Foundation Models

Policy Head

A policy head is the output module of a learned control architecture that converts a shared backbone representation into robot actions. Designs include regression heads emitting continuous commands, tokenization heads producing discretized action bins as in RT-2, and generative heads such as diffusion or flow-matching experts, as in Pi0, that sample continuous action chunks. The choice governs how well multimodal action distributions and high-frequency control are handled.

Why it matters for physical AI

Much of the recent progress in vision-language-action models has come from better action heads: generative chunking heads capture multimodal demonstrations and deliver smooth high-rate control where naive regression collapses to averages.