Review

This module covered how powerful foundation models—like GR00T—are changing healthcare robotics by learning from lots of different types of data, including images, sensors, and natural language instructions.

We explored how Vision-Language-Action (VLA) models can understand commands and camera views, then decide how a robot should act in real medical scenarios. The module also highlights why synthetic data and simulation (using things like patient phantoms) are so important: they let robots safely practice, handle rare or tricky cases, and learn efficiently without needing real patient data.

Now that we’ve explored data collection, let’s continue to training and deploying models!