Smart hardware integration with advanced robot programming technologies for efficient reconfiguration of robot workcells

•Modular and largely passive hardware components aimed towards cost-effective, autonomous workcell reconfiguration.•A software backbone based on ROS, which provides modularity of all software components.•Fast programming of assembly tasks through kinesthetic guidance and script-based state machine d...

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Vydáno v:	Robotics and computer-integrated manufacturing Ročník 66; s. 101979
Hlavní autoři:	Gašpar, Timotej, Deniša, Miha, Radanovič, Primož, Ridge, Barry, Savarimuthu, T. Rajeeth, Kramberger, Aljaž, Priggemeyer, Marc, Roßmann, Jürgen, Wörgötter, Florentin, Ivanovska, Tatyana, Parizi, Shahab, Gosar, Žiga, Kovač, Igor, Ude, Aleš
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.12.2020 Elsevier BV
Témata:	Automation Industry 4.0 Manufacturing Passive reconfigurable hardware Programming by demonstration Reconfigurable hardware Reconfigurable manufacturing systems Reconfiguration Robots ROS Reconfigurable manufacturing systems Industry 4.0 Programming by demonstration Passive reconfigurable hardware ROS
ISSN:	0736-5845, 1879-2537
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Abstract	•Modular and largely passive hardware components aimed towards cost-effective, autonomous workcell reconfiguration.•A software backbone based on ROS, which provides modularity of all software components.•Fast programming of assembly tasks through kinesthetic guidance and script-based state machine description methods supported by visual programming interfaces.•Support for quick workcell reconfiguration by manipulating and exchanging the available hardware components, facilitated by a digital twin. The manufacturing industry is seeing an increase in demand for more custom-made, low-volume production. This type of production is rarely automated and is to a large extent still performed manually. To keep up with the competition and market demands, manufacturers will have to undertake the effort to automate such manufacturing processes. However, automating low-volume production is no small feat as the solution should be adaptable and future proof to unexpected changes in customers’ demands. In this paper, we propose a reconfigurable robot workcell aimed at automating low-volume production. The developed workcell can adapt to the changes in manufacturing processes by employing a number of passive, reconfigurable hardware elements, supported by the ROS-based, modular control software. To further facilitate and expedite the setup process, we integrated intuitive, user-friendly robot programming methods with the available hardware. The system was evaluated by implementing five production processes from different manufacturing industries.
AbstractList	The manufacturing industry is seeing an increase in demand for more custom-made, low-volume production. This type of production is rarely automated and is to a large extent still performed manually. To keep up with the competition and market demands, manufacturers will have to undertake the effort to automate such manufacturing processes. However, automating low-volume production is no small feat as the solution should be adaptable and future proof to unexpected changes in customers' demands. In this paper, we propose a reconfigurable robot workcell aimed at automating low-volume production. The developed workcell can adapt to the changes in manufacturing processes by employing a number of passive, reconfigurable hardware elements, supported by the ROS-based, modular control software. To further facilitate and expedite the setup process, we integrated intuitive, user-friendly robot programming methods with the available hardware. The system was evaluated by implementing five production processes from different manufacturing industries. •Modular and largely passive hardware components aimed towards cost-effective, autonomous workcell reconfiguration.•A software backbone based on ROS, which provides modularity of all software components.•Fast programming of assembly tasks through kinesthetic guidance and script-based state machine description methods supported by visual programming interfaces.•Support for quick workcell reconfiguration by manipulating and exchanging the available hardware components, facilitated by a digital twin. The manufacturing industry is seeing an increase in demand for more custom-made, low-volume production. This type of production is rarely automated and is to a large extent still performed manually. To keep up with the competition and market demands, manufacturers will have to undertake the effort to automate such manufacturing processes. However, automating low-volume production is no small feat as the solution should be adaptable and future proof to unexpected changes in customers’ demands. In this paper, we propose a reconfigurable robot workcell aimed at automating low-volume production. The developed workcell can adapt to the changes in manufacturing processes by employing a number of passive, reconfigurable hardware elements, supported by the ROS-based, modular control software. To further facilitate and expedite the setup process, we integrated intuitive, user-friendly robot programming methods with the available hardware. The system was evaluated by implementing five production processes from different manufacturing industries.
ArticleNumber	101979
Author	Savarimuthu, T. Rajeeth Deniša, Miha Ivanovska, Tatyana Ude, Aleš Gašpar, Timotej Kovač, Igor Gosar, Žiga Roßmann, Jürgen Kramberger, Aljaž Priggemeyer, Marc Wörgötter, Florentin Ridge, Barry Parizi, Shahab Radanovič, Primož
Author_xml	– sequence: 1 givenname: Timotej surname: Gašpar fullname: Gašpar, Timotej email: timotej.gaspar@ijs.si organization: Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia – sequence: 2 givenname: Miha surname: Deniša fullname: Deniša, Miha email: miha.denisa@ijs.si organization: Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia – sequence: 3 givenname: Primož surname: Radanovič fullname: Radanovič, Primož email: primoz.radanovic@ijs.si organization: Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia – sequence: 4 givenname: Barry surname: Ridge fullname: Ridge, Barry email: barry.ridge@ijs.si organization: Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia – sequence: 5 givenname: T. Rajeeth surname: Savarimuthu fullname: Savarimuthu, T. Rajeeth email: trs@mmmi.sdu.dk organization: Mærsk McKinney Møller Institute, University of Southern Denmark, 5230, Odense M, Denmark – sequence: 6 givenname: Aljaž surname: Kramberger fullname: Kramberger, Aljaž email: alk@mmmi.sdu.dk organization: Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia – sequence: 7 givenname: Marc surname: Priggemeyer fullname: Priggemeyer, Marc email: priggemeyer@mmi.rwth-aachen.de organization: Institute for Man-Machine Interaction, RWTH Aachen University, Ahornstraße 55, 52074 Aachen, Germany – sequence: 8 givenname: Jürgen surname: Roßmann fullname: Roßmann, Jürgen email: rossmann@mmi.rwth-aachen.de organization: Institute for Man-Machine Interaction, RWTH Aachen University, Ahornstraße 55, 52074 Aachen, Germany – sequence: 9 givenname: Florentin surname: Wörgötter fullname: Wörgötter, Florentin email: worgott@gwdg.de organization: Bernstein Center for Computational Neuroscience, Third Physics Institute, Georg-August-Universität Göttingen, Friedrich-Hund-Platz 1, 37077 Göttingen, Germany – sequence: 10 givenname: Tatyana surname: Ivanovska fullname: Ivanovska, Tatyana email: tiva@uni-goettingen.de organization: Bernstein Center for Computational Neuroscience, Third Physics Institute, Georg-August-Universität Göttingen, Friedrich-Hund-Platz 1, 37077 Göttingen, Germany – sequence: 11 givenname: Shahab surname: Parizi fullname: Parizi, Shahab email: msp@blue-ocean-robotics.com organization: Blue Ocean Robotics, Niels Bohrs Allé 185, 5220 Odense SØ, Denmark – sequence: 12 givenname: Žiga surname: Gosar fullname: Gosar, Žiga email: ziga.gosar@elvez.si organization: Elvez d.o.o., Ulica Antona Tomšiča 35, 1294 Višnja Gora, Slovenia – sequence: 13 givenname: Igor surname: Kovač fullname: Kovač, Igor email: igor.kovac@ijs.si organization: Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia – sequence: 14 givenname: Aleš surname: Ude fullname: Ude, Aleš email: ales.ude@ijs.si organization: Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute Jamova cesta 39, 1000 Ljubljana, Slovenia
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Snippet	•Modular and largely passive hardware components aimed towards cost-effective, autonomous workcell reconfiguration.•A software backbone based on ROS, which... The manufacturing industry is seeing an increase in demand for more custom-made, low-volume production. This type of production is rarely automated and is to a...
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SubjectTerms	Automation Industry 4.0 Manufacturing Passive reconfigurable hardware Programming by demonstration Reconfigurable hardware Reconfigurable manufacturing systems Reconfiguration Robots ROS
Title	Smart hardware integration with advanced robot programming technologies for efficient reconfiguration of robot workcells
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