Three-dimensional laser radar-based structured road passable region extraction method

Abstract

The invention discloses a three-dimensional laser radar-based structured road passable region extraction method. The method includes the following steps that: 1) a three-dimensional laser radar scansa surrounding environment so as to acquire the point cloud information of the surrounding environment, and the point cloud information is transformed from the coordinate system of the laser radar to alocal rectangular coordinate system; 2) the interest data points of the three-dimensional laser radar are extracted; 3) a radar detection angle clustering method is used to extract laser radar scanning single lines; 4) a K-means clustering algorithm is used to obtain an optimal clustering point set; 5) obstacles are extracted by using altitude features; 6) road edges are extracted on the basis ofa DBSCAN method; and 7) polynomial curve fitting is performed on a passable road surface according to the least squares method. With the method of the invention adopted, the passable road surface canbe effectively extracted. The method has the advantages of high precision, high reliability and small judgment error rate in an identification process, and can be widely used in three-dimensional laser radar-based structured road passable region extraction practical situations.

Description

technical field [0001] The invention relates to unmanned driving technology, in particular to a method for extracting feasible regions of structured roads based on three-dimensional laser radar. Background technique [0002] Unmanned vehicles are intelligent vehicles that use on-board sensing systems to perceive the surrounding environment of the vehicle, plan their own driving route and control the vehicle to reach the destination successfully. Unmanned vehicles are generally equipped with lidar and cameras as on-board sensors to detect road areas and obstacle areas. Since the visual sensor is greatly affected by environmental factors, the detection range of the single-line lidar is very limited. Therefore, 3D lidar has been widely used in intelligent driving. [0003] The current 3D lidar processing algorithms are mainly divided into two categories: grid map-based segmentation algorithm and graph-based ground detection. [0004] 1. Perform threshold segmentation and dis...

AI Technical Summary

Problems solved by technology

Compared with raster-based algorithms, graph-based segmentation algorithms have higher precision, but are susceptible to noise interference, and the algorithm has poor robustness

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