Robotics VLA Skill

Expert guidance for building generalist robot policies using Vision-Language-Action (VLA) flow models, based on the π0 architecture.

Core Architecture

π0 model = VLM backbone + action expert + flow matching

Component	Detail
VLM backbone	PaliGemma (3B) — provides visual + language understanding
Action expert	Separate transformer weights (~300M) for robot state + actions
Total params	~3.3B
Action output	Chunks of H=50 actions; 50Hz or 20Hz robots
Inference speed	~73ms on RTX 4090

See references/architecture.md for full technical details (attention masks, flow matching math, MoE design).