CN114004873A - Method, device, equipment, medium and product for detecting flatness of operation area - Google Patents
Method, device, equipment, medium and product for detecting flatness of operation area Download PDFInfo
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Abstract
The embodiment of the invention provides a method, a device, equipment, a medium and a product for detecting the flatness of an operation area, wherein the method comprises the following steps: acquiring a target point cloud set and a target image corresponding to a working area; determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameters are used for indicating the flatness of the operation area; performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image; and detecting the flatness of the working area based on the rendering result. The invention is used for solving the defects of high cost, low efficiency and long time consumption caused by manually judging the operation effect of the operation machine in the prior art.
Description
Technical Field
The invention relates to the technical field of earthwork operation, in particular to a method, a device, equipment, a medium and a product for detecting the flatness of an operation area.
Background
At present, the intelligent technology and the unmanned technology are applied to the working machines such as excavators, loaders and road rollers more and more widely. Various auxiliary functions are provided in the work machine to improve the work efficiency of the work machine and optimize the work accuracy.
At present, when the working machine works, the judgment of the working effect is mostly finished manually, and the quality of the working effect is judged by manual measurement. However, the manual work of the working machine has many problems such as an increase in labor cost, a decrease in overall working efficiency, and an increase in work time.
Therefore, how to improve the efficiency of determining the working effect of the working machine is a problem to be solved in the industry.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment, a medium and a product for detecting the flatness of an operation area, which are used for solving the defects of high cost, low efficiency and long time consumption caused by manually judging the operation effect of an operation machine in the prior art and realizing the rapid and accurate judgment of the operation effect of the operation machine.
The embodiment of the invention provides a method for detecting the flatness of an operation area, which comprises the following steps:
acquiring a target point cloud set and a target image corresponding to a working area;
determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameter is used for indicating the flatness of the working area;
performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image;
and detecting the flatness of the operation area based on the rendering result.
According to the method for detecting the flatness of the working area, the judgment parameters comprise: normal vectors and curvatures;
the determining the judgment parameters corresponding to each target point cloud in the target point cloud set comprises the following steps:
performing the following first process on each target point cloud:
acquiring a first preset number of target point clouds from an adjacent area by taking the target point clouds as a center to obtain a local point cloud plane; and calculating a normal vector and a curvature corresponding to the target point cloud based on the local point cloud plane.
According to the method for detecting the flatness of the working area, which is provided by the embodiment of the invention, the plane fitting operation is performed on the target point cloud based on the judgment parameters to obtain a point cloud plane, and the method comprises the following steps:
selecting any one of the target point clouds from the target point cloud set as a seed point cloud;
based on the seed point cloud, performing the following second processing procedure:
acquiring a second preset number of target point clouds from an adjacent area by taking the seed point cloud as a center; extracting effective target point clouds from the second preset number of target point clouds based on the normal vector; determining at least one new seed point cloud from the valid target point clouds based on the curvature;
repeatedly executing the second processing process until each target point cloud in the target point cloud set is judged to be extracted as the effective target point cloud;
and performing plane fitting operation on the effective target point cloud obtained by executing the second processing process each time to obtain the point cloud plane.
According to an embodiment of the present invention, the method for detecting the flatness of the working area, extracting effective target point clouds from the second preset number of target point clouds based on the normal vector, includes:
calculating included angles between normal vectors corresponding to the seed point clouds and normal vectors of each target point cloud in the second preset number respectively;
taking the corresponding target point cloud when the included angle is smaller than a preset included angle as the effective target point cloud;
the determining at least one new seed point cloud from the valid target point clouds based on the curvature comprises:
and when the curvature of the target point cloud in the effective target point cloud is smaller than the preset curvature, taking the corresponding target point cloud as the new seed point cloud.
According to an embodiment of the present invention, the method for detecting the flatness of the work area based on the rendering result includes:
detecting whether an area which is not rendered is included in the rendering result;
when the area which is not rendered is determined to be included, determining that the flatness of the working area corresponding to the area which is not rendered is unqualified.
According to the method for detecting the flatness of the working area, before the target point cloud set and the target image corresponding to the working area are obtained, the method further comprises the following steps:
acquiring an original point cloud set and an original image obtained by a detection unit;
acquiring a preset range of the operation area;
extracting the target point cloud set from the original point cloud set and extracting the target image from the original image based on the extent of the work area.
The embodiment of the invention provides a detection device for the flatness of an operation area, which comprises:
the acquisition module is used for acquiring a target point cloud set and a target image corresponding to the operation area;
the determining module is used for determining a judgment parameter corresponding to each target point cloud in the target point cloud set, and the judgment parameter is used for indicating the flatness of the working area;
the fitting module is used for carrying out plane fitting operation on the target point cloud based on the judgment parameters to obtain a point cloud plane;
the rendering module is used for rendering the target point cloud in the point cloud plane based on the target image and a preset conversion relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image;
and the detection module is used for detecting the flatness of the operation area based on the rendering result.
The embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements any one of the steps of the method for detecting the flatness of the working area when executing the program.
An embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for detecting the flatness of the working area according to any one of the above methods.
An embodiment of the present invention further provides a computer program product, which includes a computer program, and is characterized in that the computer program, when executed by a processor, implements the steps of any one of the above methods for detecting the flatness of the working area.
According to the method, the device, the equipment, the medium and the product for detecting the flatness of the operation area, the target point cloud set and the target image corresponding to the operation area are obtained; determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameter is used for indicating the flatness of the operation area; performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image; based on the rendering result, the flatness of the operation area is detected, the flatness of the operation area can be detected directly according to the target point cloud set and the target image corresponding to the operation area, namely the operation effect, the defects of high cost, low efficiency and long consumed time caused by manual judgment of the operation effect of the operation machine in the prior art are overcome, the flatness of the operation area of the operation machine is judged quickly and accurately, the labor cost is effectively saved, the operation flatness detection efficiency is improved, and the user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for detecting flatness of an operation area according to an embodiment of the present invention;
FIG. 2 is a second schematic flowchart of a method for detecting the flatness of an operation area according to an embodiment of the present invention;
fig. 3 is a third schematic flow chart of a method for detecting the flatness of an operation area according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an apparatus for detecting flatness of an operating area according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for detecting the flatness of the working area according to the embodiment of the present invention is described below with reference to fig. 1 to 3.
The embodiment of the invention provides a method for detecting the flatness of a working area, which can be applied to working machines such as an excavator, a loader and a road roller and can also be applied to a server. The method is described below by way of example in the case of being applied to an excavator, but the method is described by way of example only and is not intended to limit the scope of the present invention. The other descriptions in the embodiments of the present invention are also for illustration purposes, and are not intended to limit the scope of the present invention. The specific implementation of the method is shown in fig. 1:
In a specific embodiment, an original point cloud set and an original image obtained by a detection unit installed on an excavator are acquired, and a range of a working area preset by a user is acquired; and extracting a target point cloud set from the original point cloud set and extracting a target image from the original image based on the range of the operation area.
Specifically, the detecting element includes lidar and camera, and lidar includes: solid state lidar, millimeter wave radar, ultrasonic radar, etc., and cameras include monocular cameras, two-sided cameras, etc. The laser radar is used for acquiring target point cloud, and the camera is used for acquiring a target image.
However, in the present invention, it is not necessary to detect the flatness of all the lidar coverage areas and the camera coverage area, and only the operation area in which the user is interested needs to be detected, so that the range of the operation area needs to be manually preset, and only the flatness of the preset operation area needs to be detected. See in particular fig. 2.
Specifically, the user needs to set a determination parameter for indicating the flatness of the work area, while setting the range of the work area.
In addition, after the laser radar and the camera are installed on the excavator, joint calibration needs to be performed to determine a conversion relationship between a point cloud coordinate system and a camera coordinate system, that is, a conversion relationship from point cloud coordinates to pixel coordinates, that is, a corresponding relationship between a target point cloud and a target image.
Wherein the decision parameters include: normal vectors and curvatures.
In one embodiment, the first processing procedure is performed on each target point cloud to determine the corresponding decision parameter for each target point cloud. The first treatment process specifically comprises the following steps: taking the target point cloud as a center, acquiring a first preset number of target point clouds from an adjacent area of the target point cloud to obtain a local point cloud plane; and calculating a normal vector and a curvature corresponding to the target point cloud based on the local point cloud plane.
And 103, performing plane fitting operation on the target point cloud based on the judgment parameters to obtain a point cloud plane.
Specifically, the method adopts a mode of expanding the communicated areas of adjacent points to obtain a final point cloud plane.
In a specific embodiment, the implementation process of the point cloud plane is specifically as shown in fig. 3:
In the following, a complete point cloud plane forming process is specifically described:
first, any one of the target point clouds is selected from the target point cloud set as an initial seed point cloud, and the corresponding target point cloud with the smallest curvature may be selected as the seed point cloud.
Thirdly, taking the initial seed point cloud as a center, and acquiring a second preset number of target point clouds from the adjacent area of the initial seed point cloud; and extracting effective target point clouds from the second preset number of target point clouds based on the normal vector, and performing plane fitting operation on the effective target point clouds and the initial seed point clouds to obtain an initial point cloud plane.
And finally, determining at least one new seed point cloud from the effective target point clouds based on the curvature, and taking the new seed point cloud as an initial seed point cloud.
In one embodiment, 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 is calculated, and the corresponding target point cloud when the included angle is smaller than the preset included angle is used as the effective target point cloud.
In one 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.
And step 304, performing plane fitting operation on the effective target point cloud obtained by executing the second processing process each time to obtain a point cloud plane.
Specifically, the effective target point cloud obtained by executing the second processing process and the target point cloud in the last initial point cloud plane are subjected to plane fitting operation to obtain a new initial point cloud plane, the new initial point cloud plane is used as the initial point cloud plane until whether each target point cloud in the target point cloud set is judged to be extracted as the effective target point cloud, and the new initial point cloud plane is used as the point cloud plane.
And 104, rendering the target point cloud in the point cloud plane based on the target image and a preset conversion relation to obtain a rendering result.
Specifically, determining an RGB value corresponding to each pixel in the target image, determining a target point cloud corresponding to each pixel based on the conversion relationship, and rendering a color for each target point cloud based on the RGB value of the pixel after the determination is completed, thereby obtaining a rendering result.
The rendering result may be a rendered three-dimensional perspective view or a rendered two-dimensional image.
And 105, detecting the flatness of the operation area based on the rendering result.
In one embodiment, whether an area which is not rendered is included in the rendering result is detected, when the area which is not rendered is determined to be included, the flatness of the operation area corresponding to the area which is not rendered is determined to be unqualified, and when the area which is not rendered is determined to be not included in the rendering result, the flatness of the whole operation area is determined to be qualified.
Specifically, for example, when the rendering result is a rendered three-dimensional stereo image, whether an image area which is not rendered is included in the rendered three-dimensional stereo image is detected, when the image area which is not rendered is determined to be included, the flatness of a work area corresponding to the image area which is not rendered is determined to be unqualified, and when the image area which is not rendered is determined to be not included, the flatness of the whole work area is determined to be qualified.
For another example, when the rendering result is a rendered two-dimensional image, whether an image area which is not rendered is included in the rendered two-dimensional image is detected, when the image area which is not rendered is determined to be included, the flatness of a work area corresponding to the image area which is not rendered is determined to be unqualified, and when the image area which is not rendered is determined to be not included, the flatness of the whole work area is determined to be qualified.
Specifically, the RGB values of the pixels in the target image are used to render and dye 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 the non-rendered area. And the preset color is the color corresponding to the actual operation area.
For example, when the rendering result is a rendered three-dimensional perspective view, a region of the three-dimensional perspective view, the color of which is a preset color, is a rendered region, and a region of the three-dimensional perspective view, the color of which is not the preset color, is an unrendered region. For another example, when the rendering result is a rendered two-dimensional image, a region in the two-dimensional image, the color of which is a preset color, is a rendered region, and a region in the two-dimensional image, the color of which is not the preset color, is an unrendered region.
Specifically, the RGB values of the pixels in the target image are used to render and dye each target point cloud, that is, the area with colors in the rendering result is the rendered area, and the area without colors is the area without colors.
For example, when the rendering result is a rendered three-dimensional perspective view, a region in the three-dimensional perspective view where a color exists is a rendered region, and a region in the three-dimensional perspective view where no color exists is an unrendered region. For example, when the rendering result is a rendered two-dimensional image, a region in the two-dimensional image where a color exists is a rendered region, and a region in the two-dimensional image where a color does not exist is an unrendered region.
In addition, after the smoothness of the operation area corresponding to the non-rendered image area is determined to be unqualified, the actual position of the unqualified position of the image area of the manipulator in the operation area can be prompted in a voice or character mode, the manipulator is reminded to carry out operation repair on the unqualified position, the labor cost is effectively saved, and the user experience is improved.
According to the method, the device, the equipment, the medium and the product for detecting the flatness of the operation area, the target point cloud set and the target image corresponding to the operation area are obtained; determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameter is used for indicating the flatness of the operation area; performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image; based on the rendering result, the flatness of the operation area is detected, the flatness of the operation area can be detected directly according to the target point cloud set and the target image corresponding to the operation area, namely the operation effect, the defects of high cost, low efficiency and long consumed time caused by manual judgment of the operation effect of the operation machine in the prior art are overcome, the flatness of the operation area of the operation machine is judged quickly and accurately, the labor cost is effectively saved, the operation flatness detection efficiency is improved, and the user experience is improved.
The following describes the device for detecting the flatness of the working area according to the embodiment of the present invention, and the device for detecting the flatness of the working area described below and the method for detecting the flatness of the working area described above may be referred to correspondingly, and repeated details are not repeated, and refer to fig. 4 specifically.
An obtaining module 401, configured to obtain a target point cloud set and a target image corresponding to a work area;
a determining 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;
a fitting module 403, configured to perform plane fitting operation on the target point cloud based on the determination parameter to obtain a point cloud plane;
a rendering module 404, configured to render a target point cloud in a point cloud plane based on a target image and a preset conversion relationship, to obtain a rendering result, where the conversion relationship is a corresponding relationship between the target point cloud and the target image;
and a detection module 405, configured to detect the flatness of the work area based on the rendering result.
In one embodiment, the decision parameters include: normal vectors and curvatures; the determining module 402 is specifically configured to perform the following first processing procedure on each target point cloud:
acquiring a first preset number of target point clouds from an adjacent area by taking the target point clouds as a center to obtain a local point cloud plane; and calculating a normal vector and a curvature corresponding to the target point cloud based on the local point cloud plane.
In a specific embodiment, the fitting module 403 is specifically configured to select any one of the target point clouds from the target point cloud set as a seed point cloud; based on the seed point cloud, performing the following second processing procedure: acquiring a second preset number of target point clouds from an adjacent area by taking the seed point cloud as a center; extracting effective target point clouds from a second preset number of target point clouds based on the normal vector; determining at least one new seed point cloud from the valid target point clouds based on the curvature; repeatedly executing the second processing process until each target point cloud in the target point cloud set is judged whether to be extracted as the effective target point cloud; and performing plane fitting operation on the effective target point cloud obtained by executing the second processing process each time to obtain a point cloud plane.
In a specific embodiment, the fitting module 403 is specifically configured to calculate an included angle between a normal vector corresponding to the seed point cloud and a normal vector of each target point cloud in the second preset number; taking the corresponding target point cloud when the included angle is smaller than the preset included angle as an effective target point cloud; and when the curvature of the target point cloud in the effective target point cloud is smaller than the preset curvature, taking the corresponding target point cloud as a new seed point cloud.
In one embodiment, the detecting module 405 is specifically configured to detect whether an area not rendered is included in the rendering result; and when the regions which are not rendered are determined to be included, determining that the flatness of the work regions corresponding to the regions which are not rendered is unqualified.
In a specific embodiment, the obtaining module 401 is further configured to obtain an original point cloud set and an original image obtained by the detecting unit; acquiring a preset range of an operation area; and extracting a target point cloud set from the original point cloud set and extracting a target image from the original image based on the range of the operation area.
Fig. 5 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 5: 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 are configured to communicate with each other via the communication bus 504. The processor 501 may call logic instructions in the memory 503 to perform a method for detecting the flatness of a working area, the method comprising: acquiring a target point cloud set and a target image corresponding to a working area; determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameters are used for indicating the flatness of the operation area; performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image; and detecting the flatness of the working area based on the rendering result.
In addition, the logic instructions in the memory 503 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which when executed by a computer, enable the computer to perform the method for detecting the flatness of a work area provided by the above methods, the method comprising: acquiring a target point cloud set and a target image corresponding to a working area; determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameters are used for indicating the flatness of the operation area; performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image; and detecting the flatness of the working area based on the rendering result.
In yet another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to perform the above-mentioned methods for detecting flatness of a work area, the method comprising: acquiring a target point cloud set and a target image corresponding to a working area; determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameters are used for indicating the flatness of the operation area; performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image; and detecting the flatness of the working area based on the rendering result.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for detecting the flatness of a working area is characterized by comprising the following steps:
acquiring a target point cloud set and a target image corresponding to a working area;
determining a judgment parameter corresponding to each target point cloud in the target point cloud set, wherein the judgment parameter is used for indicating the flatness of the working area;
performing plane fitting operation on the target point cloud based on the judgment parameters 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 relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image;
and detecting the flatness of the operation area based on the rendering result.
2. The method for detecting the flatness of a work area according to claim 1, wherein the determination parameters include: normal vectors and curvatures;
the determining the judgment parameters corresponding to each target point cloud in the target point cloud set comprises the following steps:
performing the following first process on each target point cloud:
acquiring a first preset number of target point clouds from an adjacent area by taking the target point clouds as a center to obtain a local point cloud plane; and calculating a normal vector and a curvature corresponding to the target point cloud based on the local point cloud plane.
3. The method for detecting the flatness of the working area according to claim 2, wherein the performing a plane fitting operation on the target point cloud based on the determination parameter to obtain a point cloud plane comprises:
selecting any one of the target point clouds from the target point cloud set as a seed point cloud;
based on the seed point cloud, performing the following second processing procedure:
acquiring a second preset number of target point clouds from an adjacent area by taking the seed point cloud as a center; extracting effective target point clouds from the second preset number of target point clouds based on the normal vector; determining at least one new seed point cloud from the valid target point clouds based on the curvature;
repeatedly executing the second processing process until each target point cloud in the target point cloud set is judged to be extracted as the effective target point cloud;
and performing plane fitting operation on the effective target point cloud obtained by executing the second processing process each time to obtain the point cloud plane.
4. The method for detecting the flatness of the working area according to claim 3, wherein the extracting effective target point clouds from the second preset number of target point clouds based on the normal vectors comprises:
calculating included angles between normal vectors corresponding to the seed point clouds and normal vectors of each target point cloud in the second preset number respectively;
taking the corresponding target point cloud when the included angle is smaller than a preset included angle as the effective target point cloud;
the determining at least one new seed point cloud from the valid target point clouds based on the curvature comprises:
and when the curvature of the target point cloud in the effective target point cloud is smaller than the preset curvature, taking the corresponding target point cloud as the new seed point cloud.
5. The method for detecting the flatness of the work area according to any one of claims 1 to 4, wherein the detecting the flatness of the work area based on the rendering result includes:
detecting whether an area which is not rendered is included in the rendering result;
when the area which is not rendered is determined to be included, determining that the flatness of the working area corresponding to the area which is not rendered is unqualified.
6. The method for detecting the flatness of the working area according to any one of claims 1 to 4, wherein before the obtaining of the target point cloud set and the target image corresponding to the working area, the method further comprises:
acquiring an original point cloud set and an original image obtained by a detection unit;
acquiring a preset range of the operation area;
extracting the target point cloud set from the original point cloud set and extracting the target image from the original image based on the extent of the work area.
7. A detection device for flatness of a working area is characterized by comprising:
the acquisition module is used for acquiring a target point cloud set and a target image corresponding to the operation area;
the determining module is used for determining a judgment parameter corresponding to each target point cloud in the target point cloud set, and the judgment parameter is used for indicating the flatness of the working area;
the fitting module is used for carrying out plane fitting operation on the target point cloud based on the judgment parameters to obtain a point cloud plane;
the rendering module is used for rendering the target point cloud in the point cloud plane based on the target image and a preset conversion relation to obtain a rendering result, wherein the conversion relation is a corresponding relation between the target point cloud and the target image;
and the detection module is used for detecting the flatness of the operation area based on the rendering result.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for detecting the flatness of a work area according to any one of claims 1 to 6 when executing the program.
9. A non-transitory computer-readable storage medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the steps of the method for detecting the flatness of a work area according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, wherein the computer program when executed by a processor implements the steps of the method for detecting the flatness of a work area according to any of claims 1-6.
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| CN202111138696.0A CN114004873A (en) | 2021-09-27 | 2021-09-27 | Method, device, equipment, medium and product for detecting flatness of operation area |
| PCT/CN2022/073796 WO2023045195A1 (en) | 2021-09-27 | 2022-01-25 | Method and apparatus for detecting flatness of working area, device, medium and product |
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| CN202111138696.0A CN114004873A (en) | 2021-09-27 | 2021-09-27 | Method, device, equipment, medium and product for detecting flatness of operation area |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117387531A (en) * | 2023-12-04 | 2024-01-12 | 中铁四局集团第二工程有限公司 | Tunnel primary support flatness detection method and system thereof |
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| US9508186B2 (en) * | 2013-11-07 | 2016-11-29 | Autodesk, Inc. | Pre-segment point cloud data to run real-time shape extraction faster |
| CN110033447B (en) * | 2019-04-12 | 2022-11-08 | 东北大学 | High-speed rail heavy rail surface defect detection method based on point cloud method |
| CN113052193B (en) * | 2019-12-27 | 2023-07-11 | 沈阳新松机器人自动化股份有限公司 | Robot repositioning method and system |
| CN112258474A (en) * | 2020-10-22 | 2021-01-22 | 深圳集智数字科技有限公司 | Wall surface anomaly detection method and device |
| CN112937444B (en) * | 2021-03-15 | 2023-12-29 | 上海三一重机股份有限公司 | Auxiliary image generation method and device for working machine and working machine |
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| CN117387531A (en) * | 2023-12-04 | 2024-01-12 | 中铁四局集团第二工程有限公司 | Tunnel primary support flatness detection method and system thereof |
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