Papers
1
Total Citations
3
H-Index
1
About
Fang Sun is a researcher in autonomous robotics and computer vision, with a primary focus on Simultaneous Localization and Mapping (SLAM) systems. His work addresses critical challenges in monocular SLAM initialization, a notoriously difficult problem where single-camera systems must estimate depth and motion without prior 3D information. Sun’s most cited paper, "Planar Homography based Monocular SLAM Initialization Method" (2019), proposes a novel approach that leverages planar homography constraints to achieve robust and efficient initialization—a key bottleneck in deploying cost-effective monocular systems over more expensive RGB-D or stereo setups. While his citation count is currently modest, this work contributes to a long-standing research area that spans decades in both robotics and computer vision communities. Sun’s research is particularly relevant for applications in autonomous navigation, where reliable initialization directly impacts system performance. His focus on algorithmic efficiency and practical deployment positions him as a contributor to making monocular SLAM more accessible for real-world robotics applications.
Research Focus
Key Achievements
Top Papers
- 1Planar Homography based Monocular SLAM Initialization Method3 citations · 2019