Jiyoung Min
Papers
1
Total Citations
3
H-Index
1
About
Jiyoung Min is a forward-thinking researcher in intelligent robotics and autonomous systems, with a specialized focus on enhancing search and rescue operations through sensor fusion and risk-aware navigation. Her work bridges computer vision and 3D LiDAR perception to address critical safety challenges in disaster response. In her most cited paper, "Intelligent Risk-Identification Algorithm with Vision and 3D LiDAR Patterns at Damaged Buildings" (2023), Min tackles a pressing limitation in firefighting robotics: the inability of existing robots to autonomously detect and assess structural hazards. By integrating visual and LiDAR data, she proposes a cost-effective algorithm that enables robots to identify dangerous patterns in damaged buildings, thereby improving the efficiency and safety of search and rescue missions. This work, with 3 citations, lays foundational groundwork for deploying intelligent, risk-aware robots in real-world emergencies. Min’s contributions are particularly notable for their practical orientation—aiming to reduce reliance on expensive, specialized equipment while maximizing operational effectiveness. Her research holds significant promise for advancing autonomous disaster response, making her a rising voice in the field of robotic perception and human-robot interaction in hazardous environments.
Research Focus
Key Achievements
Top Papers
- 1