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  • Interactive Robotics in Medicine and Care

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Reducing the Mental Model Mismatch in Cooperative Robot Teaching

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Prof. Dr.-Ing. Anna-Lisa Vollmer

Professur für Interaktive Robotik in Medizin und Pflege

Prof. Dr. Heiko Wersing

Phillip Richter

Wissenschaftlicher Mitarbeiter

Project duration

April 2023 - today

Cooperation partners

 

Logo Reducing Mental Model Mismatch
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Due to the increasing relevance of machine learning and artificial intelligence in everyday life, it is important to make the benefits accessible to inexperienced users. Of particular interest here are intelligent robots that are to be trained and taught by inexperienced users to perform specific tasks and support people in their activities. Intelligent assistance systems are also used in the fields of driving and medicine, where they are designed to adapt flexibly to the individual needs and wishes of users.

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However, challenges exist in relation to the complex and difficult to understand nature of such systems. The vision of cooperative intelligence requires a mutual understanding between humans and AI systems to enable effective collaboration and achieve common goals. This project focuses on the role of mental models in human-robot interaction. Human mental models are a key component for understanding robots. The 'Theory of Mind' shows that efficient cooperation between humans and robots strongly benefits from a small discrepancy in mental models. Therefore, this project is concerned with better understanding people's perceptions of robots' capabilities. To this end, various feedback and transparency mechanisms are used to first quantify and then reduce the discrepancy in the human's mental model of the robot. This project is being realized in cooperation with the Honda Research Institute in order to contribute to the long-term improvement of human-robot interaction and to create a bridge between humans and machines.

Research questions

  • How can the discrepancy between a person's mental model and the architecture of a complex technical system be quantified?
  • How can the discrepancy between this mental model and the architecture of a complex technical system be reduced?
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