Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26094
Title: Working with Walt: How a Cobot Was Developed and Inserted on an Auto Assembly Line
Authors: El Makrini, Ilias
Elprama, Shirley A.
VAN DEN BERGH, Jan 
Vanderborght, Bram
Knevels, Albert-Jan
Jewell, Charlotte I. C.
Stals, Frank
De Coppel, Geert
Ravyse, Ilse
Potargent, Johan
Berte, Jonathan
Diericx, Bram
Waegemans, Tim
Jacobs, An
Issue Date: 2018
Source: IEEE Robotics & Automation Magazine, 25 (2), p. 51-58
Abstract: — Collaborative robots or co-bots are a category of robots that are designed to work together with humans. By combining the strength of the robot such as precision and strength with the dexterity and problem-solving ability of the human, it is possible to achieve tasks that cannot be fully automated and improve the production quality and working conditions of workers. This paper presents the results of the ClaXon project which aims to study and implement interactions between humans and collaborative robots in factories. The project has led to the integration of a co-bot in the car manufacturing production plant of Audi Brussels in Belgium. Proofs of concepts were realized to study multimodal perceptions for human-robot interaction. The project addressed technical challenges regarding the introduction of collaborative robots on the factory floor. Social experiments were conducted with factory workers to assess the social acceptance of co-bots and study the interactions between the human and the robot.
Notes: El Makrini, I (reprint author), Vrije Univ Brussel, Robot Res Grp, Brussels, Belgium. ielmakri@vub.ac.be; selprama@vub.ac.be; jan.vandenbergh@uhasselt.be; bram.vanderborght@vub.ac.be; akn@melexis.com; charlotte.jewell@vub.be; fst@melexis.com; geert.decoppel@audi.de; IRavyse@softkinetic.com; johan.potargent@amsrobotics.com; jonathan.berte@robovision.be; bram.diericx@robovision.be; tim.waegeman@robovision.be; ajacobs@vub.ac.be
Keywords: collaborative robots; social human-robot interaction; computer vision; sensor fusion
Document URI: http://hdl.handle.net/1942/26094
ISSN: 1070-9932
e-ISSN: 1558-223X
DOI: 10.1109/MRA.2018.2815947
ISI #: 000435212800008
Category: A1
Type: Journal Contribution
Validations: ecoom 2019
Appears in Collections:Research publications

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