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Related Experiment Video

Updated: Jul 21, 2025

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs
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Intelligent soft robotic fingers with multi-modality perception ability.

Tongjing Wu1,2, Haitao Deng1, Zhongda Sun2

  • 1School of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

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|July 28, 2023
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Summary
This summary is machine-generated.

This study presents a bionic sensing system using triboelectric nanogenerators (TENGs) for real-time object recognition in Industry 4.0. The system enables intelligent robotic manipulators for applications like automatic component sorting.

Keywords:
BionicsControl engineeringRobotics

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Area of Science:

  • Materials Science
  • Robotics
  • Artificial Intelligence

Background:

  • Industry 4.0 drives demand for advanced automation in production lines.
  • Real-time object recognition is crucial for efficient industrial processes.
  • Developing sophisticated sensing systems is key to enhancing robotic capabilities.

Purpose of the Study:

  • To develop a bionic sensing system for real-time object recognition.
  • To integrate self-powered triboelectric nanogenerators (TENGs) with soft robotic actuators.
  • To enable intelligent perception for robotic manipulators in industrial applications.

Main Methods:

  • Fabrication of single-layer TENGs (SL-TENGs) and comb-shaped TENGs (CS-TENGs) as touch and bending sensors.
  • Integration of TENG sensors with a three-soft-actuator robotic manipulator.
  • Application of a one-dimensional convolutional neural network (1D-CNN) for sensor data analysis.

Main Results:

  • TENG sensors demonstrated high sensitivity (110 V/kPa) and durability (20,000 cycles).
  • The system successfully detected grasping location, contact pressure, and bending curvature.
  • The 1D-CNN achieved 98.96% accuracy in extracting sensor information.

Conclusions:

  • The bionic sensing system provides multi-modality perception for robotic manipulators.
  • The integrated system shows significant potential for Industry 4.0 applications, including automatic component sorting.
  • This work highlights the feasibility of using TENG-based self-powered sensors in advanced AI-driven robotic systems.