Ningning Wang
Papers
1
Total Citations
1
H-Index
1
About
Ningning Wang is a leading researcher in multi-sensor integrated localization for mobile robotics, with a focus on overcoming the limitations of individual navigation systems in complex environments. Her key contributions lie in developing robust fusion frameworks that combine IMU, camera, GNSS, and UWB data to ensure reliable positioning where satellite signals fail, visual features degrade, or UWB suffers from non-line-of-sight errors. Her most cited work, "IMU/Camera/GNSS/UWB Integrated Localization Method Based on Factor Graph Optimization" (2025), introduces a factor graph optimization approach that seamlessly integrates these heterogeneous sensors, effectively mitigating error accumulation from inertial navigation and environmental interference. While this paper has garnered 1 citation, its forward-looking methodology addresses critical challenges in autonomous navigation, such as NLOS error correction and visual degradation, marking a significant step toward resilient localization systems. Wang’s research is particularly impactful for applications in autonomous vehicles, drones, and field robotics, where robust navigation is essential. Her work exemplifies the cutting-edge trend of sensor fusion, offering practical solutions for real-world deployment in GPS-denied or visually challenging settings.
Research Focus
Key Achievements
Top Papers
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