Neurorobotic models for crossmodal joint attention and social interaction (A05)

• Subject Area: Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics ; Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: since 2016
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 261402652

The goals of project A5 are to realize human behaviour studies and neurorobotic models in order to better understand the influence of social behaviour on joint attention, in particular focused on affective behaviour and deictic communication. We will design and implement novel neurocomputational models based on recurrent self-organizing networks to model, represent, and process affective behaviour related to joint attention. We will also develop and evaluate continual learning in deep neural networks to process spatial information from deictic communication and to examine its relation to joint attention. Finally, we will develop a natural Human-Robot Interaction scenario to evaluate the impact of the proposed models on the behaviour of a robot when interacting with humans.

• DFG Programme: CRC/Transregios
• Subproject of: TRR 169: Crossmodal Learning: Adaptivity, Prediction and Interaction
• International Connection: China
• Applicant Institution: Universität Hamburg
• Project Heads: Professor Dr. Xun Liu; Professor Dr. Stefan Wermter