TELEOP
./data

The highest-quality humanoid training data.

For labs and robotics teams: real teleoperation episodes, captured at scale by certified human operators.

01THE BOTTLENECK

Humanoids learn from three data sources. Teleop is the only one with the signal to teach contact-rich manipulation — and the only one that doesn't scale on its own.

Egocentric video
scales · weak control signal
signal
Synthetic
scales · sim-to-real gap
signal
Teleoperation
highest signal · hard to scale
signal

02WHAT WE CAPTURE

Every datapoint logged per episode — synchronized, timestamped, and labeled. Captured on a 29-DoF humanoid (Unitree G1) under whole-body teleoperation.

vision
head cam
stereo RGB · 640×480
wrist cams
RGB + stereo IR · ×2
frame rate
30 fps · synced
intrinsics
fx/fy · ppx/ppy
distortion
brown-conrady · 5-coeff
extrinsics
R + T · per sensor
rectification
R/P/Q · 63mm baseline
state · action · labels
joints
29-DoF · pos/vel/torque
end-effector
6-DoF state + action
gripper
trigger + squeeze · L/R
dex hands
per-finger · L/R
imu
orientation + accel
odometry
base pose + mode
subtasks
161 labels · timestamped
language
task annotations
the flywheel
   operators ──drive──► robots ──capture──► teleop + ego data
       ▲                                            │
       └────────── autonomy ◄── trained humanoids ──┘

schema · ros2 / mcap · realsense calibration · sourced from HIW-500 (Unitree G1) · CC-BY-4.0

03SAMPLE EPISODES

Real captured episodes — three synchronized camera feeds with live joint, end-effector, and teleop-action telemetry. The raw signal, exactly as logged.

connecting feed…

04ACCESS

Source teleop data for your models.

Tell us the tasks and embodiments you're training.