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Sensors 2014, 14(6), 10952-10976; doi:10.3390/s140610952

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
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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)
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Abstract

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).

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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.

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