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基于MXene和PAN的碳纤维增强双模式三电传感器用于机器人手臂感知和控制

Fangyang Dong^1,2, Qinghe Peng^1,2, Guang-An Yu^1,2

¹Dalian Key Lab of Marine Micro/Nano Energy and Self-Powered Systems, Marine Engineering College, Dalian Maritime University, Dalian, 116026, China.

Small (Weinheim an der Bergstrasse, Germany)

|June 16, 2025

概括

一个新的双模电 triboelectric 传感器增强机器人的感知. 这种基于MXene和PAN的传感器可为智能机器人提供先进的无触摸和触摸传感,改善对象识别和控制.

科学领域:

材料科学材料科学材料科学
机器人技术机器人技术机器人技术
传感器技术传感器技术

背景情况:

机器人感知和智能控制正在迅速发展.
将类似人类的感觉能力整合到机器人中仍然是一个重大挑战.
现有的传感器往往缺乏复杂任务所需的双模态感知.

研究的目的:

开发一种新型双模 triboelectric 传感器 (MPBS),用于增强机器人的感知和控制.
将MPBS与商业机器人臂集成,为智能系统创造一个新的范式.
为了提高机器人的无触摸和触觉传感能力.

主要方法:

制造一种基于MXene和聚烯 (PAN) 的碳纤维增强双模体 triboelectric传感器 (MPBS).
将MPBS集成到柔性手指中,用于柔软的抓手.
开发一个卷积神经网络 (CNN) 用于数据融合和分析.
实现装备MPBS的机器人手臂用于自主任务.

主要成果:

该MPBS显示,使用2重%的MXene,电力输出增加了100%,实现了200厘米的无触摸传感范围.
软抓手通过触摸感应实现了99.4%的形状识别准确度.
这种支持人工智能的机器人手臂通过融合无触摸和触摸数据,以98.7%的准确率识别了10种物体类型.
成功展示了多任务应用程序,包括对象检测,智能分类和管道检查.

结论:

基于MXene和PAN的双模式 triboelectric传感器显著提高了机器人的感知和控制.
开发的系统提供了先进的无触摸和触摸感应,可实现精确的物体识别和自主任务执行.
这种新的传感器技术为更智能和多功能机器人应用铺平了道路.

关键词:

卷积神经网络是一种卷积神经网络.灵活的传感器灵活的传感器机器人手臂是一种机器人手臂.触觉感知是一种感知.triboelectric纳米发电机的使用情况

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