Tomoharu Nakahara

Papers

Total Citations

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About

Tomoharu Nakahara is a pioneering roboticist whose work bridges computer vision and autonomous navigation, with a focus on practical, real-world applications. His key research areas include 3D object recognition, bin-picking systems, and mobile robot navigation. Nakahara’s most cited paper, "A Practical Bin-Picking System Using 3D Object Recognition" (2001, 6 citations), introduced a stereo-vision-based method that extracts salient features from multiple viewpoints to recognize and grasp objects in cluttered bins—a foundational contribution to industrial automation. His second major work, "Navigation of Autonomous Mobile Cleaning Robot SuiPPi" (2007, 3 citations), details the development and long-term deployment of a cleaning robot at Expo 2005. SuiPPi navigated the 2.6 km Global Loop, a challenging environment with curves, slopes, and obstacles, demonstrating robust autonomy in a large-scale public setting. Though his citation counts are modest, Nakahara’s impact lies in the practicality and durability of his systems—his bin-picking work influenced later industrial robotics, while SuiPPi’s successful field trial remains a notable achievement in service robotics. His research exemplifies how vision-guided manipulation and navigation can be translated into reliable, everyday solutions.