Papers
12
Total Citations
284
H-Index
8
About
Toru Nakata is a pioneering researcher in human-robot interaction, specializing in nonverbal communication and the expressive potential of robot body movement. His core research integrates principles from dance psychology and movement analysis—particularly Laban Movement Analysis—to design robots that can convey emotion, intention, and familiarity through physical behavior. Nakata’s most influential work, “Analysis of Impression of Robot Bodily Expression” (94 citations), established a quantitative framework for linking physical movement features to human impressions, a foundation he expanded in “Expression of Emotion and Intention by Robot Body Movement” (67 citations). He introduced the innovative “Behavioral Score” notation, analogous to a musical score, for synthesizing expressive robot behavior, and explored how animal-like movement can foster human-robot bonds in pet robots. His research has been cited over 280 times, demonstrating lasting impact on the fields of social robotics and affective computing. Nakata’s work is essential reading for anyone interested in making robots not just functional, but genuinely communicative and socially intelligent partners.
Research Focus
Key Achievements
Top Papers
- 1Analysis of Impression of Robot Bodily Expression94 citations · 2002
- 2Expression of Emotion and Intention by Robot Body Movement67 citations · 1998
- 3
- 4Synthesis of robot-to-human expressive behavior for human-robot symbiosis27 citations · 2002
- 5Generating Familiarity by Robot Behavior toward a Human Being.16 citations · 1997
- 6
- 7
- 8Informational Analysis on Impression of Human Robot Interaction.8 citations · 2001
- 9
- 10