Ryutaro Kaneko

Gifu University

Papers

1

Total Citations

5

H-Index

1

About

Ryutaro Kaneko is a researcher at the forefront of autonomous mobile robotics, with a specialized focus on LiDAR-based localization and point cloud data mapping for industrial environments. His work addresses a critical challenge in factory automation: enabling robots to navigate reliably using pre-existing design drawings. In his most-cited paper, "Point cloud data map creation from factory design drawing for LiDAR localization of an autonomous mobile robot" (2022), Kaneko developed a novel method to convert 2D factory layout drawings into 3D point cloud maps, significantly reducing the time and cost of map creation for robot deployment. This contribution has garnered 5 citations, reflecting its practical relevance to the robotics and manufacturing communities. By bridging the gap between static design data and dynamic robot perception, Kaneko’s research enhances the scalability of autonomous systems in industrial settings. His work is particularly valuable for students and engineers seeking efficient solutions for robot localization in structured environments, demonstrating how synthetic data can be leveraged to overcome real-world mapping challenges.

Research Focus

Key Achievements

1
H-Index
1
Papers
5
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Point cloud data map creation from factory design drawing for LiDAR localization of an autonomous mobile robot
5 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Gifu University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago