Donghyeon Lee

Pohang University of Science and Technology

Papers

Total Citations

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About

Donghyeon Lee is a robotics researcher whose work centers on human-robot collaboration and the intuitive teaching of dynamic manipulation tasks. His primary research areas include robot trajectory generation, task teaching interfaces, and the safe execution of complex, dynamic motions such as pan-flipping. Lee’s major contribution lies in developing a novel teaching method that enables collaborative robots to learn and replicate dexterous, high-speed tasks—traditionally challenging for standard programming interfaces. By focusing on generating safe geometric paths for dynamic actions, his approach bridges the gap between human demonstration and robotic execution, enhancing the practicality of robots in domestic and culinary settings. While his most-cited paper, “A Task Teaching Method for Pan-flipping to Collaborative Robot” (2022), has garnered 2 citations, it represents a foundational step in making robots more adaptable to real-world, non-repetitive tasks. Lee’s work is notable for its emphasis on safety and usability, addressing key barriers to deploying robots alongside humans. As an emerging voice in collaborative robotics, his research promises to expand the scope of tasks robots can learn directly from human teachers.