Arvid Butting

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About

Arvid Butting is a leading researcher at the intersection of model-driven engineering (MDE) and service robotics, dedicated to making robotic systems more accessible and reusable. His key research areas include domain-specific languages (DSLs), separation of concerns in robotics, and platform-independent modeling for automation. Butting’s most influential work, “Model-driven separation of concerns for service robotics” (20 citations), addresses a critical bottleneck: the tendency of robotics to rely on general-purpose software modeling languages, which forces domain experts into a monolithic development paradigm. He proposes an infrastructure that empowers experts to use more appropriate DSLs, enabling modular, reusable applications. Expanding on this, his paper “Modeling Reusable, Platform-Independent Robot Assembly Processes” (9 citations) targets smart factories, introducing a domain-specific approach for compliant robots to be easily programmed by non-roboticists. In “Executing Robot Task Models in Dynamic Environments” (4 citations), Butting presents the *iserveU* family of executable DSLs, which leverage run-time model transformations to separate the concerns of domain and robotics experts. Through these contributions, Butting is shaping a future where flexible, user-friendly robotics can be deployed in dynamic, real-world environments.