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About

Suk-Kyo Hong is a pioneering researcher in autonomous mobile robotics, whose work has fundamentally advanced how robots navigate and interact with complex environments. His primary research areas encompass mobile robot path planning, multi-robot coordination, and intelligent obstacle avoidance systems. Hong's most influential contribution is his neural network-based path planning approach for mobile robots (40 citations), which elegantly integrates obstacle avoidance with target tracking using wall-following algorithms and pattern recognition. He further revolutionized the field with his skeleton map-based roadmap construction algorithm (30 citations), addressing critical limitations of conventional path planning methods by eliminating unnecessary turns and sharp trajectories. His notable achievements include developing a patrol robot that fuses differential GPS with curb detection for robust outdoor navigation, and creating decentralized collision avoidance algorithms using potential fields for multiple mobile robots. Hong has also made significant contributions to robot soccer systems, where he unified obstacle avoidance and shooting strategies using fuzzy-net and limit-cycle approaches. His work on cooperative control of nonholonomic mobile robots carrying objects demonstrates his expertise in multi-agent systems, while his wavefront-based local path planning with vision systems showcases his integration of perception and navigation. With over 100 citations across his most influential papers, Hong's research continues to inform modern autonomous navigation systems.