--- license: other license_name: maginoresell license_link: https://huggingface.co/datasets/MicroAGI-Labs/MicroAGI01/blob/main/LICENSE task_categories: - robotics - text-generation tags: - egocentric - fov - VLA - VLM size_categories: - 100M **License:** See `maginoresell` MicroAGI01 is an egocentric RGB-D dataset of human household manipulation with full pose annotations. 676 recordings spanning 137 task types across 14 activity categories. ## What's Included Per Recording - RGB + depth streams - Camera pose (6DoF) - Hand poses (3D landmarks) - Task segmentation with text annotations ## Quick Facts | | | |---|---| | **Recordings** | 676 mcaps (283 cut, 393 uncut) | | **Task types** | 137 | | **Container** | `.mcap` | | **Previews** | 1 sample `.mp4` file | ## Folder Structure ``` MicroAGI01/ ├── uncut_mcaps/ # Full-length recordings, ≥80% hands validity ├── cut_mcaps/ # Shorter semantic chunks, ≥95% hands validity ├── task_mapping.csv # Task labels per recording ├── microagi01viewerfoxglove.json └── LICENSE ``` **Start with `uncut_mcaps`** — full-length recordings with all annotations included. **`cut_mcaps`** contains shorter, semantically-complete segments with stricter hand tracking validity. ## Task Categories Kitchen: `kitchen_cooking`, `kitchen_prep`, `kitchen_dishes`, `kitchen_organization`, `kitchen_dining`, `kitchen_general` Cleaning: `cleaning_general`, `cleaning_floor` Laundry: `laundry` Organization: `general_organization`, `general_household` Rooms: `bedroom`, `bathroom`, `living_room` ## Topic Structure ### Overview ``` Meta /meta Camera /tf_static /camera/color/image, /camera/color/info (+ /camera/color/health) /camera/depth/image, /camera/depth/info, /camera/depth/unit_of_depth_in_mm SLAM /tf/camera (+ .../health, .../state) Hands /tf/hands, /hands/left, /hands/right (+ .../health) IMU /imu/accel/sample, /imu/gyro/sample Task /task (includes task_title) ``` ### Descriptions (of relevant topics) ``` /meta: Information about the mcap, the operator, ... (operator_height_in_m, metadata for general task description) /tf_static: Any static transforms (Includes transforms between camera, imu, depth and color) /camera/.../image: JPEG@90 image for color, PNG for depth /camera/.../info: Parameters for sensor (especially intrinsics) /camera/depth/unit_of_depth_in_mm: Defines the depth unit conversion. Currently set to 1, meaning the raw pixel values in the depth image are measured directly in millimeters (e.g., a pixel value of 1000 equals 1 meter) /camera/color/health: Signals bad images which are e.g. too dark, blurry, ... /tf/camera: Pose of camera (Only valid if a msg on .../health exists with the same timestamp and valid == true, otherwise they should be ignored. Poses are only coherent to poses in the same block of valid poses.) /tf/camera/health: Signals regions which successful tracking /tf/hands: Pose of left and right wrist /hands/...: Positions of Hand keypoints (In wrist frame) /hands/.../health: Signals whether to trust the hands position or not /imu/.../sample: Raw imu samples /task: Description of the current task (includes task_title) ``` ### TF-Tree (Across all tf (static) topics) ``` TF_TREE (RightHanded Coordinate Systems): world (On the ground; z is up, gravity aligned) camera (Center of camera; z is up, x is front) # Camera data depth (Reference for the depth image; x to the right, y is down) accel (Reference for the accel) gyro (Reference for the gyro) color (Reference for the color image; x to the right, y is down) left_wrist (x is in direction from pinky to thumb, z is in direction of arm) right_wrist (x is in direction from pinky to thumb, z is in direction of arm) ``` ## Download Everything: ```bash huggingface-cli download MicroAGI-Labs/MicroAGI01 --repo-type dataset --local-dir ./MicroAGI01 ``` Single file: ```bash huggingface-cli download MicroAGI-Labs/MicroAGI01 uncut_mcaps/open-source-06.mcap --repo-type dataset --local-dir ./ ``` ## Viewing We use [Foxglove](https://foxglove.dev/). A layout template is included in the repo: 1. Open Foxglove 2. Layout → Import layout → select `microagi01viewerfoxglove.json` 3. Load any `.mcap` file This sets up the 3D view, camera feed, hand validity state transitions, and task annotations panel. ## Extracting protobuf We use [our github repo](https://github.com/MicroAGI-Labs/mcap-topic-extractor). A script is included in the repo. ## Intended Uses - Policy and skill learning (robotics / VLA) - Action detection and segmentation - Hand/pose estimation and grasp analysis - World-model pre/post training ## Attribution ``` This work uses the MicroAGI01 dataset (MicroAGI, Inc. 2026). ``` ## Contact Questions: `info@micro-agi.com` Custom data or derived signals: `data@micro-agi.com`