Tae-Gyu Yeo
Papers
1
Total Citations
5
H-Index
1
About
Tae-Gyu Yeo is a researcher specializing in autonomous mobile robotics, with a particular focus on navigation and localization in challenging agricultural environments. His work addresses critical challenges in precision agriculture, specifically the development of robust GPS filtering techniques for autonomous robots operating in orchard settings. Yeo’s most-cited paper, "GPS Error Filtering using Continuity of Path for Autonomous Mobile Robot in Orchard Environment" (2024), introduces a novel method that leverages path continuity to mitigate GPS inaccuracies—a persistent issue in environments with dense tree canopies and signal obstructions. This contribution is foundational for enabling reliable, real-time navigation in orchards, where precise positioning is essential for tasks like fruit harvesting, spraying, and monitoring. With 5 citations in its first year, this work has quickly gained attention from researchers in agricultural robotics and field automation. Yeo’s research bridges the gap between theoretical control systems and practical deployment, offering scalable solutions for smart farming. His focus on error filtering and path continuity not only advances autonomous navigation but also supports the broader adoption of robotics in sustainable agriculture, making him a key contributor to the field.
Research Focus
Key Achievements
Top Papers
- 1