Hiromitsu Fujii

The University of Tokyo, Chiba Institute of Technology

Papers

21

Total Citations

213

H-Index

9

About

Hiromitsu Fujii is a leading researcher in robotics and infrastructure inspection, whose work bridges computer vision, teleoperation, and automated diagnosis. His primary research areas include robotic inspection systems, 3D reconstruction, and localization for mobile robots. Fujii’s most significant contribution is the development of an automated hammering test methodology using ensemble learning, which enables robots to detect material defects—such as concrete delamination—in aging social infrastructure. This work, cited 31 times, addresses a critical need for non-destructive, automated maintenance. He has also advanced teleoperation by creating free viewpoint image generation systems that combine fisheye cameras and laser rangefinders, improving operator depth perception and reducing collisions. In localization, Fujii pioneered line-based global localization for spherical cameras in Manhattan Worlds (17 citations), enabling robust indoor navigation. His research on ICP-based SLAM using LiDAR intensity and near-infrared data further enhances environmental adaptability. With over 150 total citations across his top papers, Fujii’s work is widely recognized for its practical impact on infrastructure maintenance and robotic teleoperation, making him a key figure in the field.

Research Focus

Key Achievements

9
H-Index
21
Papers
213
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Defect detection with estimation of material condition using ensemble learning for hammering test
31 citations · 2016
📈 Most Prolific Year: 2016 (4 Papers)
🤝 Key Collaborators: 37
🏛 Institutions: The University of Tokyo, Chiba Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago