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Publication - Professor Christopher Melhuish

    Perception of own and robot engagement in human-robot interactions and their dependence on robotics knowledge

    Citation

    Hall, JR, Tritton, T, Rowe, ACM, Pipe, AG, Melhuish, CR & Leonards, UB, 2014, ‘Perception of own and robot engagement in human-robot interactions and their dependence on robotics knowledge’. Robotics and Autonomous Systems, vol 62., pp. 392-399

    Abstract

    Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human's own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot's engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human-robot interactions without affecting the impact of the type of signal sent by the robot.

    Full details in the University publications repository