Model-driven engineering for mobile robotic systems: a systematic mapping study
Artikel i vetenskaplig tidskrift, 2021

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.

Systematic mapping study

Model-driven engineering

Mobile robot systems


Giuseppina Lucia Casalaro

Universita degli Studi dell'Aquila

Giulio Cattivera

Universita degli Studi dell'Aquila

Federico Ciccozzi

Mälardalens högskola

Ivano Malavolta

Vrije Universiteit Amsterdam

Andreas Wortmann

RWTH Aachen University

Patrizio Pelliccione

Chalmers, Data- och informationsteknik, Software Engineering, Software Engineering for Testing, Requirements, Innovation and Psychology

Universita degli Studi dell'Aquila

Software and Systems Modeling

1619-1366 (ISSN) 1619-1374 (eISSN)

Vol. In Press



Inbäddad systemteknik

Robotteknik och automation



Mer information

Senast uppdaterat