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A Non-Array Type Cut to Shape Soft Slip Detection Sensor Applicable to Arbitrary Surface.

Sung Joon Kim¹, Seung Ho Lee¹, Hyungpil Moon¹

¹School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea.

Sensors (Basel, Switzerland)

|November 4, 2020

Summary

This summary is machine-generated.

A novel skin-type slip sensor for robots offers adaptable attachment to curved surfaces. This tactile sensor achieves over 95% accuracy in detecting object slippage using artificial neural networks.

Keywords:

e-skin slip detection tactile sensor

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Measurement of Vibration Detection Threshold and Tactile Spatial Acuity in Human Subjects

Measurement of Vibration Detection Threshold and Tactile Spatial Acuity in Human Subjects

Published on: September 1, 2016

Area of Science:

Robotics
Materials Science
Artificial Intelligence

Background:

Tactile sensing is crucial for robotic manipulation and object handling.
Current tactile sensors often lack adaptability to complex robot geometries.
Detecting slippage is vital for preventing damage during object interaction.

Purpose of the Study:

To develop and evaluate a versatile skin-type slip sensor for robotic applications.
To assess the sensor's performance on surfaces with varying curvatures.
To investigate the efficacy of artificial neural networks in slip detection using sensor data.

Main Methods:

A flexible, cut-and-fit skin-type slip sensor with a non-array structure was designed.
Vibration signals from the sensor were analyzed in the time-frequency domain.
Four artificial neural network models were employed for slip detection and comparison.
Sensor performance was evaluated across different curvatures and contact points.

Main Results:

The developed sensor demonstrated adaptability to various robot surface curvatures.
Slip detection accuracy averaged 95.73% across diverse testing conditions.
Analysis provided insights into the strengths and weaknesses of different neural network models for this application.

Conclusions:

The proposed skin-type slip sensor offers a practical solution for enhancing robotic tactile perception.
The sensor's design allows for customization and robust operation even with partial damage.
Artificial neural networks effectively process sensor data for accurate slip detection, paving the way for more sophisticated robotic grasping.