Sorting method of vehicle-mounted laser scanning point cloud data of urban ground objects

Abstract

The invention provides a sorting method of vehicle-mounted laser scanning point cloud data of urban ground objects. The method mainly comprises two steps as follows: original vehicle-mounted laser scanning point cloud data are subjected to road surface filtering in combination of vehicle tracking data, and point cloud data of a road surface are separated from point cloud data of other ground objects; and the obtained point cloud data of other ground objects are further identified to be different ground object types. In the road surface filtering algorithm, the vehicle tracking data are combined, and a histogram statistic and analytical method is introduced, so that the self-adaption degree, the automation degree and the accuracy of the filtering algorithm of the road surface in an urban environment are improved greatly; and in the sorting algorithm of other ground objects, a point cloud feature image sorting method based on the maximum elevation value is improved, mistakenly sorted point cloud data are corrected with a cellular automaton technology, and a new thought and method are provided for the sorting algorithms of vehicle-mounted laser scanning point cloud data.

Description

technical field [0001] The invention relates to the technical field of vehicle-mounted laser radar, in particular to a method for classifying point cloud data of vehicle-mounted laser scanning. Background technique [0002] In the 1970s, NASA developed the Lidar measurement technology (LIDAR, Light Detection And Ranging), which provided a new technical means for obtaining spatial information. By the 1980s, the University of Stuttgart in Germany combined lidar technology with a timely positioning and attitude determination system, using aircraft as a carrier, and successfully developed an airborne lidar measurement system (ALSS, Airborne Laser Mapping System). In the late 1980s, the vehicle-mounted mobile measurement system (MMS, Mobile Mapping System) with the vehicle as the platform was successfully developed. This technology provides a reliable, flexible and efficient way to quickly collect high-precision 3D data of roads and related features on both sides of the road. H...

AI Technical Summary

Problems solved by technology

However, these methods are less self-adaptive and usually need to manually set more thresholds, and cannot achieve efficient and accurate classification for vehicle-mounted laser scanning point cloud data in complex urban environments.

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