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Three-dimensional laser noise reduction method and device, medium and robot

A three-dimensional laser, laser technology, applied in the field of laser, can solve the problem that the algorithm cannot be eliminated, and achieve the effect of high accuracy, good noise, and noise removal

Pending Publication Date: 2022-07-05
广州高新兴机器人有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] In method 2, for the static outlier removal algorithm, since the noise is irregular, it is very likely that a piece of noise is connected together, and the algorithm cannot be removed at this time;

Method used

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  • Three-dimensional laser noise reduction method and device, medium and robot
  • Three-dimensional laser noise reduction method and device, medium and robot
  • Three-dimensional laser noise reduction method and device, medium and robot

Examples

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Embodiment 1

[0062] For the outdoor robot, this embodiment has two assumptions:

[0063] a), the outdoor robot scene features are more obvious, there are more cars, trees, buildings, etc.;

[0064] b) The rain and snow noise of the outdoor robot is a scattered area centered on the body coordinate system and spreads outward, and is irregular.

[0065] Among them, in assumption a, the outdoor robot generally runs outdoors, and it generally has obvious buildings, cars or trees. For hypothesis a, each keyframe scanned by the laser is characterized. This embodiment makes full use of the characteristic that each key frame of the laser frame has features, so that the globally unique description corresponding to each key frame has a unique identifier, which increases robustness and reduces singular values; for hypothesis b, this is A weak assumption that all noise caused by rain and snow satisfies this assumption.

[0066] refer to figure 1 , this embodiment discloses a three-dimensional laser...

Embodiment 2

[0098] refer to Figure 5 , this embodiment discloses a three-dimensional laser noise reduction device, which includes the following units:

[0099] Point cloud acquisition unit, used to acquire 3D laser point cloud images;

[0100] Specifically, the point cloud acquisition unit can receive 3D laser point cloud data through a callback function, and the 3D laser point cloud data includes: x-direction coordinates, y-direction coordinates, and z-direction coordinates.

[0101] a downsampling unit, configured to downsample the 3D laser point cloud data to obtain downsampled 3D laser point cloud data;

[0102] After receiving the 3D laser point cloud, there are a huge number of laser points in the point cloud. The number of points will seriously affect the time complexity of noise reduction. In order to reduce the amount of calculation and ensure the integrity of the data, voxel downsampling is used.

[0103] Specifically, the down-sampling unit performs down-sampling on 0.1 m c...

Embodiment 3

[0132] refer to Figure 7 , Figure 7 It is a schematic structural diagram of a three-dimensional laser noise reduction device in this embodiment. The three-dimensional laser noise reduction apparatus 20 of this embodiment includes a processor 21 , a memory 22 , and a computer program stored in the memory 22 and executable on the processor 21 . When the processor 21 executes the computer program, the steps in the foregoing method embodiments are implemented. Alternatively, when the processor 21 executes the computer program, the functions of the modules / units in the foregoing device embodiments are implemented.

[0133] Exemplarily, the computer program may be divided into one or more modules / units, and the one or more modules / units are stored in the memory 22 and executed by the processor 21 to complete the present invention. invention. The one or more modules / units may be a series of computer program instruction segments capable of accomplishing specific functions, and t...

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Abstract

The invention provides a three-dimensional laser noise reduction method and device, a medium and a robot. The three-dimensional laser noise reduction method comprises the following steps: S1, acquiring a 3D laser point cloud image; s2, carrying out downsampling on the 3D laser point cloud data to obtain downsampled 3D laser point cloud data; s3, converting the down-sampled 3D laser point cloud data into a kd tree; s4, calculating the distance of each point in the down-sampled 3D laser point cloud under the laser coordinate system; s5, calculating a search radius ri according to the distance of each point in the laser coordinate system; and S6, calculating the nearest neighbor of each point in the point cloud according to the dynamic radius, searching whether the threshold value of the minimum point in the current sphere is satisfied, if the current point is satisfied, retaining the point, and otherwise, rejecting the point. According to the three-dimensional laser noise reduction method provided by the embodiment of the invention, noise in snow removal weather can be effectively removed.

Description

technical field [0001] The present invention relates to the field of laser technology, and in particular, to a three-dimensional laser noise reduction method, device, medium and robot. Background technique [0002] Autonomous navigation mobile robots require 3D laser sensors to measure and obtain raw data. However, due to the band characteristics of the 3D laser sensor, in extreme weather such as rain and snow, there will be a lot of random noise in the raw data, which will affect all functions based on the 3D laser sensor. [0003] For outdoor patrol inspection robots, the original 3D laser point cloud data is usually needed. However, the sparse point cloud produced by lidar can be corrupted by internal noise and external environmental noise, resulting in inaccurate measurements. And the generated noise is irregular. Therefore, some special methods need to be used for noise removal. [0004] At present, there are three methods for 3D laser point cloud denoising: [000...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/20G06T5/00
CPCG06T17/20G06T2207/10028G06T5/70
Inventor 李瀚文袁国斌刘彪柏林舒海燕沈创芸祝涛剑王恒华
Owner 广州高新兴机器人有限公司
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