Liumingyuan Zhang
Papers
1
Total Citations
9
H-Index
1
About
Liumingyuan Zhang is a researcher advancing the frontier of intelligent mobile robotics, with a primary focus on simultaneous localization and mapping (SLAM) in complex, dynamic environments. Zhang’s most notable contribution is the development of SCE-SLAM, a real-time semantic RGBD SLAM system that overcomes the longstanding limitation of traditional SLAM systems—their assumption of a static environment. By leveraging spatial coordinate error (SCE) to robustly detect and exclude dynamic objects, Zhang’s work enables robots to maintain accurate localization and mapping even in scenes with moving people or vehicles. This innovation, published in 2023, has already garnered 9 citations, signaling its growing influence in the robotics and computer vision communities. Zhang’s research directly addresses a critical gap in autonomous navigation, offering a practical solution for real-world deployment. Beyond this flagship work, Zhang’s broader research interests include semantic understanding and sensor fusion, aiming to make robots more perceptive and reliable. For students and researchers exploring SLAM in non-static settings, Zhang’s work provides a foundational reference for building robust, real-time systems.
Research Focus
Key Achievements
Top Papers
- 1