Hironaga Miyamoto

Papers

Total Citations

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About

Hironaga Miyamoto is a leading researcher in autonomous mobile robotics, with a primary focus on enabling robots to navigate complex, unstructured outdoor environments. His work centers on two critical challenges: robust localization over rough terrain and real-time detection of traversable surfaces in forestry and agricultural settings. Miyamoto's major contributions include developing a 3D scan matching technique for mobile robot localization that maintains accuracy even when odometry errors spike during travel over uneven ground—a fundamental advancement for field robotics. His most cited paper, "Forest road surface detection using LiDAR-SLAM and U-Net" (2021, 5 citations), introduces a novel approach that combines LiDAR-based SLAM with deep learning to detect passable road surfaces that adapt to changing geometry, lighting, and surface conditions. This work directly addresses the practical need for autonomous navigation of forestry vehicles carrying large logs. His earlier paper, "3D Scan matching for mobile robot localization over rough terrain" (2019, 5 citations), established a high-speed, precise localization method using iterative closest point algorithms. Together, these contributions demonstrate Miyamoto's impact in advancing autonomous navigation from controlled indoor settings to the demanding, variable conditions of real-world outdoor environments.