Papers

4

Total Citations

28

H-Index

3

About

Shingo Ino is a robotics researcher focused on transforming construction sites through autonomous material handling. His primary research areas include autonomous navigation, robotic material transportation, and human-robot collaboration in complex, dynamic environments. Ino’s most significant contribution is the development of a “hallway exploration-inspired guidance” algorithm, which enables robots to navigate unstructured construction sites without pre-mapped routes—a breakthrough that has already garnered 20 citations. His work on autonomous cart docking addresses the challenge of precise robot positioning in cluttered, ever-changing environments, while his design of a gate-type robot capable of hauling loads up to five times its own weight demonstrates a practical solution to labor shortages in the industry. Ino’s research, validated through field experiments on active construction sites, bridges the gap between laboratory robotics and real-world deployment. His 2021 paper on automatic control of material handling robots further establishes his expertise in creating efficient, safe, and scalable automation systems. With a growing citation record and a focus on solving pressing industry challenges, Ino is emerging as a key innovator in construction robotics.

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