Meet
Nipuni Wijesinghe is a PhD student in the Faculty of Science and Technology at the University of Canberra, with a background in computer science. My research interests are centred around the fields of embodied AI, social presence, and the modulating presence of embodied systems. Through my work, I aim to explore and enhance the interactions between humans and robotic systems, particularly in healthcare settings.
This large sample study used exposure to a humanoid social robot to investigate the relationship between affinity with technology, social presence and future intention to use the robot.
In this paper, we present a novel framework for robotic attention modulation that enables dynamic regulation between attention-seeking and attention-avoidance behaviours through gaze feedback. For this feedback, we incorporate SGE with gaze fixation counts to create a metric that evaluates not just the quantity but also the quality of visual attention. Our approach implements two complementary modules, a Gaze Avoidance Module (GAM) and a Gaze Garnering Module (GGM), both powered by reinforcement learning (RL) algorithms that respond to real-time human gaze patterns. Thus the system continuously adapts to each individual’s current gaze feedback level, dynamically calibrating the robot’s attention-modulating behaviours to match personal attention thresholds. This personalisation ensures that the robot can effectively engage with users when needed, while remaining unobtrusive when appropriate, all based on real-time analysis of human gaze patterns.
This paper introduces the initial phase of a dynamic SP framework, emphasizing context identification. Psychological research links contextual awareness to improved interactions, fostering empathy and adaptability. Applying this to HRI may enhance comfort and support by mirroring social dynamics. Accurate context identification is crucial, as it directly enables effective SP modulation.
In this paper, we survey the field of affective robotics, focusing on bodily expressed emotion—both recognising affect through human body movements and postures, and generating robotic movement that is perceived as emotional by human observers. We frame this examination through the lens of the performing arts, drawing on an art-inspired case study alongside foundational background material to explore the expressive potential of robots. This close engagement with the performing arts reveals the intense malleability and diversity of bodily expression, challenging some prevailing goals in the field—such as designing generally "happy" robotic movement—and highlighting the importance of context and interactional intent. We conclude by proposing future directions for bodily expressed affective robotics that integrate advances from both robotics and the performing arts
This paper presents a new framework for understanding and designing social presence in human-robot interaction, based on empirical studies and theoretical analysis.
