Unmanned vehicle real-time positioning method based on laser reflection strength

Abstract

The invention relates to an unmanned vehicle real-time positioning method based on laser reflection strength. The method comprises the following steps of S1, photographing two sides of a city road by an on-vehicle laser radar, obtaining a plurality of frames of point cloud data, extracting road edge points and converting the road edge points into a current vehicle coordinate system; S2, selecting the road edge points of which the z-axis coordinate value is in a preset range and obtaining coordinates of the road edge points in a GPS coordinate system, using the current GPS coordinate point of the unmanned vehicle as an original point, dividing a coordinate space for obtaining a grid map; S3, matching the gridded high-precision map with the grid map which is obtained in the step S2, thereby obtaining position of the unmanned vehicle on a high-precision map; and S4, predicating vehicle posture by means of a Kalman filter. Compared with prior art, the unmanned vehicle real-time positioning method can realize real-time accurate positioning in a complicated environment and can effectively improve driving safety of the unmanned aerial vehicle.

Description

technical field [0001] The invention relates to a real-time positioning method for an unmanned vehicle, in particular to a real-time positioning method for an unmanned vehicle based on laser reflection intensity. Background technique [0002] With the development of computer technology and artificial intelligence, unmanned vehicles (hereinafter referred to as unmanned vehicles) have shown great application prospects in military, transportation, industrial production, logistics and warehousing, and daily life. In terms of national defense and military affairs, unmanned vehicles are mostly used to perform military tasks in dangerous scenarios, such as military rescue and material delivery. In terms of traffic safety, unmanned driving technology is an effective means to promote the development of intelligent transportation systems. Unmanned driving technology based on artificial intelligence can improve the active safety of vehicles, and can effectively reduce traffic accidents...

AI Technical Summary

Problems solved by technology

[0008] Although the positioning algorithm based on the feature level has the advantages of simple structure and low computational complexity, there are some limitations when it is applied to the positioning of unmanned vehicles and the estimation of the state of nonlinear systems in complex environments.

When an unmanned vehicle is driving in a complex environment, it is difficult to associate the feature points detected by the on-board sensors with the map data. The reason is that there will be false detections and obstacles in the detection of feature points. match, which will cause the positioning algorithm to fail

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