A Bioinspired Robotic Finger for Multimodal Tactile Sensing Powered by Fiber Optic Sensors

IF 6.8 Q1 AUTOMATION & CONTROL SYSTEMS Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-06-02 DOI:10.1002/aisy.202400175
Baijin Mao, Kunyu Zhou, Yuyaocen Xiang, Yuzhu Zhang, Qiangjing Yuan, Hongwei Hao, Yaozhen Chen, Houde Liu, Xueqian Wang, Xiaohao Wang, Juntian Qu
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Abstract

The rapid advancement of soft robotic technology emphasizes the growing importance of tactile perception. Soft grippers, equipped with tactile sensing, can gather interactive information crucial for safe human–robot interaction, wearable devices, and dexterous manipulation. However, most soft grippers with tactile sensing abilities have limited modes of tactile perception, restricting their dexterity and safety. In addition, existing tactile systems are often complicated, leading to unstable perception signals. Inspired by various organisms, a novel multimodal tactile-sensing soft robotic finger is proposed. This finger, based on a modified fin ray structure, integrates a distributed fiber optic sensing system as part of its tactile sensory neural system. It replicates human finger capabilities, discerning contact forces as low as 0.01 N with exceptional sensitivity (106.96 mN nm−1). Through training neural networks models, the finger achieves an accuracy exceeding 96% in recognizing roughness, material stiffness, and finger pad position. Assembled into two-finger parallel gripper, it demonstrates precise manipulation capabilities for fragile items like strawberries and potato chips. Moreover, through synergistic interplay of multimodal tactile sensing, this finger can successfully grasp an underwater transparent sphere, mitigating limitations of visual perception. The developed soft finger holds promise in various scenarios including hazardous environment detection and specialized grasping tasks.

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由光纤传感器驱动的多模态触觉传感生物启发机器人手指
软体机器人技术的快速发展凸显了触觉感知日益增长的重要性。配备触觉感知功能的软机械手可以收集对安全的人机交互、可穿戴设备和灵巧操作至关重要的交互信息。然而,大多数具有触觉传感能力的软抓手的触觉感知模式有限,限制了其灵巧性和安全性。此外,现有的触觉系统往往比较复杂,导致感知信号不稳定。受各种生物的启发,我们提出了一种新型多模态触觉感应软机械手指。这种手指基于改进的鳍射线结构,集成了分布式光纤传感系统,作为其触觉神经系统的一部分。它复制了人类手指的功能,能以极高的灵敏度(106.96 mN nm-1)分辨低至 0.01 N 的接触力。通过训练神经网络模型,手指在识别粗糙度、材料硬度和指垫位置方面的准确率超过 96%。组装成双指并行抓手后,它对草莓和薯片等易碎物品具有精确的操控能力。此外,通过多模态触觉传感的协同作用,该手指还能成功抓取水下透明球体,缓解了视觉感知的局限性。开发的软手指有望应用于各种场景,包括危险环境检测和特殊抓取任务。
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CiteScore
1.30
自引率
0.00%
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0
审稿时长
4 weeks
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