Hardware

Shadow Hand

The Shadow Hand is an anthropomorphic dexterous robotic hand from the Shadow Robot Company, with 24 joints and roughly 20 actuated degrees of freedom driven by tendons, closely matching the kinematics of a human hand. It became the reference platform for dexterous manipulation research, most prominently in OpenAI's Learning Dexterity work (2018-2019), where policies trained in simulation with domain randomization performed in-hand cube reorientation and Rubik's cube manipulation on the physical hand.

Why it matters for physical AI

Human-equivalent hands expose the frontier of contact-rich control; results on platforms like the Shadow Hand calibrate how far sim-to-real training can carry high-dimensional dexterity.