Jun Hatori

Preferred Networks (Japan)

Papers

2

Total Citations

188

H-Index

2

About

Jun Hatori is a leading researcher in human-robot interaction, with a primary focus on enabling robots to understand and execute unconstrained spoken language instructions in real-world environments. His most influential work, "Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions" (2018), has garnered 175 citations, establishing a foundational framework for bridging the gap between natural human communication and robotic action. Hatori’s major contribution lies in addressing the dual challenges of linguistic complexity—such as varied sentence structures and expressions—and the inherent ambiguity of spoken commands. By developing systems that allow robots to interpret and act on natural language in real-time, he has advanced the practical deployment of interactive robots for tasks like object picking. His research demonstrates how robots can engage in dynamic, back-and-forth clarification with users, improving accuracy and usability. Hatori’s work is pivotal for students and researchers interested in robotics, natural language processing, and artificial intelligence, offering a clear path toward more intuitive human-machine collaboration.

Research Focus

Key Achievements

2
H-Index
2
Papers
188
Total Citations
94
Avg Citations/Paper
🏆 Most Cited Paper
Interactively Picking Real-World Objects with Unconstrained Spoken Language Instructions
175 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Preferred Networks (Japan)

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago