Virtual Teaching for Assembly Tasks Planning

Alexandre Angleraud; Robert Codd-Downey; Metodi Netzev; Quentin Houbre; Roel Pieters

doi:10.1109/ICHMS49158.2020.9209478

Virtual Teaching for Assembly Tasks Planning

Alexandre Angleraud, Robert Codd-Downey, Metodi Netzev, Quentin Houbre, Roel Pieters

Automation Technology and Mechanical Engineering

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

4 Citations (Scopus)

51 Downloads (Pure)

Abstract

Small and Medium-size Enterprises require increasingly versatile robots that are capable of learning new skills during their operating life span, in addition to the ability to integrate themselves into human teams as a new and effective partner. Teaching information and skills to a robot can quickly become very complex, especially when considering that the human partner of the robot is inexperienced in the field and does not have access to intuitive interaction channels to train such robots. In this work, a system is proposed that can virtually define an assembly task, based on CAD modelling that describe constraints between assembly parts. These constraints are then extracted in an ontology which is automatically translated into Simple Temporal Networks (STNs) leading to joint action plans.Results show the automatic translation between virtual teaching and knowledge acquired by the robot on a peg-in-hole problem before illustrating the connection to planning for human-robot collaborative tasks. As a proof of concept, these developments demonstrate that a CAD guided assembly planner can circumvent the need for skilled robot programming.

Original language	English
Title of host publication	Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020
Editors	Giancarlo Fortino, Fei-Yue Wang, Andreas Nurnberger, David Kaber, Rino Falcone, David Mendonca, Zhiwen Yu, Antonio Guerrieri
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9781728158716
ISBN (Print)	978-1-7281-5872-3
DOIs	https://doi.org/10.1109/ICHMS49158.2020.9209478
Publication status	Published - Sept 2020
Publication type	A4 Article in conference proceedings
Event	IEEE International Conference on Human-Machine Systems - Virtual, Rome, Italy Duration: 7 Sept 2020 → 9 Sept 2020

Conference

Conference	IEEE International Conference on Human-Machine Systems
Country/Territory	Italy
City	Virtual, Rome
Period	7/09/20 → 9/09/20

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Human-Computer Interaction

Access to Document

10.1109/ICHMS49158.2020.9209478

Virtual Teaching for Assembly 2020
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Accepted author manuscript, 3.45 MB

http://urn.fi/URN:NBN:fi:tuni-202011308314

Cite this

Angleraud, A., Codd-Downey, R., Netzev, M., Houbre, Q., & Pieters, R. (2020). Virtual Teaching for Assembly Tasks Planning. In G. Fortino, F.-Y. Wang, A. Nurnberger, D. Kaber, R. Falcone, D. Mendonca, Z. Yu, & A. Guerrieri (Eds.), Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020 Article 9209478 IEEE. https://doi.org/10.1109/ICHMS49158.2020.9209478

@inproceedings{349dcf082cb84b6792c5d490b35376eb,

title = "Virtual Teaching for Assembly Tasks Planning",

abstract = "Small and Medium-size Enterprises require increasingly versatile robots that are capable of learning new skills during their operating life span, in addition to the ability to integrate themselves into human teams as a new and effective partner. Teaching information and skills to a robot can quickly become very complex, especially when considering that the human partner of the robot is inexperienced in the field and does not have access to intuitive interaction channels to train such robots. In this work, a system is proposed that can virtually define an assembly task, based on CAD modelling that describe constraints between assembly parts. These constraints are then extracted in an ontology which is automatically translated into Simple Temporal Networks (STNs) leading to joint action plans.Results show the automatic translation between virtual teaching and knowledge acquired by the robot on a peg-in-hole problem before illustrating the connection to planning for human-robot collaborative tasks. As a proof of concept, these developments demonstrate that a CAD guided assembly planner can circumvent the need for skilled robot programming. ",

author = "Alexandre Angleraud and Robert Codd-Downey and Metodi Netzev and Quentin Houbre and Roel Pieters",

note = "Funding Information: International collaboration for this project was funded by the York University Vision Science to Application (VISTA) visiting Researcher Grant and the NSERC Canadian Robotics Network visiting Researcher Grant. Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; IEEE International Conference on Human-Machine Systems ; Conference date: 07-09-2020 Through 09-09-2020",

year = "2020",

month = sep,

doi = "10.1109/ICHMS49158.2020.9209478",

language = "English",

isbn = "978-1-7281-5872-3",

editor = "Giancarlo Fortino and Fei-Yue Wang and Andreas Nurnberger and David Kaber and Rino Falcone and David Mendonca and Zhiwen Yu and Antonio Guerrieri",

booktitle = "Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020",

publisher = "IEEE",

}

Angleraud, A, Codd-Downey, R, Netzev, M , Houbre, Q & Pieters, R 2020, Virtual Teaching for Assembly Tasks Planning. in G Fortino, F-Y Wang, A Nurnberger, D Kaber, R Falcone, D Mendonca, Z Yu & A Guerrieri (eds), Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020., 9209478, IEEE, IEEE International Conference on Human-Machine Systems, Virtual, Rome, Italy, 7/09/20. https://doi.org/10.1109/ICHMS49158.2020.9209478

Virtual Teaching for Assembly Tasks Planning. / Angleraud, Alexandre; Codd-Downey, Robert; Netzev, Metodi et al.
Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020. ed. / Giancarlo Fortino; Fei-Yue Wang; Andreas Nurnberger; David Kaber; Rino Falcone; David Mendonca; Zhiwen Yu; Antonio Guerrieri. IEEE, 2020. 9209478.

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

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AU - Angleraud, Alexandre

AU - Codd-Downey, Robert

AU - Netzev, Metodi

AU - Houbre, Quentin

AU - Pieters, Roel

N1 - Funding Information: International collaboration for this project was funded by the York University Vision Science to Application (VISTA) visiting Researcher Grant and the NSERC Canadian Robotics Network visiting Researcher Grant. Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/9

Y1 - 2020/9

N2 - Small and Medium-size Enterprises require increasingly versatile robots that are capable of learning new skills during their operating life span, in addition to the ability to integrate themselves into human teams as a new and effective partner. Teaching information and skills to a robot can quickly become very complex, especially when considering that the human partner of the robot is inexperienced in the field and does not have access to intuitive interaction channels to train such robots. In this work, a system is proposed that can virtually define an assembly task, based on CAD modelling that describe constraints between assembly parts. These constraints are then extracted in an ontology which is automatically translated into Simple Temporal Networks (STNs) leading to joint action plans.Results show the automatic translation between virtual teaching and knowledge acquired by the robot on a peg-in-hole problem before illustrating the connection to planning for human-robot collaborative tasks. As a proof of concept, these developments demonstrate that a CAD guided assembly planner can circumvent the need for skilled robot programming.

AB - Small and Medium-size Enterprises require increasingly versatile robots that are capable of learning new skills during their operating life span, in addition to the ability to integrate themselves into human teams as a new and effective partner. Teaching information and skills to a robot can quickly become very complex, especially when considering that the human partner of the robot is inexperienced in the field and does not have access to intuitive interaction channels to train such robots. In this work, a system is proposed that can virtually define an assembly task, based on CAD modelling that describe constraints between assembly parts. These constraints are then extracted in an ontology which is automatically translated into Simple Temporal Networks (STNs) leading to joint action plans.Results show the automatic translation between virtual teaching and knowledge acquired by the robot on a peg-in-hole problem before illustrating the connection to planning for human-robot collaborative tasks. As a proof of concept, these developments demonstrate that a CAD guided assembly planner can circumvent the need for skilled robot programming.

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DO - 10.1109/ICHMS49158.2020.9209478

M3 - Conference contribution

AN - SCOPUS:85093960780

SN - 978-1-7281-5872-3

BT - Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS 2020

A2 - Fortino, Giancarlo

A2 - Wang, Fei-Yue

A2 - Nurnberger, Andreas

A2 - Kaber, David

A2 - Falcone, Rino

A2 - Mendonca, David

A2 - Yu, Zhiwen

A2 - Guerrieri, Antonio

PB - IEEE

T2 - IEEE International Conference on Human-Machine Systems

Y2 - 7 September 2020 through 9 September 2020

ER -

Virtual Teaching for Assembly Tasks Planning

Abstract

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ASJC Scopus subject areas

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