My research falls within the EU project DE-ENIGMA, which aims to develop a novel intervention for autistic children to learn socio-emotional skills using Robokind's humanoid robot Zeno (R25 model). Autism Spectrum Condition is a neurodevelopmental condition, characterised by difficulties in social communication and interaction, and restricted, repetitive behaviour and interests. In my work, I look at human-robot interaction from the perspective of the computational accounts of autistic perception. The research questions I address are related to how do autistic children perceive social robots and how we can accommodate the aberrant perception of autistic children through the design of a robot's behaviour. Specifically, I look at how we can design social interaction with a robot that is perceived as being predictable by autistic children.
Zaga, C., Charisi, V., Schadenberg, B., Reidsma, D., Neerincx, M., Prescott, T., ... Evers, V. (2017). Growing-Up Hand in Hand with Robots: Designing and Evaluating Child-Robot Interaction from a Developmental Perspective. In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction (pp. 429-430). New York, NY, USA: ACM. DOI: 10.1145/3029798.3029804
Schadenberg, B. R., Aly, A. (Ed.), Neerincx, M. A., Griffiths, S. (Ed.), Cnossen, F., Stramandinoli, F. (Ed.), ... Nori, F. (Ed.) (2016). Personalising game difficulty to keep children motivated to play with a social robot: A Bayesian approach. Cognitive systems research, 43, 222-231. DOI: 10.1016/j.cogsys.2016.08.003