Locomotion

Gait Library

A gait library is a precomputed collection of reference gaits or controllers, each optimized offline for a particular condition such as speed, terrain slope, or step length, from which a legged robot selects and interpolates online. The approach was prominent in hybrid zero dynamics work on bipeds like Cassie, where libraries of periodic orbits enabled robust velocity tracking. Learned policies sometimes distill or imitate such libraries.

Why it matters for physical AI

Offline optimization can produce dynamically precise gaits that online computation cannot afford; libraries bridge model-based gait design and real-time control, and provide structured priors or training targets for learned locomotion.