Biomimetic Neural Intelligent E-Skin System for Tactile Perception and Robotic Decision-Making.

Journal: ACS sensors
Published Date:

Abstract

The widespread application of electronic skin (e-skin) in human-machine interaction necessitates intelligent and information-rich systems. However, the rapid and efficient deployment of e-skin for high-precision multisensor fusion remains a critical challenge. This study introduces a pioneering biomimetic neural intelligent e-skin system that significantly enhances human-machine interaction and robotic perception capabilities. Our innovative approach integrates two novel e-skin technologies: a highly flexible multiwalled carbon nanotube (MWCNT) based e-skin for precise pressure sensing, and a gallium-indium alloy liquid metal e-skin with exceptional stretchability for motion capture. The MWCNT e-skin, fabricated through a simple carbon nanotube impregnation method, achieves ultrathinness (<1 mm), ease of preparation, and inherent flexibility. The liquid metal e-skin, developed using a unique dispersion and reconstruction method, exhibits excellent linearity ( > 99.9%) and impressive stretchability (∼700%). By integrating our two types of e-skins, our system has achieved multidegree-of-freedom control and tactile feedback for robotic arms. It demonstrates the capability to perform object grasping tasks solely through tactile feedback in visually challenging environments, including underwater conditions. The system achieves a 98.26% accuracy in identifying diverse objects and making autonomous decisions through tactile sensing alone, showcasing its self-decision-making abilities. This research establishes a new paradigm for intelligent robotics, advancing human-machine interaction in complex environments.

Authors

  • Deliang Li
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
  • Ruiwen Wang
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, People's Republic of China.
  • Kexin Fu
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, People's Republic of China.
  • Hao Quan
  • Hongguo Wei
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
  • Ruonan Liu
  • He Liu
    Division of Endodontics, Department of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, BC, Canada.
  • Zhiwei Fu
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, People's Republic of China.
  • Huilin Yuan
    College of Management, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China.
  • Hongxing Zhou
    Department of Nephrology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong Province, China.
  • Haoqi Bai
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, People's Republic of China.
  • Xiaoyu Cui
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110169, Liaoning, China.
  • Ye Tian
    State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics and Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China.