Locomotion

Dynamic Gait

Dynamic Gait is a legged locomotion pattern that includes phases where the robot is not statically stable, relying on momentum and continuous active control to avoid falling, in contrast to static gaits that keep the center of mass over the support polygon at all times. Trotting, bounding, galloping, and human-like walking with aerial or two-legged support phases are dynamic. Analysis tools include the zero-moment point and capture point; modern quadrupeds execute dynamic gaits via model predictive control or reinforcement-learned policies.

Why it matters for physical AI

Speed and efficiency on real terrain require dynamic gaits, and their reliability on stairs, gravel, and slopes has become the benchmark by which learned locomotion controllers are judged for deployment.