Project description

Autonomous robots for assistance functions - Interactive basic skills (ARAIG)

ARAIG was a HFC-led consortium consisting of the Fraunhofer Institute for Manufacturing Engineering and Automation IPA, the Federal Institute for Occupational Safety and Health BAuA and the Competence Centre ELSI of the Technische Universität Berlin. As the associated research project for the call "Autonomous robots for assistance functions: Interactive basic skills", it was funded by the Federal Ministry of Education and Research BMBF. Through activities such as workshops, expert conferences and networking, the efforts of the call’s funded research projects were aligned, and a cross-project transfer of knowledge was facilitated.

In addition to collaborative activities, each ARAIG project partner also worked on its own research topics. Our part as HFC was to investigate a model for describing the quality of robots both from a technical point of view and from the point of view of user acceptance. In addition, we researched the influence of robot morphology on user expectation and behaviour. Initial results were discussed in September 2018 with the scientific community, manufacturers and users during the BAuA workshop series "Human-Robot Cooperation - Designing Safe, Healthy and Competitive Work" (link to BauA). In the further course of the project, we also developed a heuristic classification of human-robot interactions (HRI) and conducted a study on the suitability of virtual realities for HRI research.

Project partners

  • Firmenlogo von Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA
  • Firmenlogo von Bundesanstalt für Arbeitsschutz und Arbeitsmedizin BAuA
  • Firmenlogo von Kompetenzzentrum ELSI der Technischen Universität Berlin

Contact person

Foto von Astrid Oehme

Dr.

Astrid Oehme

oehme@human-factors.de

Related Publications

Plomin, J., Schweidler, P., & Oehme, A. (2023). Virtual reality check: a comparison of virtual reality, screen-based, and real world settings as research methods for HRI. Frontiers in Robotics and AI, 10. https://doi.org/10.3389%2Ffrobt.2023.1156715

Schweidler, P., Tausch, A., Oehme, A. & Jürgensohn, T. (2020). MRI-Szenarien einfach klassifizieren mit der Kontext-Person-Roboter-Heuristik „KOPROH“. Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, baua: Fokus, Dortmund. https://doi.org/10.21934/baua:fokus20200711

Schweidler, P., Oehme, A. & Jürgensohn, T. (2020). Objektivierbare Performancekriterien. In: Autonome Roboter für Assistenzfunktionen: Interaktive Grundfertigkeiten – Ergebnisse und Forschungsperspektiven des Förderprogramms ARA1, S. 57-75. Dortmund: Bundesanstalt für Arbeitsschutz und Arbeitsmedizin. https://www.doi.org/10.21934/baua:bericht20200917

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