Control

Reduced-Order Model

A reduced-order model is a simplified dynamics model that captures the dominant behavior of a complex system with far fewer states, trading fidelity for tractability. Legged locomotion classics include the linear inverted pendulum for bipedal walking, the spring-loaded inverted pendulum for running, and single-rigid-body models for quadrupeds, each enabling real-time model predictive control that full-order dynamics would make computationally prohibitive.

Why it matters for physical AI

Real-time planning on legged robots exists largely because reduced-order models make the optimization tractable, and template-and-anchor hierarchies remain the backbone of model-based humanoid control.