IntuiGrasp: Bio-Inspired Dexterous Hand with Intuitive Teaching

Abstract

IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors (BDIP) to bridge the gap between human tactile intuition and robotic execution. Unlike conventional programming, BDIP leverages human's innate priors (e.g., “A pack of tissues requires gentle grasps, cups demand firm contact”) by enabling real-time transfer of gesture and force policies during physical demonstration. When a human demonstrator wears IntuiGrasp, driven rings provide real-time haptic feedback on contact stress and slip, while integrated tactile sensors translate these human policies into image data, offering valuable data for imitation learning. In this study, human teachers use IntuiGrasp to demonstrate how to grasp three types of objects: a cup, a crumpled tissue pack, and a thin playing card. IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.