Large-scale Point Cloud Registration Method for Railway UAV Inspection
Under the background of China's vast railway network and huge transportation demand,the use of UAV in combination with high-precision laser radar for railway inspection not only improves efficiency compared with traditional manual methods,but also enables the development of a perfect 3D railway environment map through accurate point cloud data registration and analysis to provide reliable data support for line maintenance,troubleshooting and safety hazard positioning.In response to the challenge of large-scale unstructured data in railway and surrounding environment,a point cloud registration algorithm with strong rotation invariance and excellent generalization ability was proposed.By training the model on the 3DMatch public dataset and testing on the ETH dataset and the dataset of Beijing-Shanghai HSR,this algorithm has demonstrated its ability to efficiently and accurately register unknown datasets,significantly improving the application value of UAV in railway inspection and providing strong technical support for safe operation and efficient management of railway system.
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