神经形态工程学
计算机科学
仿生学
人工智能
假手
自然(考古学)
触觉传感器
人机交互
计算机视觉
人工神经网络
生物
机器人
古生物学
作者
Sriramana Sankar,Cheng Wenyu,Jinghua Zhang,Ariel Slepyan,Mark M. Iskarous,Rebecca J. Greene,Rene DeBrabander,Junjun Chen,Arnav Gupta,Nitish V. Thakor
出处
期刊:Science Advances
[American Association for the Advancement of Science]
日期:2025-03-05
卷期号:11 (10)
被引量:1
标识
DOI:10.1126/sciadv.adr9300
摘要
The human hand's hybrid structure combines soft and rigid anatomy to provide strength and compliance for versatile object grasping. Tactile sensing by skin mechanoreceptors enables precise and dynamic manipulation. Attempts to replicate the human hand have fallen short of a true biomimetic hybrid robotic hand with tactile sensing. We introduce a natural prosthetic hand composed of soft robotic joints and a rigid endoskeleton with three independent neuromorphic tactile sensing layers inspired by human physiology. Our innovative design capitalizes on the strengths of both soft and rigid robots, enabling the hybrid robotic hand to compliantly grasp numerous everyday objects of varying surface textures, weight, and compliance while differentiating them with 99.69% average classification accuracy. The hybrid robotic hand with multilayered tactile sensing achieved 98.38% average classification accuracy in a texture discrimination task, surpassing soft robotic and rigid prosthetic fingers. Controlled via electromyography, our transformative prosthetic hand allows individuals with upper-limb loss to grasp compliant objects with precise surface texture detection.
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