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Months of entry
At present there are many sensors and actuators in every device - so they may become embedded in a physical reality. For robots that move around in a specific setting and need to localise and orient themselves, the development of proper methods of control is a pressing need. The embedded, embodied nature of human cognition is an inspiration for this, and vise versa, computational modeling of such tasks can give insight into the nature of human mental processing.
Making sense of sensor data - developing artificial perception - is no trivial task. Auditory scene analysis: the perception, recognition and even appreciation of sound stimuli for speech and music require modeling and representation at many levels and the same hold for visual object recognition and computer vision. In this area face recognition - and the recognition of emotion from faces is a rapidly growing application area. In the area of action and motor planning, sensorimotor integration and action there are strong links with research in DCC.
At Radboud University we also look beyond the technical side of creating robots that can move, talk and interpret emotions as humans do. We believe that a robot needs to do more than simply function to its best ability. A robot that humans distrust will fail even if it is well programmed. Culture also plays a role in this; people in Japan are more open to the possibilities of robots than in, for example, the Netherlands. We will teach you how to evaluate humans’ attitudes towards a robot in order to use that information to create robots that will be accepted and trusted and therefore perform even better. All these areas get attention in this specialisation in Robot Recognition and the student has freedom to choose a focus and contribute to ongoing research.
*This is a specialisation of the Master's in Artificial Intelligence
Qualification and course duration
MSc by research
Course contact details
- Admission Office