Sanguk Noh
Papers
2
Total Citations
12
H-Index
2
About
Sanguk Noh is a researcher specializing in multi-agent systems, sensor data fusion, and intelligent coordination for defense and surveillance applications. His work focuses on developing decision-theoretic frameworks that enable teams of military surveillance robots to effectively monitor and allocate targets in complex, distributed environments. Noh’s key contributions include pioneering methods for fusing multi-sensor data—particularly from infrared sensors—and coordinating autonomous agents to optimize target tracking and allocation under uncertainty. His most-cited paper, "Intelligent Data Fusion and Multi-Agent Coordination for Target Allocation" (2020, 9 citations), proposes a novel approach that integrates sensor fusion with multi-agent decision-making, demonstrating significant impact in the field of robotic surveillance. Another notable work, "Intelligent fusion processing of data perceived through IR sensors of multiple robots" (2013, 3 citations), lays foundational techniques for combining distributed sensor data in constrained battlefield scenarios. While his citation counts reflect a focused and emerging research trajectory, Noh’s work is highly relevant to advancing autonomous systems in defense, offering practical solutions for real-time, multi-robot coordination. His research continues to influence the development of intelligent, data-driven strategies for military and security applications.
Research Focus
Key Achievements
Top Papers
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