Shohei Nogami
Papers
1
Total Citations
7
H-Index
1
About
Shohei Nogami is a robotics researcher whose work focuses on autonomous navigation and obstacle detection for indoor transportation vehicles. His key contributions lie in developing stereo camera-based systems that enable vehicles to perceive and avoid both static and moving obstacles in real time. In his most-cited work, "A Stereo Camera Based Static and Moving Obstacles Detection on Autonomous Visual Navigation of Indoor Transportation Vehicle" (2018), Nogami proposed a method that uses 3D point cloud data to separate floor and non-floor regions, then applies density-based spatial clustering to identify obstacles. This approach allows autonomous vehicles to navigate safely in cluttered indoor environments, a critical capability for logistics and service robotics. While his citation count (7) reflects a focused, early-career impact, his work addresses a fundamental challenge in visual navigation—reliable obstacle detection without expensive sensors. Nogami's research is particularly relevant for students and engineers working on cost-effective autonomous systems, demonstrating how stereo vision can replace more costly LiDAR-based solutions. His contributions help bridge the gap between computer vision and practical robotics, making indoor autonomous transportation more accessible and robust.
Research Focus
Key Achievements
Top Papers
- 1