Beomseong Kim
Papers
2
Total Citations
9
H-Index
2
About
Beomseong Kim is a robotics researcher whose work focuses on intelligent navigation and localization for autonomous mobile robots operating in complex, crowded indoor environments. His key research areas include collision avoidance, sensor fusion, and robust localization techniques. Kim’s most significant contribution is the modified dynamic window approach (DWA), a novel collision avoidance algorithm that enhances the standard DWA by optimizing the objective function to better account for heading direction, obstacle distance, and robot velocity. This work, published in 2012, has garnered 6 citations and is foundational for intelligent transport robots navigating dynamic spaces. Additionally, Kim has advanced indoor localization by integrating laser scanners with vision markers, addressing the critical limitation of laser scanners returning unreliable data in cluttered environments. This complementary approach, cited 3 times, improves robot positioning accuracy when operating in crowded settings. Through these contributions, Kim has addressed fundamental challenges in service robotics, enabling safer and more reliable autonomous navigation in real-world indoor applications where traditional methods fall short.
Research Focus
Key Achievements
Top Papers
- 1
- 2Indoor localization using laser scanner and vision marker for intelligent robot3 citations · 2012