Yutaka Hayano
Papers
1
Total Citations
87
H-Index
1
About
Yutaka Hayano is a leading figure in precision robotics, whose work bridges the gap between theoretical kinematics and real-world manufacturing accuracy. His research focuses on robot calibration, error compensation, and intelligent optimization of industrial manipulators. Hayano’s most influential contribution, a 2010 study with 87 citations, revolutionized how robots achieve sub-millimeter accuracy. By integrating a laser tracking system for high-precision measurement, he developed a two-stage calibration method: first correcting geometric errors in the kinematic model, then using neural networks to compensate for non-geometric errors like joint compliance and thermal drift. To maximize efficiency, he employed genetic algorithms to select optimal measurement poses, reducing calibration time without sacrificing accuracy. This work is foundational for industries requiring extreme precision, such as aerospace and medical robotics. Hayano’s approach—combining advanced sensing, machine learning, and evolutionary optimization—has become a benchmark in the field, influencing subsequent research on adaptive calibration and real-time error correction. His contributions continue to shape how robots are deployed in high-stakes automation environments.
Research Focus
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Top Papers
- 1