Papers
35
Total Citations
308
H-Index
10
About
Takenori Obo is a researcher whose work sits at the intersection of intelligent robotics, human-computer interaction, and assistive technology, with a particular focus on supporting elderly populations in aging societies. His most significant contributions center on the development of informationally structured spaces — sensor-networked environments enabling precise human localization and behavior measurement — a theme that anchors several of his most-cited works, including his 2010 papers that together have accumulated nearly 80 citations. Obo has pioneered the application of fuzzy spiking neural networks and hybrid evolutionary neuro-fuzzy approaches to complex challenges such as human gesture recognition and robot navigation, demonstrating a consistent commitment to biologically inspired, adaptive computational methods. His research extends into rehabilitation robotics, cognitive care, and exercise support systems for elderly users, reflecting a deeply humanistic motivation. Notable contributions include imitation learning frameworks for exercise guidance and an analysis of LED-based visual cues to improve turn-taking in human-robot conversation. With over 200 cumulative citations, Obo's body of work has meaningfully advanced the field of socially intelligent, human-aware robotics, offering practical pathways toward compassionate, technology-assisted elder care.
Research Focus
Key Achievements
Top Papers
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- 4Imitation learning for daily exercise support with robot partner19 citations · 2015
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- 6Intelligent Fuzzy Controller for Human-Aware Robot Navigation15 citations · 2018
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- 10Human Behavior Measurement Based on Sensor Network and Robot Partners10 citations · 2010