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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Veröffentlicht in: | Robotics and computer-integrated manufacturing 2020-12, Vol.66, p.101979, Article 101979 |
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Sprache: | eng |
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Zusammenfassung: | •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. |
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ISSN: | 0736-5845 1879-2537 |
DOI: | 10.1016/j.rcim.2020.101979 |