Pretraining data
- Measured whole-body motion, not single-camera estimates
- Fast, outdoor and work-site motion headcams miss
- Per-clip quality grade for data weighting
AutelicaSample clip
Sample clip: three drones to a humanoid.
Eight seconds of a jog with a 90° turn, captured by three off-the-shelf drones with no markers, timecode or calibration target. Every file below is what a customer receives per clip. Free under CC BY 4.0.
Drone 1Drone 2Drone 3Foot contact
3D reconstruction · metres · z up
Drag the timeline. Orange skeletons on the videos are the 3D reconstruction projected back into each drone. Lanes: heel and ball contact for each foot, then held-out error.
59 / 59Randomized runs completed: pushes, friction, mass, motor gains, 0–20 ms latency
2.9 cmRobot keypoint error against the captured motion
0.10 mMean path error over the clip
–Held-out-camera error, median across drones and joints
Recovered from the footage
What the pipeline solved
–Drone 2 clock offset, recovered from body motion
–Drone 3 clock offset, recovered from body motion
3 × 240Moving camera poses, one per drone per frame
1.83 mMetric scale from subject height; ground at z = 0
Download · CC BY 4.0
Clip contents
| File | Contents | Size |
|---|---|---|
| drone1.mp4 | Drone 1 video, 1920 × 1080, 29.97 fps | 11.2 MB |
| drone2.mp4 | Drone 2 video, 1920 × 1080, 29.97 fps | 13.9 MB |
| drone3.mp4 | Drone 3 video, 1920 × 1080, 29.97 fps | 16.3 MB |
| calibration/cameras.json | Intrinsics, radial k1, recovered clock offsets, keyframe flags per drone | 9 KB |
| calibration/extrinsics.npz | Per-frame R, t for each moving drone (3 × 240) | 33 KB |
| motion/body_coco17.npz | COCO-17 joints in metres (240 × 17 × 3) and each drone’s 2D detections | 123 KB |
| motion/body_fit_joints.npz | Parametric body fit joints (MHR, Apache-2.0), smoothed | 304 KB |
| motion/contacts.npz | Per-frame planted flags: left/right heel and ball | 2 KB |
| robot/g1_qpos.npz | Unitree G1 retargeted trajectory, 29 DoF + floating base | 67 KB |
| robot/g1_motion_50hz.csv | G1 trajectory resampled to 50 Hz | 136 KB |
| robot/physics_eval.json | MuJoCo evaluation: 60 runs, randomization ranges, fall rule, errors | 69 KB |
| qc/error_report.json | Held-out-camera error: per drone, per joint, percentiles | 1 KB |
| qc/heldout_residuals.npz | Per-frame held-out residuals in px and mm (3 × 240 × 17) | 88 KB |
| metadata.json | Capture metadata and licence | 1 KB |
| LICENSE.txt | CC BY 4.0 licence and attribution | 1 KB |
World frame for every file: metres, z up, ground at z = 0, right-handed. Cameras: x_cam = R x_world + t, OpenCV axes, intrinsics at 1920 × 1080. Attribution: “Autelica (autelica.com)”. The motion library and pilot data are licensed separately.
For frontier labs
How teams use clips like this
Evaluation sets
- Held-out sites and tasks with metric ground truth
- Physics validation on your embodiment
- Repeatable protocol and seeds
Label QA for egocentric data
- Exocentric cameras alongside head cameras
- Metric reference for auto-labelled body and hands
- Measured label error per session
Site-specific deployment
- Capture at the facility before go-live
- Motion and evaluation per site
- Repeat capture per rollout