Yujiro Nakaso
Papers
4
Total Citations
15
H-Index
3
About
Yujiro Nakaso’s research centers on the intersection of advanced control theory and robotics, with a particular focus on stabilizing receding horizon control (RHC) for manipulator systems. His major contributions lie in experimentally validating RHC strategies—a computationally demanding model predictive control method—on physical hardware, specifically two-link direct drive robot arms. Crucially, Nakaso demonstrated that stability could be guaranteed by employing a terminal cost function instead of traditional terminal constraints, a pragmatic solution that reduces computational load while maintaining robust performance. His work extends this approach to visual feedback systems, integrating planar manipulators with real-time vision for enhanced precision. Although his most-cited papers, such as his 2005 study on direct drive manipulators, have garnered modest citation counts (up to 5), their impact is significant in the niche field of experimental nonlinear control. Nakaso’s research bridges the gap between theoretical control algorithms and practical robotic implementation, offering a validated framework for engineers designing stable, computationally efficient robotic systems. His experimental rigor and focus on real-world applicability make his contributions a valuable reference for students and researchers working on model predictive control in robotics.
Research Focus
Key Achievements
Top Papers
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