Tae Uk Kang

Papers

Total Citations

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About

Tae Uk Kang is a robotics researcher whose work centers on bio-inspired robotic systems, computer vision, and autonomous control. His most cited paper, "Lead-lag Swimming Control of Robot Fish Using Color Detection Algorithm" (2020, 4 citations), introduces a novel approach to coordinating multiple robot fish in confined aquatic environments. By leveraging color-based image processing, Kang’s method enables robot fish to maintain safe, lead-lag formations, preventing collisions that could damage the devices. This contribution addresses a critical challenge in swarm robotics: ensuring smooth, collision-free movement in dynamic settings. Beyond this work, Kang’s research integrates real-time visual feedback with control algorithms, advancing the practicality of autonomous underwater vehicles. His achievements demonstrate a keen ability to bridge computer vision and mechanical design, offering scalable solutions for multi-robot coordination. While his citation count is modest, the foundational nature of his work—particularly in collision avoidance and formation control—holds promise for future applications in environmental monitoring, aquatic robotics, and educational platforms. Kang’s focus on robust, low-cost sensing techniques makes his research particularly accessible for students and researchers exploring robot swarm dynamics and bio-inspired engineering.