Youngseok Jang

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About

Youngseok Jang is a robotics researcher specializing in multirobot simultaneous localization and mapping (SLAM) and vision-based navigation for autonomous systems. His most impactful work, "Multirobot Collaborative Monocular SLAM Utilizing Rendezvous" (2021, 43 citations), addresses a critical challenge in multirobot systems: the systematic construction of multiple SLAM pipelines and the fusion of local maps into a cohesive global representation. This contribution is essential for enabling teams of robots to collaboratively explore unknown environments without relying on external infrastructure. Jang also developed a "Pose Correction Algorithm for Relative Frames Between Keyframes in SLAM" (2021), improving the accuracy of trajectory estimates in single-robot systems. His survey on vision-based navigation systems robust to illumination changes (2022) provides a comprehensive overview of methods that maintain performance under challenging lighting conditions—a key hurdle for real-world deployment. Through his work, Jang advances the reliability and scalability of autonomous navigation, laying groundwork for applications in search-and-rescue, exploration, and industrial automation.