Overview / Autonomy
Data & learning

Collect. Curate. Train.

Hand-grasping demonstrations, from recording to ACT deployment.

01 · Collect

Hand-grasping demonstrations.

Synchronized camera views, measured state and commanded references.

Head
Left wrist
Right wrist
38.0 minDemonstrations
68,364Frames
117Episodes
80Takes
02 · Curate

Curate on your Mac.

Review four camera views. Trim takes. Export to LeRobot.

MILO Curation · Mac app

ReviewCameras and robot state share one timeline.

CurateKeep useful intervals; preserve the source.

ExportPrepare aligned LeRobot episodes.

03 · Train

Training Studio.

Build the policy graph, choose data and inspect training runs.

Current Training Studio architecture editor with camera inputs, ACT and output nodesOpen Training Studio ↗

ObserveHead and wrist images plus state history.

PredictACT produces 120 reference steps.

EvaluateSplit whole takes into train, validation and test.

04 · Deploy

Predict 4 s. Execute 1 s.

Observe again, re-plan and execute through the shared whole-body controller.

Camera + state→ACT→Joint references→Shared controller

Explore the learning pipeline →

Navigation

Mapping & localization.

Wheel and visual odometry, lidar mapping and Nav2 goals enter the shared command path.

Explore the software stack →