Sang Hyeok An

Papers

Total Citations

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About

Sang Hyeok An is a robotics researcher whose work focuses on intelligent navigation and path planning for autonomous mobile robots, particularly in unknown and obstacle-dense environments. His primary contributions lie in integrating reinforcement learning with motion control strategies to improve robot efficiency and adaptability. An’s most cited paper, “Dyna-Q-based vector direction for path planning problem of autonomous mobile robots in unknown environments” (2013, 14 citations), addresses the critical challenge of slow learning in RL-based navigation. By combining Dyna-Q, a model-based reinforcement learning algorithm, with vector direction control, he demonstrated a method that significantly accelerates learning and enhances path planning in complex, unknown spaces. This work has been influential in advancing autonomous robot navigation, offering a practical solution for real-world applications like search-and-rescue or industrial automation. Additionally, his research on multi-robot systems, such as the “Univector Field Method Based Multi-robot Navigation for Pursuit Problem” (2012, 6 citations), explores cooperative behaviors for tasks like pursuit-evasion scenarios. An’s contributions are notable for bridging theoretical RL techniques with tangible robotic systems, providing a foundation for more responsive and autonomous mobile robots. His work continues to inspire researchers seeking efficient, real-time navigation solutions.