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Erschienen in:
Developing Embodied Agents for Education Applications with Accurate Synchronization of Gesture and Speech Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Shape Recognition Through Tactile Contour Tracing

A Simulation Study

verfasst von : André Frank Krause, Nalin Harischandra, Volker Dürr

Erschienen in: Transactions on Computational Collective Intelligence XX

Verlag: Springer International Publishing

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Abstract

We present Contour-net, a bio-inspired model for tactile contour-tracing driven by an Hopf oscillator. By controlling the rhythmic movements of a simulated insect-like feeler, the model executes both wide searching and local sampling movements. Contour-tracing is achieved by means of contact-induced phase-forwarding of the oscillator. To classify the shape of an object, collected contact events can be directly fed into machine learning algorithms with minimal pre-processing (scaling). Three types of classifiers were evaluated, the best one being a Support Vector Machine. The likelihood of correct classification steadily increases with the number of collected contacts, enabling an incremental classification during sampling. Given a sufficiently large training data set, tactile shape recognition can be achieved in a position-, orientation- and size-invariant manner. The suitability for robotic applications is discussed.

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Metadaten
Titel
Shape Recognition Through Tactile Contour Tracing
verfasst von
André Frank Krause
Nalin Harischandra
Volker Dürr
Copyright-Jahr
2015
Buch
Transactions on Computational Collective Intelligence XX

Print ISBN: 978-3-319-27542-0

Electronic ISBN: 978-3-319-27543-7

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-27543-7_3