Ryusuke Umeyama
Papers
2
Total Citations
23
H-Index
2
About
Ryusuke Umeyama is a leading researcher in autonomous mobile robotics, specializing in large-scale urban navigation and 3D mapping. His work addresses the critical challenge of enabling robots to navigate complex, pedestrian-filled city environments with precision and safety. Umeyama’s most cited paper, “City-Scale Grid-Topological Hybrid Maps for Autonomous Mobile Robot Navigation in Urban Area” (2020, 18 citations), introduces a novel map configuration that combines grid and topological structures to represent urban layouts, paired with an autonomous navigation scheme that leverages this hybrid approach. This work lays a foundation for scalable city-wide robot navigation. In his subsequent research, “Semi-Automatic Town-Scale 3D Mapping Using Building Information From Publicly Available Maps” (2022, 5 citations), Umeyama advances the field by developing a framework that generates globally consistent 3D maps from SLAM pose graphs, integrating publicly available building data to enhance accuracy and reduce manual effort. His contributions are pivotal for real-world deployment of autonomous robots in dense urban settings, bridging the gap between theoretical SLAM methods and practical, large-scale applications.
Research Focus
Key Achievements
Top Papers
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- 2