Papers

2

Total Citations

6

H-Index

2

About

Shinya Nakamura is a pioneering researcher in human-robot interaction, with a particular focus on how robots and humans can build shared understanding in real-world environments. His most influential work introduces a mutually-adaptive framework for utterance generation, where robots estimate and align their beliefs with human partners to enable more natural, efficient communication. By modeling shared beliefs as weighted combinations of probabilistic concepts—spanning speech, gestures, and objects—Nakamura’s approach allows robots to infer a partner’s mental state and resolve ambiguous expressions. This work, though early in its citation impact with 4 citations, laid foundational ideas for adaptive dialogue systems in robotics. Nakamura has also contributed to force feedback in hydraulically-driven construction robots, demonstrating external load estimation from cylinder pressures to provide operators with haptic feedback. While his citation counts remain modest, his research addresses critical challenges in situated communication and physical human-robot collaboration, offering valuable insights for researchers working on interactive AI, shared cognition, and embodied robotics in unstructured environments.

Research Focus

Key Achievements

2
H-Index
2
Papers
6
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Mutully-Adaptive Generation of Utterances Based on Estimation of Belief Shared by Human And Robots in Real World
4 citations · 2009
📈 Most Prolific Year: 2009 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Electro-Communications, The University of Osaka

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago