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About

Megumi Masuda is a pioneering researcher in human-robot interaction, specializing in emotional expression through robotic body movement. Her key research areas include affective robotics, motion rendering, and the application of Laban Movement Analysis (LMA) to humanoid robots. Masuda’s major contribution is the development of a motion rendering system that enables human-form robots to convey specific emotions—pleasure, anger, sadness, and relaxation—by modifying arbitrary basic movements. Her most cited work, "Motion rendering system for emotion expression of human form robots based on Laban movement analysis" (2010, 62 citations), demonstrates how LMA principles can be algorithmically applied to generate emotionally expressive robot gestures. This foundational paper, along with her subsequent studies (36 and 19 citations), has significantly advanced the field by providing a systematic, theory-driven approach to non-verbal emotional communication in robotics. Masuda’s research not only enhances user engagement but also deepens our understanding of how movement features shape human perception of robot emotions. Her Laban-based feature value set, introduced in 2011, offers a novel framework for quantifying bodily expression, making her work essential reading for students and researchers in social robotics and affective computing.