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Related Experiment Video

Updated: Oct 18, 2025

Measurement of Vibration Detection Threshold and Tactile Spatial Acuity in Human Subjects
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A bionic piezoelectric tactile sensor for features recognition of object surface based on machine learning.

Yi Xin1, Meng Cui1, Chenyang Liu1

  • 1College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China.

The Review of Scientific Instruments
|October 2, 2021
PubMed
Summary

A novel bionic tactile sensor uses polyvinylidene fluoride piezoelectric film to identify object surface properties like softness and texture. This sensor achieves high accuracy in recognizing surface roughness, demonstrating potential for intelligent robots.

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Area of Science:

  • Robotics and Materials Science

Background:

  • Human fingertips possess sophisticated tactile sensing capabilities.
  • Developing artificial tactile sensors is crucial for advanced robotics and human-machine interaction.

Purpose of the Study:

  • To propose a bionic tactile sensor based on polyvinylidene fluoride (PVDF) piezoelectric film.
  • To enable the sensor to identify multiple surface properties: softness, viscoelasticity, thermal conductivity, and texture roughness.
  • To enhance texture recognition accuracy using advanced algorithms.

Main Methods:

  • Fabrication of a bionic tactile sensor using PVDF piezoelectric film.
  • Mounting the sensor on a bionic manipulator for object interaction (touching and sliding).
  • Utilizing time-domain signal features for initial property discrimination.
  • Employing Particle Swarm Optimization-Back Propagation (PSO-BP) neural network for texture roughness recognition.

Main Results:

  • The sensor successfully identified surface softness, viscoelasticity, and thermal conductivity.
  • The PSO-BP algorithm achieved 98% accuracy in identifying different texture roughnesses.
  • An average recognition accuracy of 94% was achieved for texture roughness.

Conclusions:

  • The developed bionic piezoelectric tactile sensor can effectively recognize diverse object surface features.
  • The PSO-BP algorithm significantly improves texture recognition accuracy.
  • The sensor shows promising applications in intelligent robotics and object surface analysis.