Osamu Yamano

Nokia (United States), Tokyo Institute of Technology

Papers

Total Citations

217

H-Index

About

Osamu Yamano is a pioneering figure in the field of robotics and control systems, best known for his foundational work in learning control and discrete system optimization. His research focuses on developing adaptive control algorithms that enable industrial robots to improve their performance through iterative operation—a concept he termed "discrete learning systems." In his seminal 1985 paper, "Analysis and design of an optimal learning control scheme for industrial robots," which has garnered 155 citations, Yamano introduced a novel discrete learning algorithm that allows electro-mechanical systems to autonomously refine their trajectories over repeated tasks. He further advanced this framework in his 1986 work on learning control and optimality, where he established stability conditions for discrete linear time-varying systems and applied optimization schemes to robotic control. His earlier 1984 study on robust control addressed the challenge of nonlinearity in robot manipulators by employing nonlinear feedback linearization. Yamano’s contributions have had a lasting impact on industrial automation, providing the theoretical backbone for modern adaptive robotics and iterative learning control. His work remains essential reading for researchers in robotics, control theory, and mechatronics.