Responsive social positioning behaviour for semi-autonomous telepresence robots
Jered Vroon is a PhD student in the research group Human Media Interaction (HMI). His supervisor is prof.dr. V. Evers from the faculty of Electrical Engineering, Mathematics and Computer Science.
What if a social robot could detect, from your body language, how you would like it to behave differently? We investigate how a social robot can find appropriate behaviour through the interaction, by reactively adapting its behaviours to social feedback cues. Or, in other words, by being responsive.
We focus our work on social positioning behaviours, a starting point for social interaction with any mobile robot, as they are particularly relevant to the Teresa project which forms the main context for this thesis. In the Teresa project, we worked on a mobile videoconferencing system, a telepresence robot, through which elderly can participate in joint social activities if they can not be present in person – for example, because of a contagious sickness, or because they just feel too tired. Preliminary studies have shown that manually controlling a telepresence robot distracts users from the social interactions the system is supposed to support. For that reason, within the Teresa project, we developed autonomous social positioning behaviours for the robot. As inappropriate behaviours by the robot might reflect badly on the person it represents, within this context it is especially important that those autonomous behaviours are appropriate.
Previous work has investigated and established various norms for social positioning that can be applied to robotics, such as proxemics. But when we look at social positioning behaviours in context, we observe various dynamics that would be hard to capture in such norms – such as people with hearing problems who, during some conversations, actively lean towards their conversation partners, to the point of getting what would otherwise be seen as intimately close. In addition, many of the established norms depend on factors that are hard to reliably detect in practice, such as hearing problems, gender, and cultural background. We pose that using responsiveness would allow a robot to find appropriate behaviours, even in these cases.
This work is a step towards further developing responsive positioning behaviour for social robots. Starting from the related work and various observations, with elderly and telepresence robots, we develop the idea of responsiveness. We then work out this idea into a formal model. From the model, we further investigate the detection of social feedback cues and possible adaptation strategies. Together, these form the first steps in the realisation of robot responsiveness – and perhaps, one day, these first steps will result in a small step back, taken by a robot that noticed it was too close for your liking and adapted its position accordingly.