Hyong-Yeol Yang
Papers
1
Total Citations
6
H-Index
1
About
Hyong-Yeol Yang is a robotics researcher whose work focuses on autonomous navigation and sensor systems, particularly in the domain of magnet-based position sensing for robotic vehicles. His most cited paper, "Neural Network Mapping of Magnet Based Position Sensing System for Autonomous Robotic Vehicle" (2007), with 6 citations, introduces a novel approach that integrates neural networks to enhance the accuracy and reliability of magnetic field-based localization. This contribution is pivotal for autonomous vehicles operating in environments where GPS is unavailable, such as indoor or underground settings, offering a cost-effective and robust alternative for real-time positioning. Yang's work demonstrates a practical application of machine learning to solve core challenges in mobile robotics, bridging the gap between theoretical sensor modeling and real-world deployment. While his citation count reflects a focused, niche impact, his research has influenced subsequent studies in sensor fusion and neural network-based mapping for autonomous systems. For students and researchers, Yang's work serves as a valuable case study in how interdisciplinary methods—combining robotics, electromagnetics, and AI—can drive innovation in vehicle autonomy.
Research Focus
Key Achievements
Top Papers
- 1