WO2023045195A1

WO2023045195A1 - Method and apparatus for detecting flatness of working area, device, medium and product

Info

Publication number: WO2023045195A1
Application number: PCT/CN2022/073796
Authority: WO
Inventors: 程渊; 陈浩; 刘明亮
Original assignee: 上海三一重机股份有限公司
Priority date: 2021-09-27
Filing date: 2022-01-25
Publication date: 2023-03-30
Also published as: CN114004873A

Abstract

A method for detecting flatness of a working area, comprising: acquiring a target point cloud set and a target image corresponding to a working area; determining a determination parameter corresponding to each target point cloud in the target point cloud set, the determination parameter being used for indicating the flatness of the working area; performing a plane fitting operation on the target point cloud on the basis of the determination parameter to obtain a point cloud plane; rendering the target point cloud in the point cloud plane on the basis of the target image and a preset conversion relationship to obtain the rendering result, the conversion relationship being a correspondence between the target point cloud and the target image; and detecting the flatness of the working area on the basis of the rendering result. Further disclosed are a device for detecting flatness of a working area, an electronic device, a storage medium, and a product.

Description

Method, device, equipment, medium and product for detecting flatness of working area

Cross References to Related Applications

This application claims the priority of the Chinese patent application filed on September 27, 2021 with the application number 202111138696.0 and titled "Method, device, equipment, medium and product for detecting the flatness of the working area", which is incorporated by reference in its entirety. into this article.

technical field

The present application relates to the technical field of earthwork operations, in particular to a method, device, equipment, medium and product for detecting the flatness of an operation area.

Background technique

At present, intelligent technology and unmanned technology are more and more widely used in excavators, loaders, road rollers and other operating machinery. Various auxiliary functions are configured on the working machine to improve the working efficiency of the working machine and optimize the working accuracy.

At present, when the operation machine is operating, the judgment of the operation effect is mostly done manually, and the operation effect is judged by manual measurement. However, judging the operation effect of the operation machine manually has caused many problems such as an increase in labor costs, a decrease in overall operation efficiency, and an increase in operation time.

Therefore, how to improve the efficiency of judging the operating effect of the operating machine is an urgent problem to be solved in the industry.

Contents of the invention

The embodiment of the present application provides a method, device, equipment, medium and product for detecting the flatness of the working area, which is used to solve the problems of high cost, low efficiency and long time consumption caused by manual judgment of the working effect of the working machine in the prior art Defects, to achieve fast and accurate judgment of the operating effect of the operating machine.

The embodiment of the present application provides a method for detecting the flatness of the work area, including:

Obtain the target point cloud and target image corresponding to the operation area;

determining a determination parameter corresponding to each target point cloud in the target point cloud set, where the determination parameter is used to indicate the flatness of the operation area;

Based on the determination parameters, perform a plane fitting operation on the target point cloud to obtain a point cloud plane;

Rendering the target point cloud in the point cloud plane based on the target image and a preset conversion relationship to obtain a rendering result, the conversion relationship being a corresponding relationship between the target point cloud and the target image;

Based on the rendering result, the flatness of the working area is detected.

According to the detection method of the flatness of the working area according to an embodiment of the present application, the determination parameters include: normal vector and curvature;

The determination of the determination parameters corresponding to each target point cloud in the target point cloud set includes:

Perform the following first processing procedure on each target point cloud:

Taking the target point cloud as the center to acquire a first preset number of target point clouds from adjacent areas to obtain a local point cloud plane; based on the local point cloud plane, calculate the normal vector and curvature corresponding to the target point cloud.

According to the detection method of the flatness of the working area according to an embodiment of the present application, the said target point cloud is subjected to a plane fitting operation based on the determination parameters to obtain a point cloud plane, including:

Select any one of the target point clouds from the set of target point clouds as a seed point cloud;

Based on the seed point cloud, the following second processing procedure is performed:

Taking the seed point cloud as the center to obtain a second preset number of target point clouds from adjacent areas; based on the normal vector, extracting an effective target point cloud from the second preset number of target point clouds; based on the curvature, determining at least one new seed point cloud from said valid target point cloud;

Repeating the second processing procedure until it is judged whether each target point cloud in the target point cloud set is extracted as the valid target point cloud;

Perform a plane fitting operation on the valid target point cloud obtained by executing the second processing each time to obtain the point cloud plane.

According to the detection method of the flatness of the working area according to an embodiment of the present application, the extraction of effective target point clouds from the second preset number of target point clouds based on the normal vector includes:

Calculate the included angle between the normal vector corresponding to the seed point cloud and the normal vector of each target point cloud in the second preset quantity;

Using the corresponding target point cloud when the included angle is smaller than the preset included angle as the effective target point cloud;

The determining at least one new seed point cloud from the valid target point cloud based on the curvature includes:

When the curvature of the target point cloud in the effective target point cloud is smaller than the preset curvature, the corresponding target point cloud is used as the new seed point cloud.

According to the method for detecting the flatness of the work area according to an embodiment of the present application, the detection of the flatness of the work area based on the rendering result includes:

Detect whether the rendering result includes an unrendered area;

When it is determined that the unrendered area is included, it is determined that the flatness of the working area corresponding to the unrendered area is unqualified.

According to the detection method of the flatness of the work area according to an embodiment of the present application, before the acquisition of the target point cloud and the target image corresponding to the work area, it also includes:

Obtain the original point cloud set and original image obtained by the detection unit;

Obtaining the preset scope of the operation area;

The target point cloud set is extracted from the original point cloud set, and the target image is extracted from the original image based on the range of the working area.

The embodiment of the present application provides a detection device for the flatness of the working area, including:

An acquisition module, configured to acquire target point cloud sets and target images corresponding to the operation area;

A determination module, configured to determine a determination parameter corresponding to each target point cloud in the target point cloud set, where the determination parameter is used to indicate the flatness of the working area;

A fitting module, configured to perform a plane fitting operation on the target point cloud based on the determination parameters to obtain a point cloud plane;

A rendering module, configured to render the target point cloud in the point cloud plane based on the target image and a preset conversion relationship to obtain a rendering result, the conversion relationship being between the target point cloud and the target image Correspondence between;

A detection module, configured to detect the flatness of the operation area based on the rendering result.

The embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor, and the processor implements any of the above-mentioned tasks when executing the program The steps of the method for detecting the flatness of an area.

The embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any method for detecting the flatness of the working area described above are implemented.

The embodiment of the present application also provides a computer program product, including a computer program, characterized in that, when the computer program is executed by a processor, the steps of any one of the methods for detecting the flatness of the working area described above are implemented.

The method, device, equipment, medium and product for detecting the flatness of the work area provided in the embodiments of the present application obtain the target point cloud set and the target image corresponding to the work area; determine the determination parameters corresponding to each target point cloud in the target point cloud set, The judgment parameter is used to indicate the flatness of the work area; based on the judgment parameter, the plane fitting operation is performed on the target point cloud to obtain the point cloud plane; based on the target image and the preset conversion relationship, the target point in the point cloud plane is rendered Cloud, to get the rendering result, the conversion relationship is the corresponding relationship between the target point cloud and the target image; based on the rendering result, the flatness of the operation area is detected, and this application can be directly based on the target point cloud set and the target image corresponding to the operation area. Detect the flatness of the operation area, that is, the operation effect, which solves the defects of high cost, low efficiency and long time-consuming caused by manually judging the operation effect of the operation machine in the prior art, and realizes the rapid and accurate judgment of the operation of the operation machine The flatness of the area effectively saves labor costs, improves the efficiency of job flatness detection, and improves user experience.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are For some embodiments of the present application, those of ordinary skill in the art can also obtain other drawings based on these drawings without creative effort.

Fig. 1 is one of the schematic flow charts of a method for detecting the flatness of a working area provided by the embodiment of the present application;

Fig. 2 is the second schematic flow diagram of a method for detecting the flatness of a working area provided by the embodiment of the present application;

Fig. 3 is the third schematic flow diagram of a method for detecting the flatness of the work area provided by the embodiment of the present application;

Fig. 4 is a schematic structural diagram of a detection device for flatness of a work area provided by an embodiment of the present application;

FIG. 5 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

The method for detecting the flatness of the work area according to the embodiment of the present application will be described below with reference to FIGS. 1 to 3 .

An embodiment of the present application provides a method for detecting the flatness of a work area, and the method can be applied to work machines, such as excavators, loaders, and road rollers, and can also be applied to servers. In the following, the application of this method in an excavator is taken as an example for illustration, but it should be noted that it is only for illustration and is not intended to limit the scope of protection of the present application. Some other descriptions in the embodiments of the present application are also examples, and are not used to limit the protection scope of the present application, and will not be described one by one later. The specific implementation of this method is shown in Figure 1:

Step 101, acquiring target point cloud sets and target images corresponding to the work area.

In a specific example, the original point cloud set and the original image obtained by the detection unit installed on the excavator are obtained, and the range of the operation area preset by the user is obtained; based on the range of the operation area, the target point is extracted from the original point cloud set clustering, and extracting the target image from the original image.

Specifically, the detection unit includes a laser radar and a camera. The laser radar includes: solid-state laser radar, millimeter wave radar, ultrasonic radar, etc., and the camera includes a monocular camera, a double-sided camera, and the like. The lidar is used to obtain the target point cloud, and the camera is used to obtain the target image.

Among them, the area that the laser radar can detect is the laser radar coverage area, and the area that the camera can detect is the camera coverage area. However, in this application, it is not necessary to detect the flatness of all the laser radar coverage area and the camera coverage area. To detect the working area that the user is interested in, it is necessary to artificially set the scope of the working area in advance, and only detect the flatness of the preset working area. See Figure 2 for details.

Specifically, while setting the range of the work area, the user also needs to set a determination parameter, which is used to indicate the flatness of the work area.

In addition, after the lidar and the camera are installed on the excavator, joint calibration is required to determine the conversion relationship between the point cloud coordinate system and the camera coordinate system, that is, to determine the conversion relationship between point cloud coordinates and pixel coordinates, that is, to determine the target Correspondence between point cloud and target image.

Step 102, determine the decision parameters corresponding to each target point cloud in the target point cloud set.

Wherein, the determination parameters include: normal vector and curvature.

In a specific embodiment, the determination parameter corresponding to each target point cloud is determined by performing the first processing procedure on each target point cloud. The first processing process specifically includes: taking the target point cloud as the center, obtaining the first preset number of target point clouds from the adjacent area of the target point cloud to obtain a local point cloud plane; based on the local point cloud plane, calculating the target point cloud corresponding The normal vector and curvature of .

Step 103, based on the determination parameters, perform a plane fitting operation on the target point cloud to obtain a point cloud plane.

Specifically, the present application adopts the method of expanding the connected area of adjacent points to obtain the final point cloud plane.

In a specific embodiment, the implementation process of the point cloud plane is specifically shown in Figure 3:

Step 301, select any target point cloud from the target point cloud set as a seed point cloud. Step 302, based on the seed point cloud, perform the following second processing procedure: take the seed point cloud as the center, obtain a second preset number of target point clouds from the adjacent area of the seed point cloud; based on the normal vector, from the second preset number Extract an effective target point cloud from the target point cloud; determine at least one new seed point cloud from the effective target point cloud based on the curvature.

Below, a complete point cloud plane formation process is described in detail:

First, any target point cloud is selected from the target point cloud set as the initial seed point cloud, and the target point cloud corresponding to the minimum curvature can be selected as the seed point cloud.

Furthermore, with the initial seed point cloud as the center, a second preset number of target point clouds is obtained from the adjacent area of the initial seed point cloud; based on the normal vector, an effective target point cloud is extracted from the second preset number of target point clouds , the plane fitting operation is performed on the effective target point cloud and the initial seed point cloud to obtain the initial point cloud plane.

Finally, based on the curvature, at least one new seed point cloud is determined from the effective target point cloud, and the new seed point cloud is used as the initial seed point cloud.

In a specific embodiment, the present application calculates the included angle between the normal vector corresponding to the seed point cloud and the normal vector of each target point cloud in the second preset number, and the corresponding target when the included angle is smaller than the preset included angle point cloud, as a valid target point cloud.

In a specific embodiment, when the curvature of the target point cloud in the effective target point cloud is smaller than the preset curvature, the corresponding target point cloud is used as a new seed point cloud.

In step 303, step 302 is repeatedly executed until it is determined whether each target point cloud in the target point cloud set is extracted as the valid target point cloud.

Step 304, carry out the plane fitting operation on the effective target point cloud obtained by executing the second processing each time to obtain the point cloud plane.

Specifically, the plane fitting operation is performed on the effective target point cloud obtained by the second processing process and the target point cloud in the previous initial point cloud plane to obtain a new initial point cloud plane, and the new initial point cloud plane The cloud plane is used as the initial point cloud plane until it is judged whether each target point cloud in the target point cloud set is extracted as the effective target point cloud, and the new initial point cloud plane at this time is used as the point cloud plane.

Step 104, based on the target image and the preset conversion relationship, render the target point cloud in the point cloud plane to obtain a rendering result.

Specifically, determine the RGB value corresponding to each pixel in the target image, and determine the target point cloud corresponding to each pixel based on the conversion relationship. After the determination is completed, render the color of each target point cloud based on the RGB value of the pixel, and obtain the rendered result.

Wherein, the rendering result may be a rendered three-dimensional stereogram, or may be a rendered two-dimensional image.

Step 105, based on the rendering result, detect the flatness of the working area.

In a specific embodiment, it is detected whether the rendering result includes an unrendered area. When it is determined that the unrendered area is included, it is determined that the flatness of the job area corresponding to the unrendered area is unqualified. When it is determined that the rendering result does not include When including unrendered areas, make sure that the flatness of the entire working area is acceptable.

Specifically, for example, when the rendering result is a rendered 3D stereogram, it is detected whether an unrendered image area is included in the rendered 3D stereogram, and when it is determined that the unrendered image area is included, the unrendered image area is determined The flatness of the corresponding operation area is unqualified, and when it is determined that the unrendered image area is not included, it is determined that the flatness of the entire operation area is qualified.

For another example, when the rendering result is a rendered two-dimensional image, detect whether the rendered two-dimensional image includes an unrendered image area, and when it is determined that the unrendered image area is included, determine the unrendered image area The flatness of the corresponding operation area is unqualified, and when it is determined that the unrendered image area is not included, it is determined that the flatness of the entire operation area is qualified.

Specifically, this application uses the RGB value of the pixel in the target image to render and color each target point cloud, that is, the area with the preset color in the rendering result is the rendered area, and the area without the preset color in the rendering result is Areas that are not rendered. Wherein, the preset color is the color corresponding to the actual working area.

For example, when the rendering result is a rendered 3D stereogram, the area in the 3D stereogram whose color is the preset color is the rendered area, and the area in the 3D stereogram whose color is not the preset color is the unrendered area. For another example, when the rendering result is a rendered 2D image, the area in the 2D image whose color is the preset color is the rendered area, and the area in the 2D image whose color is not the preset color is the unrendered area.

Specifically, the present application uses the RGB value of the pixel in the target image to render and color each target point cloud, that is, the area with color in the rendering result is the rendered area, and the area without color is the unrendered area.

For example, when the rendering result is a rendered 3D stereogram, the region with color in the 3D stereogram is the rendered region, and the region without color in the 3D stereogram is the unrendered region. For another example, when the rendering result is a rendered 2D image, the area with color in the 2D image is the rendered area, and the area without color in the 2D image is the unrendered area.

In addition, after it is determined that the flatness of the work area corresponding to the unrendered image area is unqualified, the operator can be prompted with the actual position of the unqualified image area in the work area in the form of voice or text, reminding the operator Unqualified positions are repaired, which effectively saves labor costs and improves user experience.

The following is a description of the detection device for the flatness of the working area provided by the embodiment of the present application. The detection device for the flatness of the working area described below and the detection method for the flatness of the working area described above can be referred to each other, and the repetitions will not be repeated. , see Figure 4 for details.

An acquisition module 401, configured to acquire target point cloud sets and target images corresponding to the work area;

A determination module 402, configured to determine a determination parameter corresponding to each target point cloud in the target point cloud set, where the determination parameter is used to indicate the flatness of the work area;

The fitting module 403 is used to perform a plane fitting operation on the target point cloud based on the determination parameters to obtain a point cloud plane;

The rendering module 404 is used to render the target point cloud in the point cloud plane based on the target image and the preset conversion relationship to obtain a rendering result, and the conversion relationship is the corresponding relationship between the target point cloud and the target image;

The detection module 405 is configured to detect the flatness of the work area based on the rendering result.

In a specific embodiment, the determination parameters include: a normal vector and a curvature; the determination module 402 is specifically configured to perform the following first processing procedure on each target point cloud:

Taking the target point cloud as the center to obtain a first preset number of target point clouds from adjacent areas to obtain a local point cloud plane; based on the local point cloud plane, calculate the normal vector and curvature corresponding to the target point cloud.

In a specific embodiment, the fitting module 403 is specifically used to select any target point cloud from the target point cloud set as the seed point cloud; based on the seed point cloud, the following second processing process is performed: centering on the seed point cloud Obtaining a second preset number of target point clouds in the adjacent area; extracting a valid target point cloud from the second preset number of target point clouds based on the normal vector; determining at least one new seed from the valid target point cloud based on the curvature Point cloud: Repeat the second processing procedure until each target point cloud in the target point cloud set is judged to be extracted as the effective target point cloud; carry out plane fitting to the effective target point cloud obtained by performing the second processing procedure each time Operation to get the point cloud plane.

In a specific embodiment, the fitting module 403 is specifically used to calculate the angle between the normal vector corresponding to the seed point cloud and the normal vector of each target point cloud in the second preset number; make the angle smaller than the preset angle The target point cloud corresponding to the angle is used as the effective target point cloud; when the curvature of the target point cloud in the effective target point cloud is less than the preset curvature, the corresponding target point cloud is used as the new seed point cloud.

In a specific embodiment, the detection module 405 is specifically configured to detect whether an unrendered area is included in the rendering result; when it is determined that an unrendered area is included, it is determined that the flatness of the job area corresponding to the unrendered area is unqualified .

In a specific embodiment, the acquisition module 401 is also used to acquire the original point cloud set and the original image obtained by the detection unit; acquire the scope of the preset work area; based on the scope of the work area, extract the target point cloud set from the original point cloud set , and extract the target image from the original image.

Figure 5 illustrates a schematic diagram of the physical structure of an electronic device, as shown in Figure 5, the electronic device may include: a processor (processor) 501, a communication interface (Communications Interface) 502, a memory (memory) 503 and a communication bus 504, Wherein, the processor 501 , the communication interface 502 , and the memory 503 communicate with each other through the communication bus 504 . The processor 501 can call the logic instructions in the memory 503 to execute the method for detecting the flatness of the work area, the method includes: acquiring the target point cloud set and the target image corresponding to the work area; determining the target point cloud corresponding to each target point cloud in the target point cloud set Judgment parameters, the judgment parameters are used to indicate the flatness of the work area; based on the judgment parameters, the plane fitting operation is performed on the target point cloud to obtain the point cloud plane; based on the target image and the preset conversion relationship, the points in the point cloud plane are rendered The target point cloud obtains the rendering result, and the conversion relationship is the corresponding relationship between the target point cloud and the target image; based on the rendering result, the flatness of the work area is detected.

In addition, the above logic instructions in the memory 503 may be implemented in the form of software function units and when sold or used as an independent product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc., which can store program codes. .

On the other hand, the present application also provides a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer During execution, the computer can execute the detection method for the flatness of the work area provided by the above methods, the method includes: obtaining the target point cloud set and the target image corresponding to the work area; determining the determination parameters corresponding to each target point cloud in the target point cloud set , the judgment parameter is used to indicate the flatness of the work area; based on the judgment parameter, the plane fitting operation is performed on the target point cloud to obtain the point cloud plane; based on the target image and the preset conversion relationship, the target point in the point cloud plane is rendered Cloud, get the rendering result, and convert the relationship into the corresponding relationship between the target point cloud and the target image; based on the rendering result, detect the flatness of the work area.

In yet another aspect, the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is implemented to perform the detection methods for the flatness of the work area provided by each of the above, the The method includes: obtaining the target point cloud set and the target image corresponding to the operation area; determining the determination parameters corresponding to each target point cloud in the target point cloud set, and the determination parameters are used to indicate the flatness of the operation area; based on the determination parameters, the target point cloud is The plane fitting operation obtains the point cloud plane; based on the target image and the preset conversion relationship, the target point cloud in the point cloud plane is rendered to obtain the rendering result, and the conversion relationship is the corresponding relationship between the target point cloud and the target image; Based on the rendering results, the flatness of the working area is detected.

The device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative efforts.

Through the above description of the implementations, those skilled in the art can clearly understand that each implementation can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic discs, optical discs, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

A method for detecting the flatness of a working area, comprising:

Obtain the target point cloud and target image corresponding to the operation area;

determining a determination parameter corresponding to each target point cloud in the target point cloud set, where the determination parameter is used to indicate the flatness of the operation area;

Based on the determination parameters, perform a plane fitting operation on the target point cloud to obtain a point cloud plane;

Rendering the target point cloud in the point cloud plane based on the target image and a preset conversion relationship to obtain a rendering result, the conversion relationship being a corresponding relationship between the target point cloud and the target image;

Based on the rendering result, the flatness of the working area is detected.
The method for detecting the flatness of the work area according to claim 1, wherein the determination parameters include: a normal vector and a curvature;

The determination of the determination parameters corresponding to each target point cloud in the target point cloud set includes:

Perform the following first processing procedure on each target point cloud:

Taking the target point cloud as the center to acquire a first preset number of target point clouds from adjacent areas to obtain a local point cloud plane; based on the local point cloud plane, calculate the normal vector and curvature corresponding to the target point cloud.
The method for detecting the flatness of an operation area according to claim 2, wherein, based on the determination parameters, performing a plane fitting operation on the target point cloud to obtain a point cloud plane includes:

Select any one of the target point clouds from the set of target point clouds as a seed point cloud;

Based on the seed point cloud, the following second processing procedure is performed:

Taking the seed point cloud as the center to obtain a second preset number of target point clouds from adjacent areas; based on the normal vector, extracting an effective target point cloud from the second preset number of target point clouds; based on the curvature, determining at least one new seed point cloud from said valid target point cloud;

Repeating the second processing procedure until it is judged whether each target point cloud in the target point cloud set is extracted as the valid target point cloud;

Perform a plane fitting operation on the valid target point cloud obtained by executing the second processing each time to obtain the point cloud plane.
The detection method of the flatness of the work area according to claim 3, wherein, based on the normal vector, extracting an effective target point cloud from the target point cloud of the second preset quantity comprises:

Calculate the included angle between the normal vector corresponding to the seed point cloud and the normal vector of each target point cloud in the second preset quantity;

Using the corresponding target point cloud when the included angle is smaller than the preset included angle as the effective target point cloud;

The determining at least one new seed point cloud from the valid target point cloud based on the curvature includes:

When the curvature of the target point cloud in the effective target point cloud is smaller than the preset curvature, the corresponding target point cloud is used as the new seed point cloud.
The method for detecting the flatness of the work area according to any one of claims 1-4, wherein the detection of the flatness of the work area based on the rendering result includes:

Detect whether the rendering result includes an unrendered area;

When it is determined that the unrendered area is included, it is determined that the flatness of the working area corresponding to the unrendered area is unqualified.
According to the detection method of the flatness of the work area according to any one of claims 1-4, it is characterized in that before the acquisition of the target point cloud corresponding to the work area and the target image, it also includes:

Obtain the original point cloud set and original image obtained by the detection unit;

Obtaining the preset scope of the operation area;

The target point cloud set is extracted from the original point cloud set, and the target image is extracted from the original image based on the range of the working area.
A detection device for the flatness of a working area, characterized in that it comprises:

An acquisition module, configured to acquire target point cloud sets and target images corresponding to the operation area;

A determination module, configured to determine a determination parameter corresponding to each target point cloud in the target point cloud set, where the determination parameter is used to indicate the flatness of the working area;

A fitting module, configured to perform a plane fitting operation on the target point cloud based on the determination parameters to obtain a point cloud plane;

A rendering module, configured to render the target point cloud in the point cloud plane based on the target image and a preset conversion relationship to obtain a rendering result, the conversion relationship being between the target point cloud and the target image Correspondence between;

A detection module, configured to detect the flatness of the operation area based on the rendering result.
An electronic device, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein the processor implements the program according to claims 1 to 6 when executing the program. The step of any one of the methods for detecting the flatness of the work area.
A non-transitory computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the method for detecting the flatness of the work area according to any one of claims 1 to 6 is implemented A step of.
A computer program product, comprising a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method for detecting the flatness of the work area according to any one of claims 1-6 are realized.