Kyeong-Jin Joo
Papers
6
Total Citations
90
H-Index
3
About
Kyeong-Jin Joo is a leading researcher at the intersection of robotics, artificial intelligence, and semantic knowledge representation. His work focuses on enabling autonomous robots to understand and navigate complex environments—from hospitals and logistics centers to domestic spaces—by integrating ontology-based reasoning with deep learning and real-time edge computing. Joo’s most cited paper, “Ontology-Based Knowledge Representation in Robotic Systems: A Survey Oriented toward Applications” (2021, 54 citations), provides a foundational framework for how robots can process semantic knowledge to perform supportive tasks more efficiently. He has also made significant contributions to public health robotics, developing autonomous navigation and active SLAM systems for disinfecting robots, as well as a wall-following algorithm that ensures safe movement in cluttered spaces. His 2022 work on the Edge Deployment Framework of GuardBot (24 citations) tackles the critical challenge of deploying deep learning models for real-time face mask recognition on edge devices, balancing accuracy with computational efficiency. More recently, Joo has advanced multi-robot navigation frameworks that leverage semantic knowledge for logistics environments, pushing the boundaries of collaborative, context-aware robotic systems. His research is widely cited for its practical impact on safe, intelligent, and socially aware robotics.
Research Focus
Key Achievements
Top Papers
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- 3Autonomous Navigation with Active SLAM for Disinfecting Robot4 citations · 2022
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- 5Wall following navigation algorithm for a disinfecting robot3 citations · 2022
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