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Multi-objective constructive cooperative coevolutionary optimization of robotic press-line tending
University West, Department of Engineering Science, Division of Production System. (PTW)ORCID iD: 0000-0002-0044-2795
University West, Department of Engineering Science, Division of Production System. (PTW)ORCID iD: 0000-0002-8878-2718
University West, Department of Engineering Science, Division of Production System. (PTW)ORCID iD: 0000-0002-6604-6904
University West, Department of Engineering Science, Division of Production System. Department of Signals and Systems, Chalmers University of Technology,Gothenburg, Sweden. (PTW)
2017 (English)In: Engineering optimization (Print), ISSN 0305-215X, E-ISSN 1029-0273, Vol. 49, no 10, 1685-1703 p.Article in journal (Refereed) Published
Abstract [en]

This article investigates multi-objective optimization of the robot trajectories and position-based operation-coordination of complex multi-robot systems, such as press lines, to improve the production rate and obtaining smooth motions to avoid excessive wear of the robots’ components. Different functions for handling the multiple objectives are evaluated on realworld press lines, including both scalarizing single-objective functions and Pareto-based multi-objective functions. Additionally, the Multi-Objective Constructive Cooperative Coevolutionary (moC3) algorithm is proposed, for Pareto-based optimization, which uses a novel constructive initialization of the subpopulations in a co-adaptive fashion. It was found that Paretobased optimization performs better than the scalarizing single-objective functions. Furthermore, moC3 gives substantially better results compared to manual online tuning, as currently used in the industry. Optimizing robot trajectories and operation-coordination of complex multi-robot systems using the proposed method with moC3 significantly improves productivity and reduces maintenance. This article hereby addresses the lack of systematic methods for effectively improving the productivity of press lines.

Place, publisher, year, edition, pages
Taylor & Francis, 2017. Vol. 49, no 10, 1685-1703 p.
Keyword [en]
Multi-objective optimization, coevolutionary optimization, press tending, multi-robot coordination
National Category
Production Engineering, Human Work Science and Ergonomics Robotics
Research subject
ENGINEERING, Manufacturing and materials engineering; Production Technology
Identifiers
URN: urn:nbn:se:hv:diva-10341DOI: 10.1080/0305215X.2016.1264220ISI: 000408952800003Scopus ID: 2-s2.0-85006124128OAI: oai:DiVA.org:hv-10341DiVA: diva2:1057898
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Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2017-09-20Bibliographically approved
In thesis
1. Multi-Robot Motion Planning Optimisation for Handling Sheet Metal Parts
Open this publication in new window or tab >>Multi-Robot Motion Planning Optimisation for Handling Sheet Metal Parts
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Motion planning for robot operations is concerned with path planning and trajectory generation. In multi-robot systems, i.e. with multiple robots operating simultaneously in a shared workspace, the motion planning also needs to coordinate the robots' motions to avoid collisions between them. The multi-robot coordination decides the cycle-time for the planned paths and trajectories since it determines to which extend the operations can take place simultaneously without colliding. To obtain the quickest cycle-time, there needs to bean optimal balance between, on the one hand short paths and fast trajectories, and on the other hand possibly longer paths and slower trajectories to allow that the operations take place simultaneously in the shared workspace. Due to the inter-dependencies, it becomes necessary to consider the path planning, trajectory generation and multi-robot coordination together as one optimisation problem in order to find this optimal balance.This thesis focusses on optimising the motion planning for multi-robot material handling systems of sheet metal parts. A methodology to model the relevant aspects of this motion planning problem together as one multi-disciplinary optimisation problem for Simulation based Optimisation (SBO) is proposed. The identified relevant aspects include path planning,trajectory generation, multi-robot coordination, collision-avoidance, motion smoothness, end-effectors' holding force, cycle-time, robot wear, energy efficiency, part deformations, induced stresses in the part, and end-effectors' design. The cycle-time is not always the (only) objective since it is sometimes equally/more important to minimise robot wear, energy consumption, and/or part deformations. Different scenarios for these other objectives are therefore also investigated. Specialised single- and multi-objective algorithms are proposed for optimising the motion planning of these multi-robot systems. This thesis also investigates how to optimise the velocity and acceleration profiles of the coordinated trajectories for multi-robot material handling of sheet metal parts. Another modelling methodology is proposed that is based on a novel mathematical model that parametrises the velocity and acceleration profiles of the trajectories, while including the relevant aspects of the motion planning problem excluding the path planning since the paths are now predefined.This enables generating optimised trajectories that have tailored velocity and acceleration profiles for the specific material handling operations in order to minimise the cycle-time,energy consumption, or deformations of the handled parts.The proposed methodologies are evaluated in different scenarios. This is done for real world industrial case studies that consider the multi-robot material handling of a multi-stage tandem sheet metal press line, which is used in the automotive industry to produce the cars' body panels. The optimisation results show that significant improvements can be obtained compared to the current industrial practice.

Place, publisher, year, edition, pages
Trollhättan: University West, 2017. 196 p.
Series
PhD Thesis: University West, 10
Keyword
Multi-robot systems, motion planning, modelling and simulation, optimisation
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Technology
Identifiers
urn:nbn:se:hv:diva-10947 (URN)978-91-87531-58-3 (ISBN)978-91-87531-57-6 (ISBN)
Supervisors
Available from: 2017-05-24 Created: 2017-05-24 Last updated: 2017-05-30Bibliographically approved

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