可以自定义数据可视化模板。

这里以艾欧数据采集产品采集的数据格式为例：

人类数据格式​

文件结构​

f"{date}_{project}_{scene}_{task}_{staff_id}_{timestamp}"
├── align_result.csv # 时间戳对齐表格
├── annotation.json  # 标注数据
├── config           # 相机和传感器配置
│   ├── calib_data.yml
│   ├── depth_to_rgb.yml
│   ├── mocap_main.yml
│   ├── orbbec_depth.yml
│   ├── orbbec_rgb.yml
│   └── pose_calib.yml
└── data.mcap        # 多模态数据

多模态数据​

library:   mcap go v1.7.0                                              
profile:   ros1                                                        
messages:  45200                                                       
duration:  1m5.625866496s                                              
start:     2025-01-15T18:09:29.628202496+08:00 (1736935769.628202496)  
end:       2025-01-15T18:10:35.254068992+08:00 (1736935835.254068992)  
compression:
    zstd: [764/764 chunks] [6.13 GiB/3.84 GiB (37.39%)] [59.87 MiB/sec] 
channels:
    (1)  /rgbd/color/image_raw/compressed                  1970 msgs (30.02 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (2)  /joint_states                                     1970 msgs (30.02 Hz)   : sensor_msgs/JointState [ros1msg]       
    (3)  /claws_r_hand                                     1970 msgs (30.02 Hz)   : io_msgs/claws_angle [ros1msg]          
    (4)  /global_localization                              1970 msgs (30.02 Hz)   : geometry_msgs/PoseStamped [ros1msg]    
    (5)  /robot_description                                   1 msgs              : std_msgs/String [ros1msg]              
    (6)  /ee_visualization                                 1970 msgs (30.02 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (7)  /rgbd/depth/image_raw                             1970 msgs (30.02 Hz)   : sensor_msgs/Image [ros1msg]            
    (8)  /colorized_depth                                  1970 msgs (30.02 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (9)  /claws_l_hand                                     1970 msgs (30.02 Hz)   : io_msgs/claws_angle [ros1msg]          
    (10) /claws_touch_data                                 1970 msgs (30.02 Hz)   : io_msgs/squashed_touch [ros1msg]       
    (11) /touch_visualization                              1970 msgs (30.02 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (12) /mocap/sensor_data                                1970 msgs (30.02 Hz)   : io_msgs/squashed_mocap_data [ros1msg]  
    (13) /mocap/ros_tf                                     1970 msgs (30.02 Hz)   : tf2_msgs/TFMessage [ros1msg]           
    (14) /left_ee_pose                                     1970 msgs (30.02 Hz)   : geometry_msgs/PoseStamped [ros1msg]    
    (15) /right_ee_pose                                    1970 msgs (30.02 Hz)   : geometry_msgs/PoseStamped [ros1msg]    
    (16) /usb_cam_left/mjpeg_raw/compressed                1960 msgs (29.87 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (17) /usb_cam_right/mjpeg_raw/compressed               1946 msgs (29.65 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (18) /usb_cam_fisheye/mjpeg_raw/compressed             1957 msgs (29.82 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (19) /realsense_left_hand/depth/image_rect_raw         1961 msgs (29.88 Hz)   : sensor_msgs/Image [ros1msg]            
    (20) /realsense_left_hand/color/image_raw/compressed   1961 msgs (29.88 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (21) /realsense_right_hand/depth/image_rect_raw        1947 msgs (29.67 Hz)   : sensor_msgs/Image [ros1msg]            
    (22) /realsense_right_hand/color/image_raw/compressed  1947 msgs (29.67 Hz)   : sensor_msgs/CompressedImage [ros1msg]  
    (23) /world_left_ee_pose                               1970 msgs (30.02 Hz)   : geometry_msgs/PoseStamped [ros1msg]    
    (24) /world_right_ee_pose                              1970 msgs (30.02 Hz)   : geometry_msgs/PoseStamped [ros1msg]    
channels: 24
attachments: 0
metadata: 0
Topic名称数据含义
/mocap/sensor_data基于动作捕捉的关节速度、加速度、角速度、旋转角度和传感器数据
/mocap/ros_tf基于动作捕捉的所有关节的TF
/joint_states基于动作捕捉的所有关节的JointState
/right_ee_pose主头部相机坐标系下的右夹爪位姿
/left_ee_pose主头部相机坐标系下的左夹爪位姿
/claws_l_hand左夹爪闭合程度
/claws_r_hand右夹爪闭合程度
/claws_touch_data夹爪触觉数据（包含两个消息，每个消息的frame_id表示左或右夹爪，data的前四个值有效）
/realsense_left_hand/color/image_raw/compressed左夹爪相机的RGB图像
/realsense_left_hand/depth/image_rect_raw左夹爪相机的深度图像
/realsense_right_hand/color/image_raw/compressed右夹爪相机的RGB图像
/realsense_right_hand/depth/image_rect_raw右夹爪相机的深度图像
/rgbd/color/image_raw/compressed主头部相机的RGB图像
/rgbd/depth/image_raw主头部相机的深度图像
/colorized_depth主头部相机的彩色深度图像
/usb_cam_fisheye/mjpeg_raw/compressed主头部鱼眼相机的RGB图像
/usb_cam_left/mjpeg_raw/compressed主头部左单目相机的RGB图像
/usb_cam_right/mjpeg_raw/compressed主头部右单目相机的RGB图像
/ee_visualization主头部相机RGB图像中的末端执行器位姿可视化
/touch_visualization夹爪触觉数据可视化
/robot_description动作捕捉URDF
/global_localization主头部相机在世界坐标系中的位姿
/world_left_ee_pose左夹爪在世界坐标系中的位姿
/world_right_ee_pose右夹爪在世界坐标系中的位姿

如果是人穿戴着触觉手套采集的数据，会增加触觉数字信号阵列Topic：

/mocap/touch_data 57 msgs (30.25 Hz): io_msgs/squashed_touc [ros1msg]

自然语言标注数据​

{
  "belong_to": "20250115_InnerTest_PublicArea_TableClearing_szk_180926",
  "mocap_offset": [],
  "object_set": [
    "paper cup",
    "placemat",
    "trash can",
    "napkin",
    "plate",
    "dinner knife",
    "tableware storage box",
    "wine glass",
    "dinner fork"
  ],
  "scene": "PublicArea",
  "skill_set": [
    "pick {A} from {B}",
    "toss {A} into {B}",
    "place {A} on {B}"
  ],
  "subtasks": [
    {
      "skill": "pick {A} from {B}",
      "description": "pick the paper cup from the placemat with the left gripper",
      "description_zh": "左夹爪 从 餐垫 捡起 纸杯",
      "end_frame_id": 227,
      "end_timestamp": "1736935777206000000",
      "sequence_id": 1,
      "start_frame_id": 159,
      "start_timestamp": "1736935774906000000",
      "comment": "",
      "attempts": "success"
    },
    {
      "skill": "toss {A} into {B}",
      "description": "toss the paper cup into the trash can with the left gripper",
      "description_zh": "左夹爪 扔纸杯进垃圾桶",
      "end_frame_id": 318,
      "end_timestamp": "1736935780244000000",
      "sequence_id": 2,
      "start_frame_id": 231,
      "start_timestamp": "1736935777306000000",
      "comment": "",
      "attempts": "success"
    },
    ...
  ],
  "tag_set": [],
  "task_description": "20250115_InnerTest_PublicArea_TableClearing_szk_180926"
}

遥操作机器人数据格式​

文件结构​

f"{robot_name}_{date}_{timestamp}_{sequence_id}"
├── RM_AIDAL_250124_172033_0.mcap
├── RM_AIDAL_250124_172033_0.json
├── RM_AIDAL_250126_093648_0.metadata.yaml

多模态数据​

Files:             RM_AIDAL_250126_091041_0.mcap
Bag size:          443.3 MiB
Storage id:        mcap
Duration:          100.052164792s
Start:             Jan 24 2025 21:37:32.526605552 (1737725852.526605552)
End:               Jan 24 2025 21:39:12.578770344 (1737725952.578770344)
Messages:          62116
Topic information: Topic: /camera_01/color/image_raw/compressed | Type: sensor_msgs/msg/CompressedImage | Count: 3000 | Serialization Format: cdr
                   Topic: /camera_02/color/image_raw/compressed | Type: sensor_msgs/msg/CompressedImage | Count: 3000 | Serialization Format: cdr
                   Topic: /camera_03/color/image_raw/compressed | Type: sensor_msgs/msg/CompressedImage | Count: 3000 | Serialization Format: cdr
                   Topic: io_teleop/joint_states | Type: sensor_msgs/msg/JointState | Count: 1529 | Serialization Format: cdr
                   Topic: io_teleop/joint_cmd | Type: sensor_msgs/msg/JointState | Count: 10009 | Serialization Format: cdr
                   Topic: io_teleop/target_ee_poses | Type: geometry_msgs/msg/PoseArray | Count: 10014 | Serialization Format: cdr
                   Topic: io_teleop/target_base_move | Type: std_msgs/msg/Float64MultiArray | Count: 10010 | Serialization Format: cdr
                   Topic: io_teleop/target_gripper_status | Type: sensor_msgs/msg/JointState | Count: 10012 | Serialization Format: cdr
                   Topic: io_teleop/target_joint_from_vr | Type: sensor_msgs/msg/JointState | Count: 10012 | Serialization Format: cdr
                   Topic: /robot_description | Type: std_msgs/msg/String | Count: 1 | Serialization Format: cdr
                   Topic: /tf | Type: tf2_msgs/msg/TFMessage | Count: 1529 | Serialization Format: cdr
Topic名称数据含义
/camera_01/color/image_raw/compressed主相机的RGB图像
/camera_02/color/image_raw/compressed左相机的RGB图像
/camera_03/color/image_raw/compressed右相机的RGB图像
io_teleop/joint_states关节状态
io_teleop/joint_cmd关节命令
io_teleop/target_ee_poses末端执行器目标位姿
io_teleop/target_base_move基座移动目标
io_teleop/target_gripper_status夹爪状态目标
io_teleop/target_joint_from_vrVR设备的关节目标
/robot_description机器人URDF描述
/tfTF空间位姿变换信息

自然语言标注数据​

{
    "belong_to": "RM_AIDAL_250126_091041_0",
    "mocap_offset": [],
    "object_set": [
        "lemon candy",
        "plate",
        "pistachios"
    ],
    "scene": "250126",
    "skill_set": [
        "place {A} on {B}"
    ],
    "subtasks": [
        {
            "skill": "place {A} on {B}",
            "objecta": "lemon candy",
            "objectb": "plate",
            "options": [
                "leftHand"
            ],
            "description": "place the lemon candy on the plate with the left hand",
            "end_timestamp": "1737725886915000000",
            "sequence_id": 1,
            "start_timestamp": "1737725880757000000",
            "comment": "",
            "attempts": "success"
        },
        {
            "skill": "place {A} on {B}",
            "objecta": "pistachios",
            "objectb": "plate",
            "options": [
                "rightHand"
            ],
            "description": "place the pistachios on the plate with the right hand",
            "end_timestamp": "1737725950745000000",
            "sequence_id": 2,
            "start_timestamp": "1737725941657000000",
            "comment": "",
            "attempts": "success"
        }
    ],
    "tag_set": [],
    "task_description": "20250205_RM_ItemPacking_zhouxw"
}

模型训练数据​

我们提供将上述mcap和json数据转换成python可以解析的数据，用于直接投入大模型的数据训练。

HDF5格式​

这里是基础数据示例，具体根据原始数据和客户定制化需求，输出的训练数据格式会有差异：

/root
  ├── metadata (Group)
  │     ├── creation_time (Attribute)
  │     ├── source (Attribute)
  │     ├── schema (Dataset)
  │
  ├── messages (Group)
  │     ├── /camera_01/color/image_raw/compressed (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── /camera_02/color/image_raw/compressed (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── /camera_03/color/image_raw/compressed (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── io_teleop/joint_states (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── io_teleop/joint_cmd (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── io_teleop/target_ee_poses (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── io_teleop/target_base_move (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── io_teleop/target_gripper_status (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── io_teleop/target_joint_from_vr (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── /robot_description (Group)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)
  │     │
  │     ├── /tf (Group)
  │     │     ├── timestamps (Dataset)
  │     │     ├── data (Dataset)
  │     │     ├── schema_id (Attribute)

LeRobot格式​

可参考我们的基础样例数据：https://huggingface.co/datasets/io-ai-data/DesktopCleanup_RM_AIDAL_demo

{
    "codebase_version": "v2.1",
    "robot_type": "custom_arm",
    "total_episodes": 20,
    "total_frames": 5134,
    "total_tasks": 20,
    "total_videos": 0,
    "total_chunks": 1,
    "chunks_size": 1000,
    "fps": 30,
    "splits": {
        "train": "0:20"
    },
    "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_01": {
            "dtype": "image",
            "shape": [
                480,
                640,
                3
            ]
        },
        "observation.images.camera_02": {
            "dtype": "image",
            "shape": [
                480,
                640,
                3
            ]
        },
        "observation.images.camera_03": {
            "dtype": "image",
            "shape": [
                480,
                640,
                3
            ]
        },
        "observation.images.camera_04": {
            "dtype": "image",
            "shape": [
                480,
                640,
                3
            ]
        },
        "observation.state": {
            "dtype": "float64",
            "shape": [
                37
            ],
            "names": [
                "r_joint1",
                "r_joint2",
                "r_joint3",
                "r_joint4",
                "r_joint5",
                "r_joint6",
                "l_joint1",
                "l_joint2",
                "l_joint3",
                "l_joint4",
                "l_joint5",
                "l_joint6",
                "R_thumb_MCP_joint1",
                "R_thumb_MCP_joint2",
                "R_thumb_PIP_joint",
                "R_thumb_DIP_joint",
                "R_index_MCP_joint",
                "R_index_DIP_joint",
                "R_middle_MCP_joint",
                "R_middle_DIP_joint",
                "R_ring_MCP_joint",
                "R_ring_DIP_joint",
                "R_pinky_MCP_joint",
                "R_pinky_DIP_joint",
                "L_thumb_MCP_joint1",
                "L_thumb_MCP_joint2",
                "L_thumb_PIP_joint",
                "L_thumb_DIP_joint",
                "L_index_MCP_joint",
                "L_index_DIP_joint",
                "L_middle_MCP_joint",
                "L_middle_DIP_joint",
                "L_ring_MCP_joint",
                "L_ring_DIP_joint",
                "L_pinky_MCP_joint",
                "L_pinky_DIP_joint",
                "platform_joint"
            ]
        },
        "action": {
            "dtype": "float64",
            "shape": [
                12
            ],
            "names": [
                "l_joint1",
                "l_joint2",
                "l_joint3",
                "l_joint4",
                "l_joint5",
                "l_joint6",
                "r_joint1",
                "r_joint2",
                "r_joint3",
                "r_joint4",
                "r_joint5",
                "r_joint6"
            ]
        },
        "observation.gripper": {
            "dtype": "float64",
            "shape": [
                2
            ],
            "names": [
                "right_gripper",
                "left_gripper"
            ]
        },
        "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
        }
    }
}