Manipulation

Finger Gaiting

Finger gaiting is an in-hand manipulation strategy in which fingers are sequentially lifted, repositioned, and re-engaged on an object so it can be reoriented continuously beyond the workspace of any fixed grasp. Because contacts are broken and remade, the hand must maintain grasp stability with the remaining fingers throughout. Reinforcement learning systems such as OpenAI's Rubik's cube work demonstrated emergent finger gaiting on high-DoF hands.

Why it matters for physical AI

Dexterity beyond pick-and-place requires reorienting objects within the hand; finger gaiting is a core capability separating simple grippers from human-level manipulation and a benchmark for contact-rich policy learning.