Yusuke Deguchi
Papers
2
Total Citations
10
H-Index
2
About
Yusuke Deguchi is a researcher advancing precision motor control through innovative encoder technology. His primary research areas include magnetic absolute encoders, high-resolution angular sensing, and neural network-based feedback systems for robotics and automation. Deguchi’s major contribution lies in developing ultra-high-resolution magnetic absolute encoders using an eccentric structure—a design that overcomes traditional size and accuracy limitations in servomotors. His 2018 paper, “Evaluation of Magnetic Absolute Encoder Using an Eccentric Structure with Feedback Correction” (6 citations), established a foundation for compact, high-accuracy encoders critical for downsizing in robotics, automotive, and medical applications. Building on this, his 2020 work, “Verification of Ultra-High Resolution Magnetic Absolute Encoder Using Eccentric Structure and Neural Network” (4 citations), introduced neural network-based corrections to achieve even finer angular resolution, directly addressing the demands of flexible robots that must precisely interact with people and objects. Though early in his career, Deguchi’s work is notable for merging mechanical design with intelligent algorithms, offering a pathway to more responsive and accurate motor control systems. His research holds promise for next-generation automation and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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