Behavior Learning

Behavior learning lets humanoid robots map goals to actions without explicit scripts or step-by-step instructions. It’s about how they move, as well as how they decide what to do in dynamic, uncertain environments.

Instead of hardcoding sequences (“open drawer, grasp tool”), robots learn behaviors through imitation, reinforcement, and trial-based adaptation. This enables them to discover action strategies that respond to context: what’s in front of them, what’s changed, and what might happen next.Modern approaches integrate perception and policy learning into feedback-rich loops, letting behaviors emerge from success criteria rather than direct supervision.