Papers
1
Total Citations
18
H-Index
1
About
Xufu Mu is a leading researcher in robotics and autonomous systems, with a primary focus on state estimation, sensor fusion, and visual-inertial simultaneous localization and mapping (SLAM). His most influential work, "Accurate Initial State Estimation in a Monocular Visual–Inertial SLAM System" (2018), has garnered 18 citations and addresses a critical challenge in optimization-based SLAM: robustly initializing the system without prior knowledge. By developing a method that accurately estimates initial velocity, gravity, and gyroscope bias from monocular camera and inertial measurement unit data, Mu’s contribution enables more reliable and drift-free performance for drones, augmented reality devices, and autonomous vehicles. His research bridges the gap between theoretical optimization and practical deployment, demonstrating that careful initialization can significantly enhance the accuracy and stability of visual-inertial systems. Mu’s work is widely recognized for its impact on real-time robotics, and he continues to advance the field through innovative approaches to sensor fusion and state estimation, making him a key figure in the development of robust, autonomous navigation technologies.
Research Focus
Key Achievements
Top Papers
- 1Accurate Initial State Estimation in a Monocular Visual–Inertial SLAM System18 citations · 2018