Human-in-the-loop is not a bootstrap trick—it’s a first-class learning signal. This article explains how structured, time-aligned human input helps robot learning systems handle distribution shift, recover from failures, and perform reliably in the real world.

Most robot learning failures aren’t caused by a lack of data, but by data that isn’t learnable. This article breaks down what it actually means for robot data to be learning-ready—from episode structure and timing to calibration, action semantics, and QA.