Papers
1
Total Citations
11
H-Index
1
About
Xinyi Yu is an emerging researcher specializing in computer vision, robotics, and simultaneous localization and mapping (SLAM) systems, with a particular focus on advancing these technologies for real-world dynamic environments. Yu's most notable contribution, **CPR-SLAM**, introduced a pioneering RGB-D SLAM framework capable of operating reliably in dynamic settings — a significant departure from traditional VSLAM systems that depend on static environmental assumptions. By leveraging sub-point cloud correlations, this work addresses one of the most persistent and practical challenges in autonomous navigation and robotic perception: handling moving objects that can corrupt map construction and localization accuracy. Published in 2024, CPR-SLAM has already garnered 11 citations, a promising indicator of its early impact within the rapidly evolving SLAM research community. Yu's work sits at the intersection of 3D scene understanding, depth sensing, and robust localization, contributing meaningful solutions for applications in autonomous vehicles, service robotics, and augmented reality. As interest in deployable, real-world-ready SLAM systems continues to grow, Yu's research positions them as a valuable contributor to the next generation of intelligent, environment-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1