Robot Learning

Demonstration

Demonstration is a recorded trajectory of observation-action pairs showing how a task should be performed, serving as the supervision signal for imitation learning. Demonstrations are gathered through teleoperation, kinesthetic teaching in which the arm is physically guided, or retargeted from human video. Quality dimensions include smoothness, consistency across operators, coverage of recovery behaviors, and alignment between the demonstrator's viewpoint and the robot's sensors.

Why it matters for physical AI

Demonstration collection is the dominant cost in training manipulation policies, and demonstration quality frequently bounds final performance. Scalable, ergonomic collection interfaces are consequently a competitive frontier in physical AI.