Locomotion

Balance Recovery

Balance recovery is the set of strategies a legged robot uses to avoid falling after a push, slip, or trip, conventionally categorized as ankle, hip, and stepping strategies in order of increasing disturbance magnitude, with capture point theory formalizing where a foot must be placed to come to rest. Reinforcement-learned controllers now discover recovery behaviors, including multi-step corrections and even fall-and-stand-up sequences, that exceed hand-designed strategies.

Why it matters for physical AI

Push recovery determines whether a humanoid survives contact with the messy world of bumped tables and shifting loads, making it a gating capability for deploying legged robots outside labs.