Cross-country road surface extraction method based on a three-dimensional laser radar

A three-dimensional laser and lidar technology, applied in the field of image recognition, can solve the problems of a large number of manual labeling samples and high labor costs, and achieve the effect of reducing demand and strong adaptability

Active Publication Date: 2019-05-24
PEKING UNIV
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AI Technical Summary

Problems solved by technology

The disadvantage they all have in common is that training a deep neural network requires a large number of manually labeled samples
In the absence of public data sets for off-road road surface extraction, the human cost of labeling a large number of training samples is very high

Method used

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  • Cross-country road surface extraction method based on a three-dimensional laser radar
  • Cross-country road surface extraction method based on a three-dimensional laser radar
  • Cross-country road surface extraction method based on a three-dimensional laser radar

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Embodiment

[0041] Such as figure 1 As shown, the embodiment of the present invention provides a method for extracting off-road road surface based on three-dimensional laser radar, the method includes the following process steps:

[0042] Step S110: After superimposing the continuous multi-frame 3D laser point cloud data acquired by the lidar, project it into the top view to obtain the road surface elevation map;

[0043] Step S120: Using a deep convolutional neural network to perform feature extraction on the road elevation map to obtain a traffic cost map of the road elevation map;

[0044] Step S130: discretize the passage cost map, and obtain passable area labels, obstacle area labels, and fuzzy area labels;

[0045] Step S140: Perform image visualization on the discretized pass cost map according to the passable region label, obstacle region label and fuzzy region label, and obtain a passable off-road road area map.

[0046] Such as figure 2As shown, the embodiment of the present...

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Abstract

The invention provides a cross-country road surface extraction method based on a three-dimensional laser radar, and belongs to the technical field of image recognition. The method comprises the stepsof superposing continuous multi-frame three-dimensional laser point cloud data acquired by a laser radar, and projecting the superposed three-dimensional laser point cloud data to a top view to obtaina pavement elevation map; performing feature extraction on the pavement elevation map by using a deep convolutional neural network to obtain a traffic cost map of the pavement elevation map; discretizing the passing cost map to obtain a passable area label, an obstacle area label and a fuzzy area label; and according to the passable area label, the obstacle area label and the fuzzy area label, carrying out image visualization on the discretized passable cost map to obtain a passable cross-country road surface area map. The method is not influenced by illumination and weather, and a passable cross-country road surface can be extracted; the feature extraction method based on deep learning can adaptively learn environmental features, and is higher in adaptability in different scenes; According to the provided automatic data labeling scheme, the requirement for manually labeling samples is effectively reduced.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a three-dimensional laser radar-based off-road road surface extraction method capable of accurately identifying passable areas on the off-road road surface. Background technique [0002] In recent years, unmanned driving technology has developed rapidly, and road area extraction is one of the key technologies, which is the prerequisite for realizing safe and reliable autonomous driving of unmanned vehicles. At present, the relatively mature algorithms and application technologies are mainly aimed at the urban structured road environment, and there are few studies on off-road roads with complex structures and environments. In off-road scenarios, there are often a large number of ambiguous areas at the road boundary: for example, muddy soil or areas covered by vegetation, these areas are generally physically passable, but the cost of passage is very high, which is not str...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06N3/04G06N3/08
Inventor 高飙潘彦成徐安然赵卉菁
Owner PEKING UNIV
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