Next Article in Journal
Frequency-Shifted Interferometry — A Versatile Fiber-Optic Sensing Technique
Previous Article in Journal
Application of Wireless Power Transmission Systems in Wireless Capsule Endoscopy: An Overview
Previous Article in Special Issue
Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(6), 10952-10976;

Computational Intelligence Techniques for Tactile Sensing Systems

Department of Electric, Electronic, Telecommunication Engineering and Naval Architecture, DITEN, University of Genoa, Via Opera Pia 11a, 16145 Genova, Italy
Author to whom correspondence should be addressed.
Received: 15 January 2014 / Revised: 5 June 2014 / Accepted: 10 June 2014 / Published: 19 June 2014
(This article belongs to the Special Issue Tactile Sensors and Sensing Systems)
Full-Text   |   PDF [717 KB, uploaded 21 June 2014]


Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach. View Full-Text
Keywords: electronic skin; touch modalities; pattern recognition; computational intelligence; human-robot interaction electronic skin; touch modalities; pattern recognition; computational intelligence; human-robot interaction
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Gastaldo, P.; Pinna, L.; Seminara, L.; Valle, M.; Zunino, R. Computational Intelligence Techniques for Tactile Sensing Systems. Sensors 2014, 14, 10952-10976.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top