Locomotion

Push Recovery

Push recovery is a legged robot's ability to reject external perturbations and avoid falling, using a hierarchy of strategies: ankle torque for small pushes, hip and angular-momentum strategies for moderate ones, and reactive stepping for large disturbances. Capture point theory formalizes where a robot must step to come to rest, while modern learned controllers acquire recovery behaviors implicitly through randomized perturbations in simulation.

Why it matters for physical AI

Robustness to bumps, slips, and contact is a prerequisite for deploying humanoids around people, and standardized push tests have become a de facto benchmark for locomotion controller quality.