Yukio Kosugi
Papers
1
Total Citations
5
H-Index
1
About
Yukio Kosugi is a pioneering researcher in neural network-based robotic control, with a particular focus on adaptive systems that bridge computational intelligence and physical manipulation. His most-cited work, "Bidirectional feature map for robotic arm control" (1994, 5 citations), introduced a novel neural architecture that simultaneously addresses two critical challenges in robotic control: implementing precise input-output mappings and ensuring robust generalization capabilities. This contribution stands out for its elegant solution to the long-standing problem of neural networks struggling to maintain both accuracy and adaptability in real-world robotic applications. Kosugi's approach, which diverged from conventional methods like Back Propagation, demonstrated how bidirectional feature mapping could enable more intuitive and efficient arm control. While his citation count may appear modest, his work represents foundational thinking in the intersection of neural networks and robotics during a formative era. Researchers and students interested in the evolution of intelligent control systems will find Kosugi's contributions valuable for understanding the early conceptual frameworks that preceded modern deep learning approaches to robotics.
Research Focus
Key Achievements
Top Papers
- 1Bidirectional feature map for robotic arm control5 citations · 1994