Shuo Huai
Papers
1
Total Citations
6
H-Index
1
About
Shuo Huai is a researcher advancing the frontiers of robotic perception and autonomous navigation, with a primary focus on visual SLAM (Simultaneous Localization and Mapping) in challenging, real-world environments. Their key research areas include robust SLAM under motion blur, dynamic scene handling, and multi-sensor fusion for mobile robotics. Huai’s most notable contribution is the development of a multi-strategy visual SLAM system specifically designed to address motion blur in indoor dynamic settings—a critical problem for household robots that must operate reliably amidst moving people and objects. By moving beyond the traditional assumption of environment rigidity, this work integrates semantic information and adaptive strategies to maintain accurate localization and mapping even under rapid camera motion. The paper, published in 2025, has already garnered 6 citations, reflecting its timely relevance to the robotics community. Huai’s research bridges the gap between theoretical SLAM frameworks and practical deployment, offering tangible solutions for robots navigating cluttered, unpredictable homes. Their work stands as a valuable resource for students and engineers seeking to build more resilient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1