What is Teleoperation?

The common rigs are leader-follower: a smaller duplicate arm that the operator moves by hand while the robot mirrors it. ALOHA is the standard low-cost example — a pair of servo arms driven by matching leader arms, recording both arms, three cameras and the joint states at 50 Hz. VR controllers and 3D mice are the alternatives; they are cheaper and work at a distance, but give the operator less sense of contact.

Throughput sets the cost. A practiced operator on a tabletop rig records on the order of 20 to 30 episodes an hour, and a failed attempt still consumes the operator's time plus the reset after it. Scaled collection in Chinese training facilities costs far less per hour of effective data; small-batch collection on research hardware with an engineer operating costs several times more.

Teleoperation breaks down in three places: latency, which destroys the operator's sense of contact; tasks that need force feedback the rig does not provide; and anything repetitive enough that a scripted or simulated policy would produce the same data for less. It stays the default for fine manipulation because no other method captures the small corrections — the wiggle that seats a connector — that make a demonstration teachable. Collection is commissioned per task rather than sold as a fixed product, because the rig, the objects and the resets are different every time.