Yinmei Wang
Papers
1
Total Citations
3
H-Index
1
About
Yinmei Wang is a leading researcher in robotics and autonomous navigation, with a primary focus on multi-sensor fusion and real-time mapping for legged platforms. Her most-cited work, "Application of 3D point cloud and visual-inertial data fusion in Robot dog autonomous navigation" (2025, 3 citations), addresses a critical challenge in robotics: maintaining localization accuracy and mapping reliability in complex, unstructured environments. By integrating 3D LiDAR point clouds with visual-inertial data, Wang proposes a novel multi-sensor fusion method that significantly enhances the autonomous navigation capabilities of robot dogs—a platform increasingly vital for search-and-rescue, inspection, and exploration tasks. Her contributions are notable for bridging the gap between theoretical sensor fusion algorithms and practical deployment on dynamic, terrain-adaptive robots. While still early in her citation impact, Wang's work is already recognized for its potential to improve robustness in GPS-denied or visually degraded settings. Her research is particularly valuable for students and engineers working on field robotics, offering a clear pathway from sensor integration to real-time, reliable autonomy.
Research Focus
Key Achievements
Top Papers
- 1