Taejun Kim
Papers
1
Total Citations
7
H-Index
1
About
Taejun Kim is a robotics researcher whose work focuses on advancing 3D mapping and navigation for mobile robots. His key contributions center on improving sensor data processing, particularly in handling noise from laser range finders (LRFs) to create more accurate environmental models. His most cited paper, "Impulse Noise Removal of LRF for 3D Map Building Using a Hybrid Median Filter" (2012, 7 citations), addresses a critical challenge in robotics: the limitations of 2D laser scanners, which rely on straight beams and can only detect obstacles within a narrow plane. Kim proposed a hybrid median filter to effectively remove impulse noise from LRF data, enabling the construction of robust 3D maps using a single sensor—a cost-effective solution for mobile robot navigation. While his citation count reflects a focused, early-career impact, this work demonstrates his ability to tackle practical sensor limitations that hinder real-world robotic autonomy. Kim’s research bridges the gap between theoretical filtering techniques and applied robotics, offering a foundation for more reliable spatial perception in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1