Road extraction and indexing method based on multi-sensor fusion of global and local raster images

A multi-sensor fusion and road extraction technology, applied in still image data indexing, still image data retrieval, instruments, etc., can solve the problems of single semantic information, low efficiency and high degree of specialization, and achieve efficient data processing, compressed data, Efficient store and recall effects

CN111273305BActive Publication Date: 2022-03-25HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2022-03-25

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Abstract

The invention discloses a multi-sensor fusion road extraction and indexing method based on global and local grid maps, which uses global and local grid maps for data storage and preprocessing, and obtains the real-time position and attitude of unmanned vehicles through a differential positioning system , Obtain high-precision road boundaries, lane lines, and road sign position information through the lidar point cloud related data stored in the raster image, and project them into the monocular vision image, judge the lane line type and recognize the road sign based on the deep learning method Semantic information, so as to obtain high-precision road maps with semantic information. At the same time, multiple global sections and road sets are established to achieve efficient storage and indexing.
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Description

technical field

[0001] The invention belongs to the technical field of automatic driving, and relates to an efficient and high-precision semantic road map construction method and a visualization method thereof. Background technique

[0002] High-precision maps are of great significance in the field of autonomous driving. High-resolution maps, also known as high-resolution maps, are maps specially designed for unmanned driving. Compared with traditional maps, high-precision maps can not only provide road-level navigation information, but also provide lane-level positioning and navigation information.

[0003] In the current high-precision map mapping scheme, a large number of steps such as laser point cloud conversion, splicing, labeling and indexing are required, and the process is very complicated and depends on professional technicians. This makes high-precision maps expensive, highly specialized, and inefficient to produce. In addition, in the production process of the...

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Embodiment Construction

[0058] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] see figure 1 , the present invention proposes a method for road extraction and indexing based on global and local grid map multi-sensor fusion, including the following steps:

[0060] Step 1. Establish a global and local grid map, and establish the association between the local grid map and the global grid map according to the vehicle positioning information;

[0061] Step 2. Extract the laser point cloud raster with the av...