Remote obstacle detection method based on laser radar multi-frame point cloud fusion

An obstacle detection and lidar technology is applied in the field of long-distance obstacle detection based on lidar multi-frame point cloud fusion, which can solve the problems of sparse point clouds and inability to effectively detect long-distance obstacles.

Active Publication Date: 2019-09-10
ZHEJIANG UNIV
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Problems solved by technology

[0005] The method of the present invention can solve the problem of being unable to effectively

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  • Remote obstacle detection method based on laser radar multi-frame point cloud fusion
  • Remote obstacle detection method based on laser radar multi-frame point cloud fusion
  • Remote obstacle detection method based on laser radar multi-frame point cloud fusion

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Embodiment Construction

[0148] The present invention will be further described below in conjunction with accompanying drawings and examples.

[0149] The present invention uses the pictures provided by the public data set KITTI and the laser laser point cloud data to illustrate the implementation steps and effects of obstacle detection.

[0150] Step 1: Implement 1.1) of the present invention on the single-frame original point cloud, calculate the curvature of each point and extract feature points, where N 1 Value 5, Ths curv The value is 0.1. The obtained feature points are as figure 1 As shown, the smaller one is the original point cloud, and the larger one is the feature point.

[0151] Step 2: Implement 1.2) of the present invention on the single-frame original point cloud, obtain the inter-frame pose through inter-frame feature point matching, and remove motion distortion from the original point cloud to obtain the first de-distortion under the frame tail coordinate system point cloud. The ...

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Abstract

The invention discloses a remote obstacle detection method based on laser radar multi-frame point cloud fusion. A local coordinate system and a world coordinate system are established, an extraction feature point of each laser point is calculated on an annular scanning line of the laser radar according to the original point cloud data under the local coordinate system, and the global pose of the current position relative to the initial position and the de-distortion point cloud in the world coordinate system are obtained through inter-frame feature point matching and map feature point matching; the de-distortion point clouds of the current frame and the previous frame are fused to obtain more compact de-distortion point cloud data, which is unified to the local coordinate system, then projection is performed on two-dimensional grids, and an obstacle is screened according to the height change features of each two-dimensional grid. According to the method in the invention, the problem that the detection rate of the remote barrier caused by sparse laser point clouds is low is solved, the remote barriers can be effectively detected, the error detection rate and the leak detection rateare low, and the system cost can be greatly reduced.

Description

technical field [0001] The invention relates to a robot obstacle detection method, in particular to a long-distance obstacle detection method based on lidar multi-frame point cloud fusion for unmanned vehicle navigation. Background technique [0002] In the field of autonomous navigation of unmanned vehicles, the traditional methods for obstacle detection include detection methods based on stereo vision, structured light, millimeter-wave radar and lidar. The detection method based on stereo vision uses the color, edge and texture features of obstacles in the image for feature extraction, compares them with the prior model, extracts obstacles, and then uses the parallax information of the same object between different cameras to obtain The depth of the obstacle, so as to determine the position of the obstacle. The disadvantage of this method is that it consumes a lot of computing resources, is easily affected by illumination, and because the conversion error from image pixel...

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Application Information

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IPC IPC(8): G05D1/02G01S17/93
CPCG05D1/0257G01S17/931
Inventor 张佳鹏项志宇
Owner ZHEJIANG UNIV
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