Socially perceptive robots: challenges and concerns Ginevra Castellano¹ and Christopher Peters² ¹ Department of Computer Science, School of EECS, Queen Mary University of London, Mile End Road, London E1 4NS, United Kingdom Email: ginevra@dcs.qmul.ac.uk ² Faculty of Engineering and Computing Department of Computing and the Digital Environment Coventry University, Coventry CV1 5FB, United Kingdom Email: Christopher.Peters@coventry.ac.uk Social robots are those endowed with communication channels and abilities that take inspiration from human beings. The scope of such abilities should include those allowing a robot to understand people’s affective states and expressions, intentions, actions, and to interpret them based on contextual information. Childcare robots are an example of robots that could take advantage of the integration of these capabilities. This commentary conducts a technical appraisal of the notion of autonomous childcare robots, focusing on these social perceptive capabilities, reviewing some of the key challenges remaining to be investigated by the research community in this respect. Keywords: human-robot interaction, social perceptive robots, social cues, affect recognition Ginevra Castellano received a Ph.D. in Electronic and Computer Engineering from University of Genoa, Italy, in 2008. She is currently a post-doctoral researcher at Queen Mary University of London, where she works in the EU FP7 LIREC (Living with Robots and intEractive Companions) project. Her research interests include affect recognition from face and body, closing the affective loop in virtual agents and robots, evaluation of affective interaction.