iTeach: In the Wild Interactive Teaching for Failure-Driven Adaptation of Robot Perception
The episode discusses iTeach, a framework for failure-driven adaptation of robot perception. It describes how a human can observe and correct robot model predictions during deployment using mixed reality headsets. The method uses few-shot semi-supervised learning to generate dense training supervision from short interactions, allowing robots to adapt quickly to real-world failures.