CN117636135A - Laser radar point cloud online data classification method and device based on edge calculation - Google Patents
Laser radar point cloud online data classification method and device based on edge calculation Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000004364 calculation method Methods 0.000 title claims abstract description 25
- 230000002159 abnormal effect Effects 0.000 claims description 15
- 230000005856 abnormality Effects 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 3
- 238000002310 reflectometry Methods 0.000 claims description 3
- 238000005265 energy consumption Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004093 laser heating Methods 0.000 description 1
- 238000002844 melting Methods 0.000 description 1
- 230000008018 melting Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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Abstract
The application discloses a laser radar point cloud online data classification method and device based on edge calculation, wherein the classification method comprises the following steps: the edge equipment collects and processes laser radar point cloud data in real time; and carrying out online data classification on the processed laser radar point cloud data to divide a region of interest of the laser radar point cloud data. The classifying device comprises: edge devices and point cloud data region of interest dividing devices. The method and the device have the advantages of improving the data classification efficiency, reducing the energy consumption of the edge equipment and the like.
Description
Technical Field
The application relates to the technical field of laser radar point cloud data online classification, in particular to a laser radar point cloud online data classification method and device based on edge calculation.
Background
Along with the wider and wider application of the laser radar at the edge end, how to apply the laser radar becomes important, and one of the key points of using the laser radar is to process the point cloud data.
Disclosure of Invention
In order to optimize the related traditional technical scheme, the application provides a laser radar point cloud online data classification method and device based on edge calculation.
In one aspect, the application provides a laser radar point cloud online data classification method based on edge calculation, which may include the following steps:
the edge equipment collects and processes laser radar point cloud data in real time;
and carrying out online data classification on the processed laser radar point cloud data to divide a region of interest of the laser radar point cloud data.
According to the technical scheme, the laser radar point cloud data after processing is subjected to online data classification to divide the region of interest of the laser radar point cloud data, so that the laser radar point cloud data which is not interested can be removed, the laser radar point cloud data for calculation is reduced, the calculation power of edge equipment can be reduced, the data classification efficiency is improved, and the energy consumption of the edge equipment is reduced.
The present application may be further configured in a preferred example to:
in the step of acquiring and processing the laser radar point cloud data in real time by the edge device, the acquisition method for acquiring the laser radar point cloud data may be the following expression:
wherein D is the point cloud data collected by the laser radar, F is the laser radar field angle, θ is the laser radar angle resolution, S is the laser radar detection distance, R is the reflectivity, and t is the time for collecting the laser radar point cloud data.
By adopting the technical scheme, the laser radar point cloud data can be efficiently and rapidly acquired and processed.
The present application may be further configured in a preferred example to:
the laser radar point cloud online data classification method based on edge calculation can further comprise the following steps:
and identifying a target in the interested area of the laser radar point cloud data and tracking the target.
In the technical scheme, the target of interest can be identified and tracked.
The present application may be further configured in a preferred example to:
the step of identifying a target within the region of interest of the lidar point cloud data and tracking the target may comprise the steps of:
identifying whether an abnormal condition occurs in the point cloud data concentration in the laser radar point cloud data region of interest;
when the cloud data concentration degree is abnormal, identifying a region in which the abnormal state of the point cloud data concentration degree appears as a target region of interest;
identifying a target of the target area and tracking the target.
By adopting the technical scheme, the accuracy of identifying and tracking the interested target can be improved.
The present application may be further configured in a preferred example to:
the laser radar point cloud online data classification method based on edge calculation can further comprise the following steps:
when targets in the laser radar point cloud data interested area cannot be identified, the microprocessor sends the point cloud data in the laser radar point cloud data interested area to a cloud server.
In the technical scheme, when the target in the region of interest of the laser radar point cloud data cannot be identified, the cloud server assists the edge device to identify the target, so that the range of the edge device capable of identifying the target is enlarged.
The present application may be further configured in a preferred example to:
in the step of classifying the processed laser radar point cloud data to obtain the region of interest of the laser radar point cloud data, the method for obtaining the region of interest of the laser radar point cloud data may be the following expression:
wherein m is i Is the ith laser radar point cloud data, m i-1 The i-1 th light Lei Dadian cloud data is that n is the total number of laser radar point cloud data, i is a positive integer, and epsilon is a constant.
In the technical scheme, the calculation method for dividing the laser radar point cloud data region of interest is simpler, and the calculation force of the edge equipment is further reduced.
On the other hand, the application provides a classification device of a laser radar point cloud online data classification method based on edge calculation, which can comprise the following steps:
the edge equipment is used for collecting and processing laser radar point cloud data in real time;
and the point cloud data interesting region dividing device is used for carrying out online data classification on the processed laser radar point cloud data so as to divide the laser radar point cloud data interesting region.
Aspects of another aspect of the present application may be further configured in a preferred example to:
the classification device may further include:
and the target identification and tracking equipment is used for identifying the target in the laser radar point cloud data region of interest and tracking the target.
Aspects of another aspect of the present application may be further configured in a preferred example to:
the target recognition and tracking device may include:
the point cloud data concentration degree abnormality identification unit is used for identifying whether an abnormality exists in the point cloud data concentration degree in the laser radar point cloud data region of interest;
the interesting target area dividing unit is used for identifying an area with abnormal conditions of the point cloud data concentration as an interesting target area when the abnormal conditions of the cloud data concentration occur;
and the target identification and tracking unit is used for identifying the target of the target area and tracking the target.
Aspects of another aspect of the present application may be further configured in a preferred example to:
the classification device may further include:
and the point cloud data sending equipment is used for sending the point cloud data in the laser radar point cloud data interested area to the cloud server when the target in the laser radar point cloud data interested area cannot be identified.
In summary, compared with the prior art, the application has at least the following beneficial effects:
according to the laser radar point cloud online data classification method based on edge calculation, the laser radar point cloud data after processing is subjected to online data classification to divide the region of interest of the laser radar point cloud data, the laser radar point cloud data which is not interested can be removed, the laser radar point cloud data used for calculation is reduced, so that the computing power of edge equipment is reduced, the data classification efficiency is improved, and the energy consumption of the edge equipment is reduced.
Drawings
Fig. 1 is a flowchart of a laser radar point cloud online data classification method based on edge calculation.
Fig. 2 is a block diagram of a sorting apparatus of the present application.
Detailed Description
The present application is described in further detail below with reference to the accompanying drawings.
Examples:
as shown in fig. 1, the process flow chart of the tapering method for melting the laser heating optical fiber in the application comprises the following steps:
s1, acquiring and processing laser radar point cloud data in real time by edge equipment;
s2, performing online data classification on the processed laser radar point cloud data to divide a region of interest of the laser radar point cloud data.
In order to efficiently and rapidly collect and process laser radar point cloud data, in the step of collecting and processing the laser radar point cloud data in real time by the edge device, a collecting method for collecting the laser radar point cloud data is as follows:
wherein D is the point cloud data collected by the laser radar, F is the laser radar field angle, θ is the laser radar angle resolution, S is the laser radar detection distance, R is the reflectivity, and t is the time for collecting the laser radar point cloud data.
In order to identify and track the interested target, the laser radar point cloud online data classification method based on edge calculation can further comprise the following steps:
and identifying a target in the interested area of the laser radar point cloud data and tracking the target.
In order to improve the accuracy of identifying and tracking the target of interest, the steps of identifying the target in the laser radar point cloud data region of interest and tracking the target include the following steps:
identifying whether an abnormal condition occurs in the point cloud data concentration in the laser radar point cloud data region of interest;
when the cloud data concentration degree is abnormal, identifying a region in which the abnormal state of the point cloud data concentration degree appears as a target region of interest;
identifying a target of the target area and tracking the target.
When the target in the interested area of the laser radar point cloud data cannot be identified, the cloud server assists the edge equipment to identify the target, and the range of the identifiable target of the edge equipment is enlarged, so that the online data classification method of the laser radar point cloud based on the edge calculation can further comprise the following steps:
when targets in the laser radar point cloud data interested area cannot be identified, the microprocessor sends the point cloud data in the laser radar point cloud data interested area to a cloud server.
In order to further reduce the calculation force of the edge equipment, performing online data classification on the processed laser radar point cloud data so as to divide the region of interest of the laser radar point cloud data, wherein the dividing method for dividing the region of interest of the laser radar point cloud data is as follows:
wherein m is i Is the ith laser radar point cloud data, m i-1 The i-1 th light Lei Dadian cloud data is that n is the total number of laser radar point cloud data, i is a positive integer, and epsilon is a constant.
Fig. 2 is a block diagram of a classification device for implementing the above-mentioned laser radar point cloud online data classification method based on edge calculation, which specifically includes:
the edge equipment is used for collecting and processing laser radar point cloud data in real time;
and the point cloud data interesting region dividing device is used for carrying out online data classification on the processed laser radar point cloud data so as to divide the laser radar point cloud data interesting region.
The classification device may further include:
and the target identification and tracking equipment is used for identifying the target in the laser radar point cloud data region of interest and tracking the target.
The target recognition and tracking device specifically comprises:
the point cloud data concentration degree abnormality identification unit is used for identifying whether an abnormality exists in the point cloud data concentration degree in the laser radar point cloud data region of interest;
the interesting target area dividing unit is used for identifying an area with abnormal conditions of the point cloud data concentration as an interesting target area when the abnormal conditions of the cloud data concentration occur;
and the target identification and tracking unit is used for identifying the target of the target area and tracking the target.
The sorting apparatus further includes:
and the point cloud data sending equipment is used for sending the point cloud data in the laser radar point cloud data interested area to the cloud server when the target in the laser radar point cloud data interested area cannot be identified.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. The laser radar point cloud online data classification method based on edge calculation is characterized by comprising the following steps of:
the edge equipment collects and processes laser radar point cloud data in real time;
and carrying out online data classification on the processed laser radar point cloud data to divide a region of interest of the laser radar point cloud data.
2. The method for classifying laser radar point cloud online data based on edge calculation according to claim 1, wherein in the step of acquiring and processing laser radar point cloud data in real time by the edge device, the acquisition method for acquiring the laser radar point cloud data is as follows:
wherein D is the point cloud data collected by the laser radar, F is the laser radar field angle, θ is the laser radar angle resolution, S is the laser radar detection distance, R is the reflectivity, and t is the time for collecting the laser radar point cloud data.
3. The method for classifying laser radar point cloud online data based on edge calculation according to claim 1, further comprising the steps of:
and identifying a target in the interested area of the laser radar point cloud data and tracking the target.
4. The method for classifying lidar point cloud online data based on edge computation of claim 3, wherein the steps of identifying a target within a region of interest of the lidar point cloud data and tracking the target comprise the steps of:
identifying whether an abnormal condition occurs in the point cloud data concentration in the laser radar point cloud data region of interest;
when the cloud data concentration degree is abnormal, identifying a region in which the abnormal state of the point cloud data concentration degree appears as a target region of interest;
identifying a target of the target area and tracking the target.
5. The laser radar point cloud online data classification method based on edge calculation according to claim 3, further comprising the steps of:
when targets in the laser radar point cloud data interested area cannot be identified, the microprocessor sends the point cloud data in the laser radar point cloud data interested area to a cloud server.
6. The method for classifying laser radar point cloud online data based on edge calculation according to claim 1, wherein in the step of classifying the processed laser radar point cloud data to classify the region of interest of the laser radar point cloud data, the method for classifying the region of interest of the laser radar point cloud data is as follows:
wherein m is i Is the ith laser radar point cloud data, m i-1 The i-1 th light Lei Dadian cloud data is that n is the total number of laser radar point cloud data, i is a positive integer, and epsilon is a constant.
7. A classification apparatus for implementing the edge-computing-based laser radar point cloud online data classification method of claim 1, comprising:
the edge equipment is used for collecting and processing laser radar point cloud data in real time;
and the point cloud data interesting region dividing device is used for carrying out online data classification on the processed laser radar point cloud data so as to divide the laser radar point cloud data interesting region.
8. The classification apparatus of claim 7, further comprising:
and the target identification and tracking equipment is used for identifying the target in the laser radar point cloud data region of interest and tracking the target.
9. The classification apparatus of claim 7, wherein the target recognition and tracking device comprises:
the point cloud data concentration degree abnormality identification unit is used for identifying whether an abnormality exists in the point cloud data concentration degree in the laser radar point cloud data region of interest;
the interesting target area dividing unit is used for identifying an area with abnormal conditions of the point cloud data concentration as an interesting target area when the abnormal conditions of the cloud data concentration occur;
and the target identification and tracking unit is used for identifying the target of the target area and tracking the target.
10. The classification apparatus of claim 7, further comprising:
and the point cloud data sending equipment is used for sending the point cloud data in the laser radar point cloud data interested area to the cloud server when the target in the laser radar point cloud data interested area cannot be identified.
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