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A constraint programming model for the scheduling and workspace layout design of a dual-arm multi-tool assembly robot
ABB Corporate Research, Västerås, Sweden.
RISE Research Institutes of Sweden, Uppsala, Sweden.
KTH Royal Institute of Technology, Stockholm, Sweden.
Uppsala University, Uppsala, Sweden.
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2023 (English)In: Constraints, ISSN 1383-7133, E-ISSN 1572-9354, Vol. 28, no 2, p. 71-104Article in journal (Refereed) Published
Abstract [en]

The generation of a robot program can be seen as a collection of sub-problems, where many combinations of some of these sub-problems are well studied. The performance of a robot program is strongly conditioned by the location of the tasks. However, the scope of previous methods does not include workspace layout design, likely missing high-quality solutions. In industrial applications, designing robot workspace layout is part of the commissioning. We broaden the scope and show how to model a dual-arm multi-tool robot assembly problem. Our model includes more robot programming sub-problems than previous methods, as well as workspace layout design. We propose a constraint programming formulation in MiniZinc that includes elements from scheduling and routing, extended with variable task locations. We evaluate the model on realistic assembly problems and workspaces, utilizing the dual-arm YuMi robot from ABB Ltd. We also evaluate redundant constraints and various formulations for avoiding arm-to-arm collisions. The best model variant quickly finds high-quality solutions for all problem instances. This demonstrates the potential of our approach as a valuable tool for a robot programmer.

Place, publisher, year, edition, pages
Springer, 2023. Vol. 28, no 2, p. 71-104
Keywords [en]
Assembly manufacturing, Constraint programming, Robot planning and scheduling, Workspace layout design
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:oru:diva-107731DOI: 10.1007/s10601-023-09345-4ISI: 001032500800001Scopus ID: 2-s2.0-85164960102OAI: oai:DiVA.org:oru-107731DiVA, id: diva2:1791335
Available from: 2023-08-25 Created: 2023-08-25 Last updated: 2025-02-07Bibliographically approved

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Pecora, Federico

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