Nobuaki Fujiki
Papers
5
Total Citations
24
H-Index
4
About
Nobuaki Fujiki’s research bridges precision robotics and advanced control theory, with a primary focus on enhancing the machining performance of robot-type machine tools. His most influential work, a 2021 study on calibrating kinematics parameters for hybrid parallel-serial robot tools, has garnered 10 citations and demonstrates how error modeling can dramatically improve machining accuracy—a critical contribution for automated manufacturing. Fujiki further advanced this field by developing forward kinematics models that evaluate how simultaneous multi-axis control affects tool posture and motion range, enabling robot machine tools to outperform conventional systems in flexibility and reach. Beyond manufacturing, Fujiki has explored nonlinear control challenges, including the swinging-up and inverted stabilization of a pendulum with an inertia rotor—a problem that mimics gymnastic bar exercises and tests torque-limited actuation. He also proposed a novel state and disturbance estimation framework based on internal model control (IMC) structure, applied to sensorless grasping, and investigated decoupling properties in H∞ control for mechanical systems. Though his citation counts are modest, Fujiki’s work is notable for its breadth: from practical calibration techniques that directly improve industrial robot accuracy to theoretical control designs that handle complex, underactuated dynamics. His research offers valuable insights for engineers seeking to merge kinematic modeling with robust control in next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
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