Toyokazu Mituoka
Papers
3
Total Citations
9
H-Index
2
About
Toyokazu Mituoka is a robotics researcher whose work centers on the intersection of neural network-based learning and advanced control strategies for robotic manipulators. Emerging in the early 1990s, his research addressed one of the fundamental challenges in robotics: enabling manipulators to interact intelligently and adaptively with their physical environments through precise force and position regulation. His most notable contribution, "Force Control of a Robotic Manipulator by Application of a Neural Network" (1990), introduced a hybrid control architecture combining a standard PID controller with a multilayered neural network model, accounting for object dynamics to achieve more robust and responsive force control. Building on this foundation, Mituoka extended his framework to position and force hybrid control of two-degree-of-freedom manipulators, incorporating considerations of manipulator orientation and object dynamics — work published across two related 1991 studies. While his citation counts remain modest — his leading paper accumulating 5 citations — Mituoka's research represents meaningful early-stage exploration of neural adaptive control in robotics, contributing to a foundational body of work that anticipated the now-widespread application of machine learning techniques in robotic systems and intelligent automation.
Research Focus
Key Achievements
Top Papers
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