Flexible multimodal tactile sensing system for object identification

Jonathan Engel; Nannan Chen; Craig Tucker; Chang Liu; Sung Hoon Kim; Douglas Jones

doi:10.1109/ICSENS.2007.355530

Flexible multimodal tactile sensing system for object identification

Jonathan Engel^*, Nannan Chen, Craig Tucker, Chang Liu, Sung Hoon Kim, Douglas Jones

^*Corresponding author for this work

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

34 Scopus citations

Abstract

This work presents results towards realizing a flexible multimodal tactile sensing system for object identification. Using polymer substrates and simple fabrication, robust devices are made that can identify objects based on texture, temperature, as well as material properties such as hardness and thermal conductivity. These capabilities are possible using signal processing techniques and physical models along with individual sensing structures inspired by the specialization found in biological skin. These structures are used to sense various object parameters, and array-wide processing to identify texture using a Maximum Likelihood decision rule. 80% texture classification is achieved. In blind object identification tests, over 90% correct identification was achieved by measurement of material properties.

Original language	English (US)
Title of host publication	2006 5th IEEE Conference on Sensors
Pages	563-566
Number of pages	4
DOIs	https://doi.org/10.1109/ICSENS.2007.355530
State	Published - Dec 1 2006
Event	2006 5th IEEE Conference on Sensors - Daegu, Korea, Republic of Duration: Oct 22 2006 → Oct 25 2006

Publication series

Name	Proceedings of IEEE Sensors

Other

Other	2006 5th IEEE Conference on Sensors
Country/Territory	Korea, Republic of
City	Daegu
Period	10/22/06 → 10/25/06

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/ICSENS.2007.355530

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title = "Flexible multimodal tactile sensing system for object identification",

abstract = "This work presents results towards realizing a flexible multimodal tactile sensing system for object identification. Using polymer substrates and simple fabrication, robust devices are made that can identify objects based on texture, temperature, as well as material properties such as hardness and thermal conductivity. These capabilities are possible using signal processing techniques and physical models along with individual sensing structures inspired by the specialization found in biological skin. These structures are used to sense various object parameters, and array-wide processing to identify texture using a Maximum Likelihood decision rule. 80% texture classification is achieved. In blind object identification tests, over 90% correct identification was achieved by measurement of material properties.",

author = "Jonathan Engel and Nannan Chen and Craig Tucker and Chang Liu and Kim, {Sung Hoon} and Douglas Jones",

year = "2006",

month = dec,

day = "1",

doi = "10.1109/ICSENS.2007.355530",

language = "English (US)",

isbn = "1424403766",

series = "Proceedings of IEEE Sensors",

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note = "2006 5th IEEE Conference on Sensors ; Conference date: 22-10-2006 Through 25-10-2006",

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TY - GEN

T1 - Flexible multimodal tactile sensing system for object identification

AU - Engel, Jonathan

AU - Chen, Nannan

AU - Tucker, Craig

AU - Liu, Chang

AU - Kim, Sung Hoon

AU - Jones, Douglas

PY - 2006/12/1

Y1 - 2006/12/1

N2 - This work presents results towards realizing a flexible multimodal tactile sensing system for object identification. Using polymer substrates and simple fabrication, robust devices are made that can identify objects based on texture, temperature, as well as material properties such as hardness and thermal conductivity. These capabilities are possible using signal processing techniques and physical models along with individual sensing structures inspired by the specialization found in biological skin. These structures are used to sense various object parameters, and array-wide processing to identify texture using a Maximum Likelihood decision rule. 80% texture classification is achieved. In blind object identification tests, over 90% correct identification was achieved by measurement of material properties.

AB - This work presents results towards realizing a flexible multimodal tactile sensing system for object identification. Using polymer substrates and simple fabrication, robust devices are made that can identify objects based on texture, temperature, as well as material properties such as hardness and thermal conductivity. These capabilities are possible using signal processing techniques and physical models along with individual sensing structures inspired by the specialization found in biological skin. These structures are used to sense various object parameters, and array-wide processing to identify texture using a Maximum Likelihood decision rule. 80% texture classification is achieved. In blind object identification tests, over 90% correct identification was achieved by measurement of material properties.

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U2 - 10.1109/ICSENS.2007.355530

DO - 10.1109/ICSENS.2007.355530

M3 - Conference contribution

AN - SCOPUS:50149113331

SN - 1424403766

SN - 9781424403769

T3 - Proceedings of IEEE Sensors

SP - 563

EP - 566

BT - 2006 5th IEEE Conference on Sensors

T2 - 2006 5th IEEE Conference on Sensors

Y2 - 22 October 2006 through 25 October 2006

ER -

Flexible multimodal tactile sensing system for object identification

Abstract

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