Byounghyun Yoo

Korea Institute of Science and Technology

Papers

Total Citations

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About

Byounghyun Yoo is a leading researcher at the intersection of robotics, computer vision, and 3D scanning, with a primary focus on automating the digitalization of physical objects. His most impactful work, "Automatic Pose Generation for Robotic 3-D Scanning of Mechanical Parts" (2020, 41 citations), addresses a critical bottleneck in reverse engineering: the complex, manual process of aligning multiple 3D measurements. Yoo’s key contribution is a novel algorithm that autonomously computes optimal scanning poses for robotic arms, dramatically simplifying the acquisition of complete, high-fidelity 3D models of mechanical parts. This work has become a foundational reference for researchers seeking to automate industrial inspection and digital twin creation. Expanding on this, his more recent study, "Autonomous view planning methods for 3D scanning" (2024, 13 citations), provides a comprehensive survey of the field, synthesizing advancements in view planning for broader applications, including autonomous robot navigation. By systematically addressing the "next-best-view" problem, Yoo’s research directly enables more efficient and intelligent 3D data acquisition, with significant implications for manufacturing, heritage preservation, and autonomous systems.