Papers

4

Total Citations

28

H-Index

3

About

Kazuo Okuhata is a leading researcher in construction robotics, specializing in autonomous material handling and transportation for dynamic, labor-scarce job sites. His work focuses on developing intelligent guidance systems and robust mechanical designs that enable robots to navigate complex, unstructured construction environments. Okuhata’s most impactful contribution is his “hallway exploration-inspired guidance” algorithm, which allows robots to autonomously transport materials through cluttered sites—a method validated in field experiments and cited 20 times. He has also pioneered a novel gate-type robot capable of hauling carts loaded with building materials up to five times its own weight, addressing critical safety and efficiency challenges. His recent 2025 work on autonomous cart docking further advances precision maneuvering in dynamic settings. Through field-tested algorithms and innovative mechanical designs, Okuhata’s research directly tackles the labor shortage crisis in construction, offering scalable, practical solutions that bridge the gap between robotics theory and real-world deployment. His contributions are essential reading for engineers and researchers seeking to automate heavy material logistics in hazardous environments.

Research Focus

Key Achievements

3
H-Index
4
Papers
28
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Hallway exploration-inspired guidance: applications in autonomous material transportation in construction sites
20 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Systems, Applications & Products in Data Processing (United Kingdom)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago