Junghwan Lee

Korea Advanced Institute of Science and Technology

Papers

Total Citations

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About

Junghwan Lee is a roboticist whose research focuses on motion planning for complex robotic systems, particularly in constrained and high-dimensional environments. His major contributions center on developing efficient sampling-based algorithms that overcome the notorious challenges of narrow passages and redundancy. In his highly cited 2014 work, "A Selective Retraction-Based RRT Planner for Various Environments" (33 citations), Lee introduced a bridge line test to identify narrow passage regions, then selectively applied optimization-based retraction only in those areas, dramatically improving planning efficiency across diverse environments. He further advanced the field with "PROT: Productive regions oriented task space path planning for hyper-redundant manipulators" (11 citations), where he defined "productive regions" in task space—states that most effectively lead to a goal—and used them as a sampling bias to accelerate trajectory planning for hyper-redundant arms. This work is particularly notable for addressing the curse of dimensionality in high-DOF systems. Lee’s research is characterized by its practical, problem-driven approach: rather than applying generic planners, he identifies the geometric or topological bottlenecks of a problem and designs targeted strategies to resolve them. His contributions have direct implications for industrial robotics, autonomous navigation, and manipulation in cluttered spaces.