Yuyao Shen
Papers
1
Total Citations
2
H-Index
1
About
Yuyao Shen’s research focuses on advancing monocular visual odometry and state estimation for autonomous systems, particularly addressing the critical challenge of scale ambiguity in single-camera setups. In their most-cited work, “Fully Scaled Monocular Direct Sparse Odometry with A Distance Constraint,” Shen introduced a novel approach that leverages distance measurements—obtainable from GPS, wheel encoders, or other odometry sources—to restore scale in direct sparse odometry without relying on inertial sensors or multiple cameras. This contribution offers a practical, cost-effective solution for real-world robotics and autonomous vehicle applications, where accurate scale estimation is essential for reliable navigation. Though still early in their career, with 2 citations on this key paper, Shen’s work demonstrates a clear ability to identify and address fundamental limitations in existing methods. Their research sits at the intersection of computer vision, robotics, and sensor fusion, and holds promise for enabling more robust, lightweight visual odometry systems in GPS-denied or resource-constrained environments.
Research Focus
Key Achievements
Top Papers
- 1Fully Scaled Monocular Direct Sparse Odometry with A Distance Constraint2 citations · 2019