Ryota Matsuo
Papers
1
Total Citations
3
H-Index
1
About
Ryota Matsuo is a robotics researcher specializing in computer vision and sensor fusion for autonomous mobile systems. His primary research areas include obstacle detection, laser-based perception, and real-time environmental sensing for moving platforms. Matsuo’s most notable contribution is a novel method that integrates a fisheye camera with a circle line laser to detect obstacles surrounding a moving object. This system, designed to be mounted on mobile robots, enables real-time obstacle detection during motion, addressing a key limitation of conventional approaches that often struggle with dynamic environments or require complex calibration. His work has practical implications for improving navigation safety in autonomous vehicles and service robots. While his citation count is still growing—with his top-cited paper accumulating 3 citations since 2022—Matsuo’s research demonstrates a clear focus on low-cost, efficient sensing solutions. His approach stands out for its simplicity and effectiveness, offering a promising alternative to more computationally expensive methods. As an emerging researcher, Matsuo’s work is beginning to attract attention in the robotics community, particularly among those developing affordable obstacle avoidance systems for small-scale robots.
Research Focus
Key Achievements
Top Papers
- 1