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Point Cloud Data Registration Method

A technology of point cloud data and cloud data, applied in the field of lidar data post-processing, can solve the problems of large position error, difficult application, large amount of calculation, etc., to achieve the effect of improving accuracy and efficiency, small amount of calculation and high precision

Active Publication Date: 2021-11-30
XIDIAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In the prior art, the lidar point cloud information conversion modeling method mainly includes: (1) local coordinate system conversion; (2) world coordinate conversion; (3) point cloud data registration; in the point cloud data registration process, The existing optimal registration matrix acquisition technology for 3D point cloud data registration is a registration method based on geometric transformation model, which has a large position error; the registration based on singular value decomposition and quaternion iterative nearest algorithm The quasi-accuracy has been significantly improved, but the calculation amount is relatively large, and it is difficult to apply in the actual system

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Embodiment 1

[0055] See figure 1 , is a schematic flowchart of a point cloud data registration method provided by an embodiment of the present invention. The point cloud data registration method includes the following steps:

[0056] (a) obtaining the first point cloud data set and the second point cloud data set;

[0057] (b) constructing the sum of squares of distances between the first point cloud dataset and the second point cloud dataset;

[0058] (c) Minimizing the sum of squared distances to obtain a registration matrix.

[0059] The point cloud data registration method of the present invention obtains the optimal registration matrix by constructing the sum of squares of the distances of the feature points and calculating the minimum value of the sum of squares of the distances, which has small errors, high precision, small amount of calculation, and significantly improves the point cloud data registration method. Accuracy and efficiency of cloud registration.

Embodiment 2

[0061] see again figure 1 , on the basis of the foregoing embodiments, this embodiment focuses on a detailed description of the point cloud data registration method. The point cloud data registration method includes the following steps:

[0062] (a) obtaining the first point cloud data set and the second point cloud data set;

[0063] (b) constructing the sum of squares of distances between the first point cloud dataset and the second point cloud dataset;

[0064] (c) Minimizing the sum of squared distances to obtain a registration matrix.

[0065] Wherein, step (c) includes: minimizing the sum of squared distances includes: making a derivative of the sum of squared distances be 0.

[0066] Specifically, step (c) includes:

[0067] (c1) according to the expression of rotation parameter rotation matrix and according to the expression of translation parameter construction translation matrix;

[0068] (c2) constructing an expression of the distance sum of squares according to ...

Embodiment 3

[0086] This embodiment introduces a laser radar data processing method on the basis of the above embodiments, including the following steps:

[0087] (x1) Obtain distance response information;

[0088] (x2) performing local coordinate transformation on the distance response information to obtain the first point cloud data;

[0089] (x3) performing world coordinate transformation on the first point cloud data to obtain second point cloud data;

[0090] (x4) Acquiring the first point cloud data set and the second point cloud data set respectively corresponding to the distance response information of two adjacent frames according to the second point cloud data;

[0091] (x5) generating a registration matrix using the point cloud data registration method as described in the above-mentioned embodiment according to the first point cloud data set and the second point cloud data set;

[0092] (x6) generating the third point cloud data after registration according to the registration...

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Abstract

The present invention relates to a point cloud data registration method, comprising the following steps: (a) acquiring a first point cloud data set and a second point cloud data set; (b) constructing the first point cloud data set and the second point cloud data set The sum of squares of the two point cloud datasets; (c) minimizing the sum of squares of the distances to obtain a registration matrix. The point cloud data registration method of the present invention obtains the optimal registration matrix by constructing the sum of squares of the distances of the feature points and calculating the minimum value of the sum of squares of the distances, which has small errors, high precision, small amount of calculation, and significantly improves the point cloud data registration method. Accuracy and efficiency of cloud registration.

Description

technical field [0001] The invention belongs to the field of laser radar data post-processing, and in particular relates to a point cloud data registration method. Background technique [0002] Lidar, collectively referred to as optical radar, or LIDAR (Light Detection and Ranging) for short, is an optical remote sensing technology that measures the distance and other parameters of the target by irradiating a beam of light, usually a pulsed laser, to the target. LiDAR has a wide range of applications in surveying and mapping, archaeology, geography, landforms, earthquakes, forestry, remote sensing, and atmospheric physics. In addition, this technology is also used in airborne laser mapping, laser altimetry, and lidar contour drawing. [0003] LiDAR is an active optical sensor that fires a laser beam at a target while moving along a specific measurement path. The receiver in a lidar sensor detects and analyzes the laser light reflected from the target. These receiving sens...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/16
CPCG06F17/16
Inventor 吴鑫谢建王迷珍黄曦张建奇
Owner XIDIAN UNIV