About

Suguru Arimoto is a pioneering figure in robotics and control theory, best known for founding the field of **iterative learning control (ILC)**. His landmark 1984 paper, "Bettering Operation of Robots by Learning," introduced the transformative idea that robots could improve their performance across repeated tasks by leveraging data from previous iterations — a concept that has since become foundational in robotics research, accumulating over 3,400 citations. Arimoto's work bridges mathematics, neuroscience, and engineering: his learning control framework drew inspiration from how the human central nervous system generates and refines motor programs, offering a biologically motivated alternative to classical control methods. Beyond learning control, Arimoto made substantial contributions to nonlinear mechanical systems theory, redundant manipulator kinematics, multi-fingered robotic hand manipulation, and cooperative manipulator control. His 1996 book on nonlinear mechanical systems control provided a rigorous new analytical framework for intelligent machines. He also addressed fundamental challenges such as Bernstein's degrees-of-freedom problem and path planning for mobile robots. With research spanning over three decades and thousands of cumulative citations, Arimoto's work profoundly shaped modern robotics, leaving an enduring legacy in both theoretical foundations and practical robotic applications.

Research Focus

Key Achievements

28
H-Index
119
Papers
6,598
Total Citations
55
Avg Citations/Paper
🏆 Most Cited Paper
Bettering operation of Robots by learning
3,445 citations · 1984
📈 Most Prolific Year: 2007 (10 Papers)
🤝 Key Collaborators: 50
🏛 Institutions: The University of Osaka, The University of Tokyo, Ritsumeikan University, Tokyo University of Information Sciences, Catalytic Materials (United States), Kyushu University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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