The openpi project has released three policy models—PI0, PI0.5, and PI0-FAST—each designed for different trade-offs in robotics control. This technical breakdown examines each model along a consistent pipeline: data processing, state representation, network architecture, and how image, language, state, and action conditions are fused. PI0 serves as the baseline, PI0.5 introduces optimizations for better performance, and PI0-FAST focuses on inference speed. Understanding these differences is crucial for researchers and engineers deploying policy models in real-world robotic systems. The post provides enough detail to replicate or adapt the architectures, making it a valuable reference for the robotics AI community.
This post offers a thorough explanation of three policy models from the openpi project: PI0, PI0.5, and PI0-FAST. It systematically covers data processing, state representation, network structure, and fusion of image, language, state, and action conditions, making it a valuable resource for robotics AI researchers.