Yang Naiming
Papers
1
Total Citations
11
H-Index
1
About
Yang Naiming is a researcher whose work lies at the intersection of robotics, 3D perception, and long-term autonomous navigation. His key research areas include change detection from 3D point cloud maps, viewpoint-invariant localization, and robust mapping for mobile robots. In his most-cited work, "Scalable Change Detection from 3D Point Cloud Maps: Invariant Map Coordinate for Joint Viewpoint-Change Localization" (2018, 11 citations), Yang tackles the critical challenge of detecting environmental changes under global viewpoint uncertainty—a problem essential for reliable long-term robot autonomy. By introducing an invariant map coordinate system, his approach enables joint viewpoint-change localization, allowing robots to distinguish between actual scene changes and mere shifts in observation perspective. This contribution is particularly valuable for applications in autonomous driving, persistent surveillance, and infrastructure monitoring, where maps must remain accurate over time. Yang’s work demonstrates a thoughtful integration of geometric reasoning and scalable algorithms, offering practical solutions for real-world robotic systems. His research continues to influence the development of more resilient and adaptive mapping technologies.
Research Focus
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Top Papers
- 1