Papers
1
Total Citations
7
H-Index
1
About
Lin Lyu is a researcher specializing in visual simultaneous localization and mapping (SLAM), with a particular focus on robust performance in dynamic environments. Their most notable contribution is the development of DOC-SLAM (Dynamic Object Culling SLAM), a stereo SLAM system that significantly improves camera trajectory estimation accuracy by intelligently detecting and culling moving objects in highly dynamic scenes. By integrating semantic information from deep learning, DOC-SLAM addresses a critical challenge in autonomous navigation and augmented reality, where traditional SLAM systems often fail due to moving pedestrians or vehicles. This work has garnered 7 citations since its 2021 publication, reflecting its relevance to the growing field of robust perception in real-world settings. Lyu’s research bridges computer vision and robotics, offering practical solutions for systems that must operate reliably in unpredictable environments. Their work stands as a valuable reference for students and engineers seeking to understand how semantic cues can enhance SLAM resilience against dynamic disturbances.
Research Focus
Key Achievements
Top Papers
- 1DOC-SLAM: Robust Stereo SLAM with Dynamic Object Culling7 citations · 2021