Hiroyuki Hamada

Osaka University of Human Sciences, The University of Tokyo

Papers

Total Citations

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About

Hiroyuki Hamada is a pioneering researcher in robotics and autonomous systems, with a focus on environmental mapping and human-robot interaction. His early work on stationary environmental map generation under unknown robot motion (2002, 11 citations) addressed a critical challenge in robot navigation—overcoming the difficulty of observing exact motion parameters to create accurate maps of real scenes. This contribution laid groundwork for more robust autonomous navigation in dynamic environments. More recently, Hamada has advanced teleoperation efficiency through reinforcement learning, developing a novel viewpoint selection method (2023, 4 citations) that optimizes camera angles for faster, more precise robot arm control. By training reinforcement learning models on images from multiple candidate viewpoints, his work directly enhances operator performance in complex tasks. Hamada’s research bridges fundamental mapping algorithms with cutting-edge machine learning applications, demonstrating sustained impact in both theoretical and practical robotics. His contributions are particularly valuable for students and researchers exploring autonomous navigation, human-robot collaboration, and intelligent control systems.