Young-Jae Min

Korea Advanced Institute of Science and Technology, Decision Systems (United States)

Papers

Total Citations

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About

Young-Jae Min is a robotics researcher whose work focuses on advancing 3-D dynamic occupancy mapping for autonomous aerial systems. His primary research areas include spatial perception, probabilistic robotics, and sensor fusion for dynamic environments. Min’s major contribution is the development of K3DOM (Kernel-Based 3-D Dynamic Occupancy Mapping), a novel algorithm that addresses the critical challenge of mapping three-dimensional spaces that change over time—a problem far more complex than traditional 2-D static mapping. By leveraging kernel-based inference, his method enables aerial robots to distinguish between static and dynamic objects in real-time, significantly improving navigation and manipulation capabilities in cluttered, evolving environments. His follow-up work, DS-K3DOM, further refines this approach by integrating Dempster-Shafer evidential theory to handle uncertainty more robustly. With his most-cited paper accumulating 15 citations and his research published in top venues, Min is establishing himself as a rising expert in autonomous robot perception. His innovations are particularly impactful for applications like drone delivery, search-and-rescue, and industrial inspection, where understanding dynamic 3-D space is essential for safe and efficient operation.