Robot Learning

Flow Matching Policy

A flow matching policy is a robot control policy that generates action chunks by integrating a learned velocity field from noise to actions, conditioned on observations such as images, proprioception, and language. Physical Intelligence's pi0 is the best-known example, attaching a flow matching action expert to a pretrained vision-language model to produce continuous 50 Hz actions for dexterous tasks like laundry folding.

Why it matters for physical AI

Continuous action heads determine how precisely and quickly a foundation model can move a real robot; flow matching heads have become a leading design for high-frequency dexterous control in modern VLAs.