Min-Chul Lee
Papers
1
Total Citations
6
H-Index
1
About
Min-Chul Lee is a researcher whose work lies at the critical intersection of perception, mapping, and motion planning for autonomous vehicles. His most cited paper, "Hybrid Local Route Generation Combining Perception and a Precise Map for Autonomous Cars" (2019), addresses a fundamental challenge in self-driving technology: how to safely and efficiently navigate complex environments by fusing real-time sensor data with high-definition maps. This hybrid approach, which has garnered 6 citations, is essential for enabling robust behavior and motion planning—a core requirement for reliable autonomous driving. Lee’s contributions are particularly notable for bridging the gap between theoretical planning algorithms and practical, real-world implementation. By integrating perception outputs directly into route generation, his work helps autonomous cars make safer, more context-aware decisions. While his citation count reflects a focused, early-career impact, the problem he tackles—local route generation under uncertainty—is a cornerstone of the autonomous driving field, making his research highly relevant for students and engineers working on the next generation of self-driving systems.
Research Focus
Key Achievements
Top Papers
- 1