Jiyeong Chae

Daegu Gyeongbuk Institute of Science and Technology

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About

Jiyeong Chae is a robotics researcher whose work sits at the intersection of autonomous navigation, sensor perception, and intelligent system architecture. His primary research focuses on enabling mobile robots to operate reliably in complex, obstacle-rich environments, with a particular emphasis on addressing the challenge of glass detection—a notoriously difficult problem for standard LiDAR sensors. In his highly cited work, "PINMAP: A Cost-Efficient Algorithm for Glass Detection and Mapping Using Low-Cost 2-D LiDAR" (2025), Chae introduced a novel, computationally efficient method that allows autonomous mobile robots (AMRs) to detect and map transparent surfaces without expensive hardware, directly improving the safety and robustness of SLAM-based navigation. Building on this, his paper "Integrating ROS 2 and Physical AI: Architecture and Challenges" (2025) explores the architectural demands of next-generation robotics, analyzing how the Robot Operating System 2 can serve as a backbone for Physical AI systems that learn and adapt in real time. Though early in his career, Chae’s contributions are already shaping practical solutions for cost-effective, real-world deployment of intelligent robots.