Age-Dependent Emotional Communication in Humanoid Robots

Emotional communication plays a central role in human–robot interaction (HRI), particularly in the case of humanoid robots whose embodied form enables rich nonverbal expression through posture, movement, and gesture. Over the past decade, research in affective robotics and social robotics has increasingly focused on enabling robots to generate recognizable emotional signals to support natural and intuitive interaction with humans. While significant progress has been made indesigning expressive behaviors and multimodal affective displays, comparatively less attention has been devoted to how such emotional cues are interpreted by different user populations. One important but still underexplored dimension concerns the role of age in shaping the perception and interpretation of emotional body language produced by robots. Developmental differences, cognitive processing changes across the lifespan, and varying levels of technological familiarity may influence how emotional signals are decoded. Understanding these factors is particularly relevant for applications involving children, adults, and older adults in contexts such as education, rehabilitation, assistive robotics, and social companionship.The goal of this Research Topic is to advance a deeper understanding of age-sensitive emotional communication in humanoid robots, bringing together interdisciplinary perspectives from robotics, affective computing, cognitive science, developmental psychology, neuroscience, and human–computer interaction. We invite contributions that investigate how people at different stages of life perceive, interpret, and respond to emotional expressions conveyed by humanoid robots, with a particular focus on body language, movement dynamics, and embodied interaction. Submissions may explore empirical studies, computational models, and design methodologies that help explain or improve emotional communication between humans and robots across different age groups. Relevant topics include, but are not limited to: age-related differences in emotional perception in HRI; interpretation of robot body language and expressive motion; multimodal emotional communication combining facial, vocal, and bodily cues; developmental and lifespan perspectiveson affective interaction with robots; cognitive and neural mechanisms involved in emotion recognition from robotic agents; and design frameworks for adaptive or age-aware expressive behaviors. By consolidating insights from multiple disciplines, this Research Topic aims to move beyond a one-size-fits-all approach to robot emotional expression and instead promote the development of socially aware robotic systems capable of adapting their expressive communication to diverse user populations.Key themes include age-related differences in decoding robot-generated emotional body language; the role of embodiment, kinematics, and morphology in emotional attribution; cross-modal integration of facial, vocal, and bodily emotional cues; developmental and lifespan perspectives in affective HRI; neural and cognitive mechanisms underlying emotion perception in robots; cultural and demographic moderators of emotional interpretation; design methodologies for adaptive, age-aware expressive behaviors; evaluation protocols and metrics for emotional clarity and user engagement; and applications in education, rehabilitation, eldercare, and therapy.We particularly encourage empirical studies, computational modeling approaches, and design-oriented contributions that inform the development of humanoid systems capable of tailoring their emotional expressivity to specific age groups. Conceptual and theoretical papers proposing integrative frameworks for age-aware affective robotics are also welcome. Topic editors: Giuseppe Palestra, Giovanna Varni, Berardina Nadja De Carolis Source: https://www.frontiersin.org/research-topics/79203/age-dependent-emotional-communication-in-humanoid-robots