Yotaro Fuse
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
Top Papers
- 1Social Influence of Group Norms Developed by Human-Robot Groups17 citations · 2020
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- 5Decision-Making Model for Robots that Consider Group Norms and Interests4 citations · 2022
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- 9Online Topological Mapping on a Quadcopter with Fast Growing Neural Gas2 citations · 2024
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