Rei OGAMI
Papers
1
Total Citations
2
H-Index
1
About
Rei Ogami is a researcher in mobile robotics, with a focus on path planning and navigation for wheeled and tracked vehicles operating in complex, three-dimensional environments. Their key contribution lies in integrating vertical information—such as ground gradients and step heights—into path generation algorithms, addressing the critical limitation that wheeled robots cannot traverse obstacles like steps. In their most cited work, "1P1-L06 Path Planning by Using 3-dimensional Map Including Vertical Information," Ogami employed Q-learning to generate feasible, collision-free paths from start to goal positions, explicitly accounting for terrain slope and elevation changes. This approach enhances autonomous navigation in real-world settings where flat ground cannot be assumed. While their citation count is modest (2 citations), the work represents an early and practical step toward more adaptive robotic mobility. Ogami’s research is particularly relevant for students and engineers developing robots for uneven or urban environments, where understanding both horizontal and vertical constraints is essential for reliable movement.
Research Focus
Key Achievements
Top Papers
- 1