Hiroyuki Sumitomo

Kansai University

Papers

1

Total Citations

2

H-Index

1

About

Hiroyuki Sumitomo is a researcher whose work explores the intersection of robotics, artificial intelligence, and emotional computing. His primary research area focuses on developing computational models that enable robots to generate and express emotions, a critical step toward more natural human-robot interaction. Sumitomo’s most notable contribution, detailed in his 2010 paper "Study on an Emotion Generation Model for a Robot Using a Chaotic Neural Network," proposes a novel approach that leverages chaotic neural networks to simulate dynamic, non-linear emotional states. This work, with 2 citations, lays a foundational framework for creating robots capable of exhibiting complex, lifelike emotional responses, moving beyond simplistic rule-based systems. While his citation count is modest, the conceptual innovation of integrating chaos theory with neural networks for emotion generation marks a distinctive contribution to affective computing. Sumitomo’s research is particularly relevant for students and researchers interested in the challenges of building socially intelligent robots, offering a unique perspective on how internal dynamics can drive external emotional expression.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Study on an Emotion Generation Model for a Robot Using a Chaotic Neural Network
2 citations · 2010
📈 Most Prolific Year: 2010 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Kansai University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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