Yotaro Fuse

Kansai University, Toyama Prefectural University

Papers

10

Total Citations

55

H-Index

4

About

Yotaro Fuse is a pioneering researcher in human-robot interaction, specializing in how robots can learn and obey social norms within human groups. His work focuses on developing robotic models that enable machines to adapt to group dynamics, personal space, and collective decision-making—a critical step toward seamless human-robot coexistence. Fuse’s most influential paper, “Social Influence of Group Norms Developed by Human-Robot Groups” (2020, 17 citations), demonstrates how robots can internalize group norms through interaction, while his 2018 model for norm obedience (8 citations) and 2020 study on indirect mutual interaction (8 citations) further establish his foundational contributions. His research also explores navigation models that adjust robot positioning based on changing personal space (6 citations) and fairness in group decision-making, as seen in his 2023 work on the Ultimatum Game. With over 55 total citations across his top papers, Fuse’s work is shaping the future of socially intelligent robots. Notably, his 2024 paper on online topological mapping for quadcopters extends his expertise into autonomous 3D navigation, showcasing his versatility. Fuse’s research is essential for anyone interested in building robots that truly belong in human communities.

Research Focus

Key Achievements

4
H-Index
10
Papers
55
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Social Influence of Group Norms Developed by Human-Robot Groups
17 citations · 2020
📈 Most Prolific Year: 2020 (4 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Kansai University, Toyama Prefectural University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago