Yoichiro Nakamura
Papers
3
Total Citations
15
H-Index
2
About
Yoichiro Nakamura is a robotics researcher whose work centers on the development of flexible, human-like robotic systems, with a particular focus on pneumatic artificial muscle actuators and behavior-based learning. His most cited paper, "Spring-damper model and articulation control of pneumatic artificial muscle actuators" (2011, 10 citations), addresses a critical challenge in robotics: creating robots that combine human-like flexibility with high-level safety. By modeling and controlling pneumatic actuators, Nakamura laid groundwork for safer, more adaptable robotic hands and arms. In earlier work, "Behavior Acquisition of Autonomous Mobile Robots Using Instance-Based Classifier Generator" (1999, 3 citations), he introduced a novel reinforcement learning method called IBCG, enabling robots to acquire reactive behaviors by memorizing and classifying experienced states. This approach contributed to the field of autonomous robot learning. His research on master-slave robot hands driven by pneumatic actuators (2008, 2 citations) further demonstrates his commitment to dexterous, human-safe manipulation. Though his citation counts are modest, Nakamura’s work represents foundational steps toward integrating soft actuation and adaptive learning in robotics—key themes for future human-robot interaction.
Research Focus
Key Achievements
Top Papers
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