Hyobin Suk

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About

Hyobin Suk is a researcher advancing autonomous navigation and mobile robotics, with a focus on real-world operational challenges. Their work addresses critical limitations in autonomous systems, particularly in environments where traditional sensors fail. Suk's most cited paper, "Orchard Navigation Algorithm for Self-Driving Vehicles Under Poor GPS Signal" (2025, 2 citations), pioneers a robust navigation framework for agricultural and unstructured settings, enabling self-driving vehicles to maintain precise path planning despite GPS degradation—a key contribution to field robotics. Another significant work, "Docking Control Algorithm for Autonomous Mobile Robot Through Sensor Fusion" (2023, 1 citation), develops a methodology integrating position estimation, path planning, and control for autonomous docking systems. By fusing sensor data, Suk’s approach accurately estimates the relative position between an autonomous mobile robot (AMR) and its docking station, solving a fundamental problem in industrial automation and logistics. These contributions demonstrate Suk’s impact in bridging sensor fusion and control theory for practical deployment, with applications spanning agriculture, manufacturing, and service robotics. Their research is particularly notable for addressing low-citation but high-applicability niches, laying groundwork for future advances in autonomous vehicle reliability and precision docking.