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Model-driven engineering for mobile robotic systems: a systematic mapping study
Univ Aquila, Dept Informat Engn Comp Sci & Math, Laquila, Italy.
Univ Aquila, Dept Informat Engn Comp Sci & Math, Laquila, Italy.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-0401-1036
Vrije Univ Amsterdam, Dept Comp Sci, Amsterdam, Netherlands..
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2022 (English)In: Software and Systems Modeling, ISSN 1619-1366, E-ISSN 1619-1374, Vol. 21, no 1, p. 19-49Article in journal (Refereed) Published
Abstract [en]

Mobile robots operate in various environments (e.g. aquatic, aerial, or terrestrial), they come in many diverse shapes and they are increasingly becoming parts of our lives. The successful engineering of mobile robotics systems demands the interdisciplinary collaboration of experts from different domains, such as mechanical and electrical engineering, artificial intelligence, and systems engineering. Research and industry have tried to tackle this heterogeneity by proposing a multitude of model-driven solutions to engineer the software of mobile robotics systems. However, there is no systematic study of the state of the art in model-driven engineering (MDE) for mobile robotics systems that could guide research or practitioners in finding model-driven solutions and tools to efficiently engineer mobile robotics systems. The paper is contributing to this direction by providing a map of software engineering research in MDE that investigates (1) which types of robots are supported by existing MDE approaches, (2) the types and characteristics of MRSs that are engineered using MDE approaches, (3) a description of how MDE approaches support the engineering of MRSs, (4) how existing MDE approaches are validated, and (5) how tools support existing MDE approaches. We also provide a replication package to assess, extend, and/or replicate the study. The results of this work and the highlighted challenges can guide researchers and practitioners from robotics and software engineering through the research landscape.

Place, publisher, year, edition, pages
SPRINGER HEIDELBERG , 2022. Vol. 21, no 1, p. 19-49
Keywords [en]
Model-driven engineering, Mobile robot systems, Systematic mapping study
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-55627DOI: 10.1007/s10270-021-00908-8ISI: 000683257900001Scopus ID: 2-s2.0-85112060247OAI: oai:DiVA.org:mdh-55627DiVA, id: diva2:1586337
Available from: 2021-08-19 Created: 2021-08-19 Last updated: 2024-01-17Bibliographically approved

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Ciccozzi, Federico

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