Structuring of tactile sensory information for category formation in robotics palpation

This paper proposes a framework to investigate the influence of physical interactions to sensory information, during robotic palpation. We embed a capacitive tactile sensor on a robotic arm to probe a soft phantom and detect and classify hard inclusions within it. A combination of PCA and K-Means cl...

Full description

Bibliographic Details
Main Authors: Scimeca, L, Maiolino, P, Bray, E, Iida, F
Format: Journal article
Language:English
Published: Springer 2020
_version_ 1797079690694885376
author Scimeca, L
Maiolino, P
Bray, E
Iida, F
author_facet Scimeca, L
Maiolino, P
Bray, E
Iida, F
author_sort Scimeca, L
collection OXFORD
description This paper proposes a framework to investigate the influence of physical interactions to sensory information, during robotic palpation. We embed a capacitive tactile sensor on a robotic arm to probe a soft phantom and detect and classify hard inclusions within it. A combination of PCA and K-Means clustering is used to: first, reduce the dimensionality of the spatiotemporal data obtained through the probing of each area in the phantom; second categorize the re-encoded data into a given number of categories. Results show that appropriate probing interactions can be useful in compensating for the quality of the data, or lack thereof. Finally, we test the proposed framework on a palpation scenario where a Support Vector Machine classifier is trained to discriminate amongst different types of hard inclusions. We show the proposed framework is capable of predicting the best-performing motion strategy, as well as the relative classification performance of the SVM classifier, solely based on unsupervised cluster analysis methods.
first_indexed 2024-03-07T00:49:22Z
format Journal article
id oxford-uuid:85d53497-dd18-40a6-95a7-a2971638f34c
institution University of Oxford
language English
last_indexed 2024-03-07T00:49:22Z
publishDate 2020
publisher Springer
record_format dspace
spelling oxford-uuid:85d53497-dd18-40a6-95a7-a2971638f34c2022-03-26T22:00:12ZStructuring of tactile sensory information for category formation in robotics palpationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:85d53497-dd18-40a6-95a7-a2971638f34cEnglishSymplectic ElementsSpringer2020Scimeca, LMaiolino, PBray, EIida, FThis paper proposes a framework to investigate the influence of physical interactions to sensory information, during robotic palpation. We embed a capacitive tactile sensor on a robotic arm to probe a soft phantom and detect and classify hard inclusions within it. A combination of PCA and K-Means clustering is used to: first, reduce the dimensionality of the spatiotemporal data obtained through the probing of each area in the phantom; second categorize the re-encoded data into a given number of categories. Results show that appropriate probing interactions can be useful in compensating for the quality of the data, or lack thereof. Finally, we test the proposed framework on a palpation scenario where a Support Vector Machine classifier is trained to discriminate amongst different types of hard inclusions. We show the proposed framework is capable of predicting the best-performing motion strategy, as well as the relative classification performance of the SVM classifier, solely based on unsupervised cluster analysis methods.
spellingShingle Scimeca, L
Maiolino, P
Bray, E
Iida, F
Structuring of tactile sensory information for category formation in robotics palpation
title Structuring of tactile sensory information for category formation in robotics palpation
title_full Structuring of tactile sensory information for category formation in robotics palpation
title_fullStr Structuring of tactile sensory information for category formation in robotics palpation
title_full_unstemmed Structuring of tactile sensory information for category formation in robotics palpation
title_short Structuring of tactile sensory information for category formation in robotics palpation
title_sort structuring of tactile sensory information for category formation in robotics palpation
work_keys_str_mv AT scimecal structuringoftactilesensoryinformationforcategoryformationinroboticspalpation
AT maiolinop structuringoftactilesensoryinformationforcategoryformationinroboticspalpation
AT braye structuringoftactilesensoryinformationforcategoryformationinroboticspalpation
AT iidaf structuringoftactilesensoryinformationforcategoryformationinroboticspalpation