Medical Assistance Systems
Pepper
Pepper is a humanoid robot from Softbank Robotics / Aldebaran Robotics. Pepper can recognize faces and basic human emotions and has been designed for social human interaction. It can engage with humans through conversation and its touch screen.
Projects
- Flexible User-Robot Interaction
- The persuasiveness of robots in relation to the acceptance of health regulations
© Bielefeld University The project"The persuasiveness of robots in relation to the acceptance of health rules" explores the hypothesis that, in the face of the Corona pandemic, social robots in public places could be a useful tool to guide and remind people to abide by the general rules (e.g. wearing a mask, maintaining social distance).
- TRR 318 - Constructing Explainability (SFB)
© Bielefeld University The Collaborative Research Centre/Transregio "Constructing Explainability" (TRR 318), newly established by the DFG at the Universities of Bielefeld and Paderborn as of 1 July 2021, deals with the question of how transparency of algorithmic decisions can be established, especially through black-box methods of modern artificial intelligence. The central hypothesis of TRR 318 is that explanations are most effective when they are co-constructed by both the explainer and the receiver.
- Evening routine with a robot in a child psychiatry clinic
© Bielefeld University The project "Evening routine with a robot" pursues the approach of establishing an evening routine for children in the clinic for child psychiatry. Normally, the ratio of staff to patients is lowest in the evening hours, but children have difficulties calming down and falling asleep due to the unfamiliar environment and the time of day. An evening routine of a caregiver reading a book to them helps them become calmer. However, this is difficult to implement due to the limited staff ratio. A robot could support the staff by taking over evening tasks.
- Content Management System for a Robot as a Therapy Assistant (CMS)
- B05 - Explainability co-construction with an interactive learning robot
© Bielefeld University The overarching goal of B05 is to achieve context-sensitive explainability in interactive task learning - explainability that should be primarily implicit and not involve pronounced explanations. The projects considers the scenario of an AI system in the form of a humanoid robot equipped with a state-of-the-art learning mechanism. It also learns physical tasks in interaction with human users without deeper technical knowledge.
- Joint attention training
