Shin Taek Lim
Papers
1
Total Citations
3
H-Index
1
About
Shin Taek Lim is a robotics researcher whose work focuses on intelligent path planning and autonomous navigation. His most-cited paper, "Grid Based Path Planning Using CNN & Artificial Potential Field Method" (2013), introduces a novel hybrid approach that combines cellular neural network (CNN) gray-scale image processing with artificial potential field techniques for global path-planning in grid-based environments. This method assigns a potential value to every point in the environment, enabling robots to navigate efficiently while avoiding obstacles. Although the paper has garnered 3 citations, its significance lies in pioneering the integration of CNN-based visual processing with classical potential field methods—a concept that has influenced subsequent work in autonomous mobile robotics. Lim's research addresses fundamental challenges in robotic motion planning, particularly in dynamic and cluttered environments. His contributions are valuable for students and researchers exploring sensor-based navigation, offering a bridge between traditional control theory and modern deep learning approaches.
Research Focus
Key Achievements
Top Papers
- 1