Building a Robot Teleoperation System for Data Collection
If you're training robot policies with imitation learning, the quality of your dataset almost entirely depends on how good your teleoperation system is. A clunky, high-latency teleop rig produces jerky, inconsistent demonstrations — and your policy will happily learn those bad habits. This tutorial walks through designing and building a teleoperation system purpose-built for collecting clean, high-frequency demonstration data.
What "good" teleoperation looks like for data collection
Teleoperation for entertainment or remote inspection has different priorities than teleoperation for data collection. For ML data collection, you specifically need:
Low, consistent latency — variable lag introduces noise that looks like intentional motion to a learning algorithm.
