Daishi Kaneta
Papers
4
Total Citations
17
H-Index
3
About
Daishi Kaneta is a researcher whose work sits at the intersection of biomechanics and robotics, focusing on the fundamental question of how humans maintain upright balance. His primary research area is the identification and modeling of human motor control, specifically the "standing controller" that stabilizes posture against perturbations. Kaneta’s major contribution lies in his rigorous application and reassessment of the COM-ZMP (center of mass and zero-moment point) model—a framework originally developed for humanoid robot control—to decode the macroscopic dynamics of human stance. He has pioneered techniques like the returning recursive-least-square method to identify piecewise-linear feedback controllers from motion measurement data. While his citation counts (ranging from 2 to 6) reflect a specialized, emerging field, his work is foundational for bridging human physiology and bipedal robot design. Notably, his 2022 paper in *IEEE Access* represents a mature synthesis of his decade-long effort to map the phase-space of human balance, offering a validated process for identifying the stabilizer that keeps us upright. For students and researchers, Kaneta’s research provides a compelling case study in how biological inspiration can refine robotic control theory.
Research Focus
Key Achievements
Top Papers
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