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Large-Scale Tactile Detection System Based on Supervised Learning for Service Robots Human Interaction.

Fábio Cunha1,2, Tiago Ribeiro1,2, Gil Lopes3

  • 1Industrial Electronics Department, University of Minho, 4800-058 Guimarães, Portugal.

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|January 21, 2023
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Summary
This summary is machine-generated.

A new tactile detection system uses machine learning and computer vision to map forearm sleeve surfaces for enhanced human-robot interaction. This system enables collaborative robots like CHARMIE to detect contact and perform specific behaviors, improving safety and functionality.

Keywords:
Artificial Neural NetworksMachine Learninghuman-machine interfaceroboticsservice robotstouch sensor

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Service robots require advanced sensory capabilities for safe and effective human interaction.
  • Existing tactile systems often lack comprehensive coverage or adaptability for dynamic environments.

Purpose of the Study:

  • To develop a large-scale tactile detection system for a collaborative robot (CHARMIE).
  • To enable robust forearm surface contact detection for improved human-robot interaction.

Main Methods:

  • Utilized a soft structure with Machine Learning and Computer Vision algorithms.
  • Developed an Artificial Neural Network (ANN), the Section Detection Network (SDN), using Supervised Learning.
  • Employed Stratified K-Fold Cross Validation (SKFCV) for dataset division and model evaluation.

Main Results:

  • Achieved a test data accuracy higher than 80% for contact location prediction.
  • Demonstrated real-time evaluation via a graphical interface showing predicted class and probability.
  • The system maps forearm sleeve surfaces, enabling segmented contact detection.

Conclusions:

  • The proposed tactile detection system significantly enhances human-robot interaction capabilities.
  • This technology holds substantial potential for service robots in domestic and medical settings.
  • The system's modular design allows for configurable functionalities based on detected contact points.