Makimi Fujita
Papers
1
Total Citations
2
H-Index
1
About
Makimi Fujita is a researcher whose work lies at the intersection of nonlinear control theory and robotic vision, with a particular focus on dynamic visual feedback systems. Her most-cited paper, "Stability and tracking performance of dynamic visual feedback control for nonlinear mechanical systems" (2002, 2 citations), addresses a fundamental challenge in robotics: enabling precise motion control using visual information. In this work, Fujita developed a comprehensive framework that models relative rigid body motion and integrates a nonlinear observer to construct a robust visual feedback system. She then proposed a design algorithm for 3D visual feedback control, tackling the complexities of stability and tracking performance in nonlinear mechanical systems. While her citation count is modest, her contributions are notable for their theoretical rigor and practical relevance to fields like autonomous robotics and manufacturing. Fujita’s research provides foundational insights for engineers seeking to enhance robot perception and control, making her a valuable reference for students and researchers exploring the synergy between vision and dynamics in mechanical systems.
Research Focus
Key Achievements
Top Papers
- 1