Ryusuke Miyamoto
Papers
20
Total Citations
230
H-Index
8
About
Ryusuke Miyamoto is a robotics and computer vision researcher whose work centers on autonomous mobile robot navigation, semantic segmentation, and visual perception systems. His most significant contributions challenge the prevailing reliance on expensive 3D LiDAR and RADAR sensors by demonstrating that monocular cameras, combined with semantic segmentation, can effectively enable robust autonomous navigation in human-centric environments. His 2019 paper on vision-based road-following using semantic segmentation has garnered 47 citations, while his follow-up work on purely monocular visual navigation has attracted 38 citations, reflecting strong community interest in his cost-effective, camera-first approach to robot mobility. Miyamoto's research spans both outdoor and indoor navigation challenges, including intersection detection, pedestrian-resilient localization, and domain-specific dataset creation to improve segmentation accuracy. His attention to practical deployment is evident in studies addressing real-world complications such as shadows on traversable areas and environmental variability across weather and time of day. His involvement in the Tsukuba Challenge, a prestigious real-world robot navigation competition, underscores his commitment to translating laboratory results into authentic urban environments. Earlier work optimizing OpenCV for the Cell Broadband Engine further demonstrates his breadth across computer vision and high-performance computing, making him a versatile and impactful contributor to intelligent robotics research.
Research Focus
Key Achievements
Top Papers
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- 5Highly optimized implementation of OpenCV for the Cell Broadband Engine15 citations · 2010
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