Map construction method and device, terminal and computer readable storage medium

Abstract

The embodiment of the invention discloses a map construction method and device, a terminal and a computer readable storage medium. The map construction method comprises: acquiring scene resources, thescene resources comprising image data and point cloud data of a target scene, the image data comprising two-dimensional image data of the target scene, and each point in the point cloud data comprising three-dimensional space coordinate data; determining first point cloud distribution of the first map element based on the image data; determining second point cloud distribution of the second map element based on the point cloud data; and constructing a three-dimensional map of the target scene according to the first point cloud distribution and the second point cloud distribution. By adoptingthe embodiment of the invention, map element editing work can be more efficient, accurate and convenient, so that the automation rate of map construction work is improved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a map construction method, device, terminal and computer-readable storage medium. Background technique [0002] With the rapid development of computer technology, the autonomous driving system, as its derivative product, has received more and more social attention. As the basic support module of the automatic driving system, the high-precision map has a crucial impact on the accuracy and richness of its data on the positioning, navigation and decision-making of the automatic driving system vehicle. [0003] With the development of mapping technology, most of the production of high-precision maps can be automatically completed by algorithms. The point cloud segmentation algorithm currently used uses points as units to divide the point cloud into several interesting data blocks for the identification of map elements. For positioning, it is difficult to obtain point cloud...

AI Technical Summary

Problems solved by technology

[0003] With the development of mapping technology, most of the production of high-precision maps can be automatically completed by algorithms. The point cloud segmentation algorithm currently used uses points as units to divide the point cloud into several interesting data blocks for the identification of map elements. Positioning, the acquisition of point cloud data is difficult, the amount of data is huge, and the load on the map construction platform is heavy

The image segmentation algorithm uses pixels as the unit to divide the image into several sub-images of interest for the identification and positioning of map elements. The accuracy of the result is low, it is easily affected by data collection and the actual road environment, and the production efficiency is low.

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