Manipulation

Lazy Grasping

Lazy grasping is a strategy that defers committing to a specific grasp pose or fully evaluating grasp candidates until execution demands it, refining the choice online as the robot approaches the object. Analogous to lazy evaluation in motion planning, it avoids exhaustive up-front grasp analysis, instead validating only the candidates actually pursued and re-ranking them as new observations arrive during the reach.

Why it matters for physical AI

Deferring grasp commitment lets closed-loop policies exploit fresh, close-range observations, improving robustness to perception error, object movement, and clutter compared with executing a grasp planned once from a distance.