A Mixed-Stiffness Anthropomimetic Fingertip Broadens the Operating Range for Coin Grasping

2026-08-07

AI Summary

This study addresses the challenge of robotic grasping of thin, flat objects such as coins, which traditionally requires flipping, contact with the object’s underside, or specialized nail-like structures, thereby limiting manipulation versatility. The authors propose a nail-less, anthropomorphic fingertip design featuring a heterogeneous stiffness distribution—soft at the center (Shore E10) and stiff on the sides (Shore A60)—that creates an internal constraint boundary during oblique rotational pinch grasps, effectively expanding the manipulation workspace without relying on anatomical features. Introducing boundary stiffness layout as a novel design variable, the hybrid fingertips are fabricated via multi-material 3D printing and validated on an automated experimental platform. Results demonstrate consistently high success rates across varying approach distances, vertical displacements, and rotation angles, achieving reliable grasps of all six Japanese coin types and significantly outperforming uniformly soft fingertips.

Abstract

Robotic grasping of thin, flat objects such as coins on hard surfaces remains challenging because conventional methods require reorienting the object, accessing its underside, or adding a dedicated nail mechanism. We previously showed that a rigid nail arrests soft-pad deformation and thereby forms a geometric constraint that improves precision grasping. Here we asked whether an additional constraint-forming boundary, created within the pad by material choice rather than by anatomy, could extend the conditions under which that constraint holds. We fabricated anthropomimetic fingertips with Shore E10 silicone at the center and Shore A60 at the sides, and compared them with uniformly soft E10 fingertips. An automated apparatus performed an oblique rotational tip pinch in which the pad engaged the coin's lateral surface, lifting it from flush contact with no gap beneath it. Over variations in horizontal approach distances, vertical finger displacements, and index-finger rotation, the mixed-stiffness pair maintained high success rates across more tested settings than the uniform pair during both geometric-constraint formation and the transition to a stable grasp. The nail-free pair failed in all 36 conditions of Experiment 1-1. However, the uniform pair performed better when coin position along the finger axis was varied, a condition-dependent trade-off. After tuning for coin size, both fingertip types grasped all six Japanese denominations. These results suggest that the operating range for thin-object grasping depends not only on pad softness but also on where stiffness is placed within a nail-supported pad, making boundary placement a candidate fingertip design variable.

Problem

• robotic grasping
• thin objects
• anthropomimetic fingertips
• geometric constraint
• stiffness distribution

Innovation

• mixed-stiffness fingertip
• anthropomimetic design
• geometric constraint
• thin-object grasping
• soft robotics