Minoru Sekiguchi
Papers
1
Total Citations
2
H-Index
1
About
Minoru Sekiguchi is a pioneering researcher in the field of intelligent robotics, with a foundational focus on neurocomputing and autonomous behavior control. His most-cited work, "Behavior control for a mobile robot by dual-hierarchical neural network" (1990), introduced a novel architecture that leveraged the highly parallel data processing and learning capabilities of neural networks to enable adaptive robot navigation. This early contribution helped lay the groundwork for integrating hierarchical learning systems into mobile robotics, demonstrating how neural networks could manage complex behavioral sequences without explicit programming. Although his citation count is modest, Sekiguchi’s work is notable for its forward-thinking approach at a time when neurocomputing was still emerging. His research bridges the gap between theoretical neural network models and practical robot control, offering a blueprint for later advances in autonomous systems. For students and researchers, Sekiguchi’s legacy underscores the importance of interdisciplinary thinking—combining computational neuroscience with mechanical engineering—to solve real-world robotics challenges. His dual-hierarchical model remains a reference point for those exploring adaptive, learning-based control in uncertain environments.
Research Focus
Key Achievements
Top Papers
- 1Behavior control for a mobile robot by dual-hierarchical neural network.2 citations · 1990