Fengrong Huang
Papers
1
Total Citations
5
H-Index
1
About
Fengrong Huang is a researcher in computer vision and robotics, with a primary focus on visual simultaneous localization and mapping (SLAM) systems. Her work addresses the critical challenge of robust perception in real-world environments, particularly through the detection and mitigation of image blur—a common issue in dynamic or low-light settings. In her 2021 paper, "Visual Simultaneous Localization and Mapping (SLAM) Based on Blurred Image Detection," she proposed a novel framework that integrates blur detection into the SLAM pipeline, enabling more accurate and reliable mapping and localization even under adverse visual conditions. This contribution has garnered attention in the field, with the paper accumulating 5 citations as a key reference for researchers tackling sensor degradation in autonomous systems. Huang’s work is particularly relevant for applications in mobile robotics, augmented reality, and autonomous navigation, where consistent performance in non-ideal conditions is essential. By advancing the robustness of visual SLAM, she has laid groundwork for more resilient perception systems, making her research a valuable resource for students and engineers developing next-generation autonomous technologies.
Research Focus
Key Achievements
Top Papers
- 1