Recognition of Key Targets of Locomotive Bottom Based on 3D Point Cloud Data

摘要

In this paper, a new method is designed to recognize the key targets of the locomotive bottom based on the 3D point cloud data. In this method, the key points were selected on the basis of ISS (Intrinsic Shape Signatures) algorithm, the feature descriptors were constructed using FPFH (Fast Point Feature Histograms) algorithm, and the recognition and localization of the targets were conducted by the combination of template matching and cluster analysis. The experiment was carried out on bolts for validation. Experimental results verified the effectiveness of the proposed method and proved the feasibility of recognition and localization of key targets of the locomotive bottom based on 3D point cloud data.