Minako Nakamura
Papers
3
Total Citations
37
H-Index
2
About
Minako Nakamura is a leading researcher in human-robot interaction, specializing in learning-from-observation systems and conversational robotics. Her work bridges the gap between human movement and robotic understanding, with a particular focus on enabling robots to naturally interpret and replicate human gestures. Nakamura’s foundational research on describing upper-body motions using Labanotation—a notation system traditionally used for dance—has provided a groundbreaking framework for robots to learn complex tasks by observing human demonstrations. This work, which has garnered 33 citations, established a paradigm that moves beyond simple mimicry toward genuine task comprehension. More recently, Nakamura has advanced the field of conversational robotics by developing architectures that enable humanoid robots to generate contextually appropriate, concept-based gestures synchronized with speech. Her research on personalized gesture vocabularies and gesture-generating systems addresses the growing demand for socially adept communication robots, particularly in elder care and daily life support. Through these contributions, Nakamura is helping shape a future where robots can coexist with humans as natural, expressive conversational partners.
Research Focus
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Top Papers
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