Yu Kataoka
Papers
3
Total Citations
8
H-Index
2
About
Yu Kataoka is a pioneering researcher in autonomous robotics, with a focus on bio-inspired control systems and motion generation algorithms. His early work laid the foundation for integrating human skill-based decision-making into robotic platforms, particularly through the use of artificial neural networks and fuzzy reasoning. In his most-cited paper, "Autonomous mobile robot based on behavior decision skill and control skill of the operator" (2000, 4 citations), Kataoka introduced a novel control algorithm that enables mobile robots to adapt their motion patterns to real-world environments by learning from human operators via backpropagation. He further advanced the field of legged locomotion with two companion papers on hopping robots (2000, 2 citations each), where he applied genetic algorithms to optimize the parameters of central pattern generators, allowing robots to achieve stable, continuous jumping to a reference height. Though his citation counts are modest, Kataoka’s contributions are notable for their early integration of evolutionary computation and neural learning in robotics, presaging later developments in adaptive and autonomous systems. His work remains a valuable reference for researchers exploring skill-based control and evolutionary motion planning.
Research Focus
Key Achievements
Top Papers
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