Use of machine vision in collaborative robotics: An industrial case.

Alberto Tellaeche; Inaki Maurtua; Aitor Ibarguren

doi:10.1109/ETFA.2016.7733689

Use of machine vision in collaborative robotics: An industrial case.

Alberto Tellaeche
, Inaki Maurtua
, Aitor Ibarguren

TEKNIKER

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

9 Citations (Scopus)

Abstract

Robotic applications are evolving to a paradigm of collaborative robotics, where human workers and compliant robots work together to solve complex tasks, until now done fully manually. These tasks also present another challenging issue for the use of robotics, variability in part and tool positions, in robot placement and even in the targets for the robot operation. To comply with all this uncertainties while solving the work efficiently, the robot needs to be equipped with sensors that allow it perceive the environment. For this, machine vision techniques in all its variants (2D, 3D, point clouds) becomes fundamental. This paper outlines a real industrial case of collaborative robotics, and the details of use of machine vision techniques to cope with variability and uncertainties. The industrial case presented has been developed as part of the EuRoC European project, under the 7th European Framework.

Original language	English
Title of host publication	2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509013142
DOIs	https://doi.org/10.1109/ETFA.2016.7733689
Publication status	Published - 3 Nov 2016
Externally published	Yes
Event	21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016 - Berlin, Germany Duration: 6 Sept 2016 → 9 Sept 2016

Publication series

Name	IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume	2016-November
ISSN (Print)	1946-0740
ISSN (Electronic)	1946-0759

Conference

Conference	21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016
Country/Territory	Germany
City	Berlin
Period	6/09/16 → 9/09/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

collaborative robotics
human robot interaction
machine vision

Access to Document

10.1109/ETFA.2016.7733689

Cite this

Tellaeche, A., Maurtua, I., & Ibarguren, A. (2016). Use of machine vision in collaborative robotics: An industrial case. In 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016 Article 7733689 (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA; Vol. 2016-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETFA.2016.7733689

Tellaeche, Alberto ; Maurtua, Inaki ; Ibarguren, Aitor. / Use of machine vision in collaborative robotics : An industrial case. 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA).

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title = "Use of machine vision in collaborative robotics: An industrial case.",

abstract = "Robotic applications are evolving to a paradigm of collaborative robotics, where human workers and compliant robots work together to solve complex tasks, until now done fully manually. These tasks also present another challenging issue for the use of robotics, variability in part and tool positions, in robot placement and even in the targets for the robot operation. To comply with all this uncertainties while solving the work efficiently, the robot needs to be equipped with sensors that allow it perceive the environment. For this, machine vision techniques in all its variants (2D, 3D, point clouds) becomes fundamental. This paper outlines a real industrial case of collaborative robotics, and the details of use of machine vision techniques to cope with variability and uncertainties. The industrial case presented has been developed as part of the EuRoC European project, under the 7th European Framework.",

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author = "Alberto Tellaeche and Inaki Maurtua and Aitor Ibarguren",

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year = "2016",

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doi = "10.1109/ETFA.2016.7733689",

language = "English",

series = "IEEE International Conference on Emerging Technologies and Factory Automation, ETFA",

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Tellaeche, A, Maurtua, I & Ibarguren, A 2016, Use of machine vision in collaborative robotics: An industrial case. in 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016., 7733689, IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, vol. 2016-November, Institute of Electrical and Electronics Engineers Inc., 21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016, Berlin, Germany, 6/09/16. https://doi.org/10.1109/ETFA.2016.7733689

Use of machine vision in collaborative robotics: An industrial case. / Tellaeche, Alberto; Maurtua, Inaki; Ibarguren, Aitor.
2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016. Institute of Electrical and Electronics Engineers Inc., 2016. 7733689 (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA; Vol. 2016-November).

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

TY - GEN

T1 - Use of machine vision in collaborative robotics

T2 - 21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016

AU - Tellaeche, Alberto

AU - Maurtua, Inaki

AU - Ibarguren, Aitor

PY - 2016/11/3

Y1 - 2016/11/3

N2 - Robotic applications are evolving to a paradigm of collaborative robotics, where human workers and compliant robots work together to solve complex tasks, until now done fully manually. These tasks also present another challenging issue for the use of robotics, variability in part and tool positions, in robot placement and even in the targets for the robot operation. To comply with all this uncertainties while solving the work efficiently, the robot needs to be equipped with sensors that allow it perceive the environment. For this, machine vision techniques in all its variants (2D, 3D, point clouds) becomes fundamental. This paper outlines a real industrial case of collaborative robotics, and the details of use of machine vision techniques to cope with variability and uncertainties. The industrial case presented has been developed as part of the EuRoC European project, under the 7th European Framework.

AB - Robotic applications are evolving to a paradigm of collaborative robotics, where human workers and compliant robots work together to solve complex tasks, until now done fully manually. These tasks also present another challenging issue for the use of robotics, variability in part and tool positions, in robot placement and even in the targets for the robot operation. To comply with all this uncertainties while solving the work efficiently, the robot needs to be equipped with sensors that allow it perceive the environment. For this, machine vision techniques in all its variants (2D, 3D, point clouds) becomes fundamental. This paper outlines a real industrial case of collaborative robotics, and the details of use of machine vision techniques to cope with variability and uncertainties. The industrial case presented has been developed as part of the EuRoC European project, under the 7th European Framework.

KW - collaborative robotics

KW - human robot interaction

KW - machine vision

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DO - 10.1109/ETFA.2016.7733689

M3 - Conference contribution

AN - SCOPUS:84996520516

T3 - IEEE International Conference on Emerging Technologies and Factory Automation, ETFA

BT - 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 6 September 2016 through 9 September 2016

ER -

Tellaeche A, Maurtua I, Ibarguren A. Use of machine vision in collaborative robotics: An industrial case. In 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7733689. (IEEE International Conference on Emerging Technologies and Factory Automation, ETFA). doi: 10.1109/ETFA.2016.7733689

Use of machine vision in collaborative robotics: An industrial case.

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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