Masatoshi Nakamura
Papers
10
Total Citations
188
H-Index
6
About
Masatoshi Nakamura is a robotics and intelligent control researcher whose career spans foundational contributions to neural network-based control systems, mobile robotics, and assistive technologies. He is perhaps best known for pioneering the Fuzzy-Gaussian Neural Network (FGNN), introduced in the early 1990s and refined throughout the decade, which applies Gaussian activation functions to fuzzy neural architectures to enable adaptive learning without requiring expert-labeled training data. His 1996 paper on FGNN-based mobile robot control remains his most influential work, accumulating 114 citations and establishing a practical framework for intelligent tracking control in dynamic environments. Nakamura's research further extended into high-precision industrial robot manipulation, where he developed master-slave synchronous positioning and contour control methods for articulated robot arms — critical capabilities for applications like laser cutting and sealing. His work on Gaussian neural networks for contour control demonstrated measurable improvements in high-speed accuracy under real-world interference conditions. Beyond industrial robotics, Nakamura made meaningful contributions to assistive technology, developing EMG- and EOG-driven control systems for meal assistance robots and human-computer interfaces — work with direct implications for individuals with physical disabilities. Across more than two decades of research, his interdisciplinary blend of soft computing, control theory, and human-centered robotics reflects a sustained commitment to making robotic systems both smarter and more accessible.
Research Focus
Key Achievements
Top Papers
- 1A fuzzy-Gaussian neural network and its application to mobile robot control114 citations · 1996
- 2A new method for mobile robots to avoid collision with moving obstacle18 citations · 2012
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- 47 Master-Slave Synchronous Positioning Control9 citations · 2004
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- 8Reliable EOG signal-based control approach with EEG signal judgment3 citations · 2009
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