Taeghyun Kang

University of Central Missouri, Texas Tech University

Papers

Total Citations

H-Index

About

Taeghyun Kang is a researcher whose work focuses on the reliability, adaptability, and self-management of autonomous robotic systems. His key contributions lie in developing architectures and methodologies that enable unmanned systems to detect, diagnose, and recover from component failures without human intervention. Kang’s most cited paper, “Blackboard Architecture for Detecting and Notifying Failures for Component-Based Unmanned Systems” (2017), introduces a centralized framework for real-time failure monitoring, a critical step toward robust autonomy. Earlier foundational work, including “Reconfiguration of Robot Applications using Data Dependency and Impact Analysis” (2012) and “Self-Management of Component Executors for Robot Applications” (2010), explores how robots can dynamically reconfigure their software components based on dependency analysis and self-managing execution environments. Though his citation counts are modest—with his top paper garnering 4 citations—Kang’s research addresses a fundamental challenge in robotics: ensuring system resilience in unpredictable environments. His work is particularly relevant for students and engineers interested in fault-tolerant design, component-based software engineering, and autonomous systems. By focusing on practical, architecture-level solutions, Kang contributes to the broader goal of creating truly self-sufficient robots capable of operating safely in the field.