Yeol-Min Yun
Papers
1
Total Citations
3
H-Index
1
About
Dr. Yeol-Min Yun is a robotics researcher whose work centers on autonomous navigation and sensor-based mapping for mobile robots. His primary contributions lie in developing efficient algorithms for 2D grid map construction, particularly through the integration of the Iterative Closest Point (ICP) algorithm with line extraction techniques. In his most cited work, "2D grid map building using ICP algorithm and line extraction" (2014), Yun proposed a method to enhance mapping accuracy by calibrating line errors from sensor data—specifically using only encoder values and onboard sensors without reliance on external positioning systems. This approach addresses a fundamental challenge in robotics: building reliable environmental maps in real-time with limited computational resources. While his citation count is modest, his research contributes to the foundational toolkit for simultaneous localization and mapping (SLAM), a critical area for autonomous systems. Yun’s work demonstrates a practical, sensor-driven methodology that continues to inform low-cost, lightweight mapping solutions for mobile robots operating in unstructured environments.
Research Focus
Key Achievements
Top Papers
- 12D grid map building using ICP algorithm and line extraction3 citations · 2014