Method and device for spraying a building wall based on a three-dimensional point cloud

Abstract

Embodiments of the present disclosure disclose a three-dimensional point cloud-based building wall spraying method and device. A specific embodiment of the method includes: collecting a three-dimensional target position coordinate set of a building to be sprayed and a building site position coordinate set corresponding to the three-dimensional target position coordinate set; performing a similarity transformation on the building site position coordinate set and the three-dimensional target position coordinate set to generate a transformed building site position coordinate set; generating a building contour fused point cloud according to the transformed building site position coordinate set; performing defect repair on the building contour fused point cloud to generate a defect repair result set; and controlling a UAV spraying device to perform a spraying operation on a set of building wall surfaces to be sprayed. The embodiment shortens the time consumed by building spraying, and improves the quality and integrity of building wall spraying.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a building wall spraying method and device based on three-dimensional point cloud. BACKGROUND

[0002] The building wall spraying based on three-dimensional point cloud is a technology for spraying a building wall. At present, when spraying a building wall, the commonly used way is to manually spray the building wall by workers. For example, workers manually spray the wall using a spray gun.

[0003] However, when spraying a building wall by using the above way, the following technical problems often exist:

[0004] Manually spraying a building wall by workers is difficult to adapt to complex building structures, resulting in a long time consumed for building spraying, and uneven spraying thickness caused by manual spraying, which makes the quality of building wall spraying poor. Since the defect positions of the wall are not fixed, manual intervention may cause the defects to be unable to be repaired, and the integrity of the wall is low. SUMMARY

[0005] The summary part of the present disclosure is used to introduce the concepts in a brief form, which will be described in detail in the specific embodiments part. The summary part of the present disclosure is not intended to identify the key features or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0006] Some embodiments of the present disclosure propose a building wall spraying method and device based on three-dimensional point cloud to solve the technical problems mentioned in the background part.

[0007] In a first aspect, some embodiments of the present disclosure provide a three-dimensional point cloud-based building wall spraying method, which comprises: collecting a three-dimensional target position coordinate set of a building to be sprayed and a building site position coordinate set corresponding to the three-dimensional target position coordinate set, wherein the three-dimensional target position coordinate set is located on a concrete ground outside the building to be sprayed, the three-dimensional target position coordinates in the three-dimensional target position coordinate set are connected to each other to form a triangle, and the building site position coordinates in the building site position coordinate set are real position coordinates of the building to be sprayed in a three-dimensional scene; performing a similarity transformation on the building site position coordinate set and the three-dimensional target position coordinate set to generate a transformed building site position coordinate set; generating a building contour fusion point cloud according to the transformed building site position coordinate set; performing defect repair on the building contour fusion point cloud to generate a defect repair result set; in response to determining that a defect repair result in the defect repair result set meets a preset defect repair condition, performing wall division on the building to be sprayed corresponding to the defect repair result set to generate a building wall set to be sprayed; and controlling a UAV spraying device to perform a spraying operation on the building wall set to be sprayed.

[0008] In a second aspect, some embodiments of the present disclosure provide a three-dimensional point cloud-based building wall spraying device, which comprises: a processing unit configured to collect a three-dimensional target position coordinate set of a building to be sprayed and a building site position coordinate set corresponding to the three-dimensional target position coordinate set, wherein the three-dimensional target position coordinate set is located on a concrete ground outside the building to be sprayed, the three-dimensional target position coordinates in the three-dimensional target position coordinate set are connected to each other to form a triangle, and the building site position coordinates in the building site position coordinate set are real position coordinates of the building to be sprayed in a three-dimensional scene; a transformation unit configured to perform a similarity transformation on the building site position coordinate set and the three-dimensional target position coordinate set to generate a transformed building site position coordinate set; a generation unit configured to generate a building contour fusion point cloud according to the transformed building site position coordinate set; a repair unit configured to perform defect repair on the building contour fusion point cloud to generate a defect repair result set; a division unit configured to, in response to determining that a defect repair result in the defect repair result set meets a preset defect repair condition, perform wall division on the building to be sprayed corresponding to the defect repair result set to generate a building wall set to be sprayed; and a control unit configured to control a UAV spraying device to perform a spraying operation on the building wall set to be sprayed.

[0009] In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having stored thereon one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the method described in any implementation manner of the first aspect.

[0010] In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having stored thereon a computer program, wherein the program, when executed by a processor, implements the method described in any implementation manner of the first aspect.

[0011] The above various embodiments of the present disclosure have the following beneficial effects: through the three-dimensional point cloud-based building wall spraying method of some embodiments of the present disclosure, the time consumed by building spraying is shortened, and the quality and integrity of building wall spraying are improved. Specifically, the reason why the time consumed by building spraying is long and the quality of building wall spraying is poor is that the building wall is manually sprayed, which is difficult to adapt to complex building structures, resulting in a long time consumed by building spraying, and manual spraying is prone to cause uneven spraying thickness, resulting in poor quality of building wall spraying. Since the defect position of the wall is not fixed, manual intervention may cause the defect to be unable to be repaired, and the integrity of the wall is low. Based on this, the three-dimensional point cloud-based building wall spraying method of some embodiments of the present disclosure first collects a three-dimensional target position coordinate set for a building to be sprayed and a building site position coordinate set corresponding to the three-dimensional target position coordinate set, wherein the three-dimensional target position coordinate set is located on a concrete floor outside the building to be sprayed, and the graph surrounded by the connection lines between each three-dimensional target position coordinate in the three-dimensional target position coordinate set is a triangle, and the building site position coordinate in the building site position coordinate set is the real position coordinate of the building to be sprayed in a three-dimensional scene. Thus, two coordinate systems can be established, and the coordinates measured by the total station and the real coordinates can be obtained for subsequent operations. Then, the building site position coordinate set and the three-dimensional target position coordinate set are subjected to similarity transformation to generate a transformed building site position coordinate set. Thus, the coordinates of the two coordinate systems can be aligned to facilitate spraying by the unmanned aerial vehicle spraying device. Then, according to the transformed building site position coordinate set, a building contour fusion point cloud is generated. Thus, the complex building structure can be adapted, and the building contour fusion point cloud can be obtained without manual operation, thereby shortening the time consumed by building spraying. Next, the building contour fusion point cloud is subjected to defect repair to generate a defect repair result set. Thus, the area containing defects in the contour of the building can be repaired, and the quality and integrity of building wall spraying are improved. Then, in response to determining that the defect repair result in the defect repair result set meets a preset defect repair condition, the building to be sprayed corresponding to the defect repair result set is subjected to wall division to generate a building wall set to be sprayed. Thus, the wall can be divided and sprayed in blocks to improve the quality of building wall spraying. Finally, the unmanned aerial vehicle spraying device is controlled to perform spraying operation on the building wall set to be sprayed. Thus, the time consumed by building spraying is shortened, and the quality and integrity of building wall spraying are improved. BRIEF DESCRIPTION OF DRAWINGS

[0012] The above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings. In the drawings like or common elements and characteristics are denoted by the same reference numerals throughout the drawings. It is to be understood that the drawings are schematic, and elements and features are not necessarily drawn to scale.

[0013] Figure 1 is a schematic diagram of one application scenario of the three-dimensional point cloud-based building wall spraying method of some embodiments of the present disclosure;

[0014] Figure 2 is a flowchart of the three-dimensional point cloud-based building wall spraying method according to some embodiments of the present disclosure;

[0015] Figure 3 is a structural schematic diagram of some embodiments of the three-dimensional point cloud-based building wall spraying device according to the present disclosure;

[0016] Figure 4 is a structural schematic diagram of an electronic device suitable for implementing some embodiments of the present disclosure;

[0017] Figure 5 is an abnormal film thickness boundary point cloud diagram of some embodiments of the three-dimensional point cloud-based building wall spraying device according to the present disclosure. DETAILED DESCRIPTION

[0018] Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms, and should not be interpreted as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes, and are not intended to limit the scope of protection of the present disclosure.

[0019] In addition, it should be noted that only the parts related to the present application are shown in the drawings for ease of description. The embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0020] It should be noted that the terms "first", "second", etc. mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not intended to limit the order or interdependence of the functions performed by these devices, modules or units.

[0021] It should be noted that the adjectives "one" and "multiple" mentioned in the present disclosure are illustrative and not limiting, and those skilled in the art should understand that, unless otherwise explicitly stated in the context, it should be understood as "one or more".

[0022] The names of the messages or information exchanged between the devices in the embodiments of the present disclosure are only for illustrative purposes, and are not intended to limit the scope of the messages or information.

[0023] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0024] Figure 1 is a schematic diagram of one application scenario of the three-dimensional point cloud-based building wall spraying method of some embodiments of the present disclosure.

[0025] In Figure 1 application scenario, first, the three-dimensional target position coordinate set 104 for the to-be-sprayed building 101 is collected by the total station 106, and the three-dimensional target position coordinate set 104 is shown as A coordinate, B coordinate and C coordinate in the figure. The building site position coordinate set 105 corresponding to the three-dimensional target position coordinate set 104 is collected by the three-dimensional laser scanner 107, and the building site position coordinate set 105 is shown as P coordinate, Q coordinate and R coordinate in the figure. Among them, the above-mentioned three-dimensional target position coordinate set 104 is located on the concrete ground outside the above-mentioned to-be-sprayed building 101, the figure surrounded by the mutual connection lines between each three-dimensional target position coordinate in the above-mentioned three-dimensional target position coordinate set 104 is a triangle, and the building site position coordinate in the above-mentioned building site position coordinate set 105 is the real position coordinate of the above-mentioned to-be-sprayed building in the three-dimensional scene. The coordinate system 102 is the real coordinate system of the to-be-sprayed building 101. The coordinate system 102 is shown as X axis, Y axis and Z axis in the figure. The coordinate system 103 is the reference coordinate system of the total station 106. The coordinate system 103 is shown as X1 axis, Y1 axis and Z1 axis in the figure. Among them, the direction arrow drawn from the origin of the coordinate system 102 and the origin of the coordinate system 103 represents the relative position between the coordinate system 103 and the coordinate system 102, that is, located on the same horizontal ground and the origins do not coincide.

[0026] With reference to Figure 2 , the flow 200 of some embodiments of the three-dimensional point cloud-based building wall spraying method according to the present disclosure is shown. The three-dimensional point cloud-based building wall spraying method comprises the following steps:

[0027] Step 201, collecting a three-dimensional target position coordinate set for a to-be-sprayed building and a building site position coordinate set corresponding to the three-dimensional target position coordinate set.

[0028] In some embodiments, the execution subject (for example, a computing device) of the three-dimensional point cloud-based building wall spraying method can collect a three-dimensional target position coordinate set for a to-be-sprayed building by a total station (Total Station), and collect a building site position coordinate set corresponding to the three-dimensional target position coordinate set by a three-dimensional laser scanner (3d laser scanner), wherein the above-mentioned three-dimensional target position coordinate set is located on the concrete ground outside the above-mentioned to-be-sprayed building, the figure surrounded by the mutual connection lines between each three-dimensional target position coordinate in the above-mentioned three-dimensional target position coordinate set is a triangle, and the building site position coordinate in the above-mentioned building site position coordinate set is the real position coordinate of the above-mentioned to-be-sprayed building in the three-dimensional scene.

[0029] Here, the aforementioned to-be-sprayed building can refer to a building that has not been sprayed with paint. The aforementioned paint can refer to cement, pigment, and putty. For example, the three-dimensional target position coordinate set can refer to {A(0, 0, 0), B(30.000, 0.000, 0.021), C(0.000, 20.000, 0.015)}. The building site position coordinate set can refer to {P(–0.120, 0.050, 0.000), Q(29.890, 0.050, 0.021), R(–0.120, 20.050, 0.015)}.

[0030] In step 202, a similarity transformation is performed on the aforementioned building site position coordinate set and the aforementioned three-dimensional target position coordinate set to generate a transformed building site position coordinate set.

[0031] In some embodiments, the aforementioned execution subject can perform a similarity transformation on the aforementioned building site position coordinate set and the aforementioned three-dimensional target position coordinate set to generate a transformed building site position coordinate set.

[0032] Here, the aforementioned transformed building site position coordinate set can refer to a transformed building site position coordinate set after aligning the three-dimensional target position coordinate set to the building site position coordinate set. For example, a three-dimensional target position coordinate in the three-dimensional target position coordinate set can refer to (5, 3, 20). After aligning (5, 3, 20) to a building site position coordinate in the building site position coordinate set, it becomes (4.88, 3.05, 20.00).

[0033] As an example, the aforementioned execution subject can perform a similarity transformation on the aforementioned building site position coordinate set and the aforementioned three-dimensional target position coordinate set by the Umeyama algorithm to generate a transformed building site position coordinate set.

[0034] Alternatively, the aforementioned execution subject can perform a similarity transformation on the aforementioned building site position coordinate set and the aforementioned three-dimensional target position coordinate set to generate a transformed building site position coordinate set by the following steps:

[0035] First, data processing is performed on the aforementioned three-dimensional target position coordinate set and the aforementioned building site position coordinate set to generate a parameter data set.

[0036] Here, the parameter dataset can include a scale factor, a translation vector, and a rotation matrix. For example, the scale factor can be referred to as k, and k can be referred to as 1. The translation vector can be referred to as T, and T can be a 3x1 translation vector. T can be ΔX, ΔY, and ΔZ. The rotation matrix can be referred to as R, and R can be a 3x3 rotation matrix. R can be ωX, ωY, and ωZ. The scale factor is used to scale the size of the coordinate set. The translation vector is used to translate the position of the coordinate set. The rotation matrix is used to rotate the direction of the coordinate set. The coordinate set can be a three-dimensional target position coordinate set. It can also be a construction site position coordinate set.

[0037] As an example, the execution subject can perform least squares processing on the three-dimensional target position coordinate set and the construction site position coordinate set to generate the parameter dataset.

[0038] In the process of using the technical solutions to solve the problems mentioned in the background, the following problems often occur:

[0039] The changing environmental factors can cause errors in the measured coordinates, and when generating the parameter dataset, the coordinate transformation accuracy can be reduced due to misalignment of the coordinate system, resulting in poor spraying quality when spraying the building to be sprayed.

[0040] In the face of the above technical problems, the inventors decided to use the following solutions:

[0041] Optionally, the execution subject can perform data processing on the three-dimensional target position coordinate set and the construction site position coordinate set to generate the parameter dataset by the following steps:

[0042] First sub-step, according to the environmental parameter, adjusting the three-dimensional target position coordinate set to generate an adjusted three-dimensional target position coordinate set.

[0043] Here, the environmental parameter can be the temperature. For example, the temperature can be 25 degrees Celsius.

[0044] As an example, the execution subject can first determine the change in the environmental parameter to obtain the changed environmental parameter. For example, the target temperature is 17 degrees Celsius, and the environmental temperature is 25 degrees Celsius, so the changed environmental parameter is 8. Then, determine the thermal expansion coefficient of the building wall. For example, the thermal expansion coefficient can be 1.2x10 -5 For each three-dimensional target position coordinate in the three-dimensional target position coordinate set, determine the adjusted three-dimensional target position coordinate as the three-dimensional target position coordinate x (1 + thermal expansion coefficient x changed environmental parameter) to obtain the adjusted three-dimensional target position coordinate set.

[0045] Second sub-step, determine the centroid coordinates of the adjusted three-dimensional target position coordinate set.

[0046] Here, the centroid coordinate can refer to (10, 6.67, 0.012).

[0047] A third sub-step is to subtract the centroid coordinate from the adjusted three-dimensional target position coordinate set to obtain a de-centroidized three-dimensional target position coordinate set.

[0048] As an example, the execution subject can subtract the centroid coordinate from each adjusted three-dimensional target position coordinate in the adjusted three-dimensional target position coordinate set to generate a de-centroidized three-dimensional target position coordinate, thereby obtaining the de-centroidized three-dimensional target position coordinate set. For example, the de-centroidized three-dimensional target position coordinate set is {(-10, -6.67, -0.012), (19.998, -6.67, 0.009), (-10, 13.33, 0.003)}.

[0049] A fourth sub-step is to perform matrix construction on the de-centroidized three-dimensional target position coordinate set to generate a de-centroidized three-dimensional target matrix.

[0050] As an example, the execution subject can arrange the de-centroidized three-dimensional target position coordinates in the de-centroidized three-dimensional target position coordinate set horizontally to obtain a 3x3 matrix as the de-centroidized three-dimensional target matrix.

[0051] A fifth sub-step is to perform principal direction extraction on the de-centroidized three-dimensional target matrix to generate a principal direction extraction result.

[0052] As an example, the execution subject can perform principal direction extraction on the de-centroidized three-dimensional target matrix by principal component analysis (PCA) to generate the principal direction extraction result.

[0053] A sixth sub-step is to determine an initial rotation matrix according to the principal direction extraction result.

[0054] Here, the initial rotation matrix can refer to an identity matrix.

[0055] As an example, the execution subject can compare the principal direction extraction result with the principal directions of a real coordinate system to obtain a comparison result. Then, in response to determining that the comparison result represents a consistent comparison, the identity matrix is determined as the initial rotation matrix. The real coordinate system is a physical coordinate system in which the building to be sprayed is located.

[0056] A seventh sub-step is to perform least squares optimization on the adjusted three-dimensional target position coordinate set to generate an optimized rotation matrix and a translation vector.

[0057] As an example, the execution subject can use the least square method to arrange each adjusted three-dimensional target position coordinate in the adjusted three-dimensional target position coordinate set horizontally to obtain a coordinate matrix. Then, a covariance matrix determination is performed on the coordinate matrix to obtain a coordinate covariance matrix. Next, a singular value decomposition (SVD) is performed on the coordinate covariance matrix to obtain a decomposition result matrix set. Then, a rotation matrix determination is performed on the decomposition result matrix set to obtain an optimized rotation matrix. Finally, a difference between the centering-free three-dimensional target position coordinate set and a target coordinate in a real coordinate system is determined as a translation vector. For example, the target coordinate can be (-0.120, 0.050, 0.000), (29.880, 0.050, 0.021), and (-0.120, 20.050, 0.015).

[0058] In the eighth sub-step, a scale factor is generated according to the optimized rotation matrix and the translation vector.

[0059] As an example, the execution subject can multiply the optimized rotation matrix and the translation vector by the adjusted three-dimensional target position coordinate set through the least square method to obtain a coordinate variable set. Then, a mean value determination is performed on the coordinate variable set to generate a variable mean value as the scale factor.

[0060] In the ninth sub-step, the optimized rotation matrix, the translation vector, and the scale factor are combined into a parameter data set.

[0061] Here, the parameter data set can be {ΔX=-0.120, ΔY=0.050, ΔZ=0.000, ωX=0, ωY=0, ωZ=0, k=1.000}.

[0062] The above-mentioned related contents in the first to ninth sub-steps are an application point of the present disclosure, which solves the technical problem of "poor spraying quality when spraying the building to be sprayed". Factors that lead to poor spraying quality when spraying the building to be sprayed are often as follows: changing environmental factors can cause errors in the measured coordinates, and when generating the parameter data set, the coordinate transformation accuracy can be reduced due to misalignment of the coordinate system, resulting in poor spraying quality when spraying the building to be sprayed. If the above factors are solved, the spraying quality of the building to be sprayed can be improved. In order to achieve this effect, first, the first sub-step, according to the environmental parameters, the three-dimensional target position coordinate set is adjusted to generate an adjusted three-dimensional target position coordinate set. In this way, environmental factors can be taken into account to avoid errors in the measured coordinates. The second sub-step determines the centroid coordinates of the adjusted three-dimensional target position coordinate set. In this way, the centroid of the three coordinates in the three-dimensional target position coordinate set can be obtained. The third sub-step subtracts the centroid coordinates from the adjusted three-dimensional target position coordinate set to obtain a de-centered three-dimensional target position coordinate set. The fourth sub-step constructs a matrix for the de-centered three-dimensional target position coordinate set to generate a de-centered three-dimensional target matrix. In this way, the coordinates can be aligned through matrix construction, and the coordinate transformation accuracy can be improved. The fifth sub-step extracts the main direction of the de-centered three-dimensional target matrix to generate a main direction extraction result. The sixth sub-step determines the initial rotation matrix according to the main direction extraction result. The seventh sub-step performs least squares optimization on the adjusted three-dimensional target position coordinate set to generate an optimized rotation matrix and a translation vector. The eighth sub-step generates a scale factor according to the optimized rotation matrix and the translation vector. In this way, the parameter data can be obtained. The ninth sub-step combines the optimized rotation matrix, the translation vector and the scale factor into a parameter data set. Therefore, the coordinate system is more accurate, and the spraying quality is improved.

[0063] Secondly, according to the parameter data set, the three-dimensional target position coordinate set is transformed to generate a transformed building site position coordinate set.

[0064] As an example, the execution subject can multiply each three-dimensional target position coordinate in the three-dimensional target position coordinate set and the scale factor, the optimized rotation matrix and the translation vector in the parameter data set to generate a transformed building site position coordinate, and obtain a transformed building site position coordinate set.

[0065] Step 203, generating a building contour fusion point cloud according to the transformed building site position coordinate set.

[0066] In some embodiments, the execution subject can generate a building contour fusion point cloud according to the transformed building site position coordinate set.

[0067] Optionally, the execution subject can generate the building contour fused point cloud from the transformed building site position coordinate set according to the following steps:

[0068] Firstly, the laser device is controlled to collect the building contour point cloud of the building to be painted according to the transformed building site position coordinate set.

[0069] Here, the laser device can be a laser radar. The building contour point cloud can be a three-dimensional point cloud of the building contour obtained by laser scanning.

[0070] As an example, the execution subject can use the laser radar to collect each transformed building site position coordinate in the transformed building site position coordinate set in the building to be painted to obtain the building contour point cloud. For example, the laser radar is used to fly along the outer contour of the building to be painted at a constant speed for two laps to collect the building contour point cloud.

[0071] Secondly, a grid map is generated from the building contour point cloud to obtain a building contour grid map.

[0072] Here, the building contour grid map can be a map in which the contour of the building to be painted is divided into a plurality of identical grids.

[0073] As an example, the execution subject can generate a grid map from the building contour point cloud by a Cartographer algorithm to obtain a building contour grid map.

[0074] Thirdly, in response to determining that the building contour grid map meets a preset contour condition, a camera device is controlled to collect a set of multi-directional building to be painted oblique images.

[0075] Here, the preset contour condition can be a pre-set condition that the building facade has no holes or noise points. The multi-directions can be front, back, left, right, and down. The camera device can be a camera.

[0076] Fourthly, point cloud registration is performed on the building contour point cloud and the corresponding point cloud of the set of building to be painted oblique images to obtain a building contour fused point cloud.

[0077] As an example, the execution subject can perform point cloud alignment on the building contour point cloud and the corresponding point cloud of the set of building to be painted oblique images to obtain an aligned building contour point cloud set. Then, the aligned building contour point clouds in the aligned building contour point cloud set are fused to obtain a building contour fused point cloud.

[0078] Step 204: Defects are repaired on the building contour fused point cloud to generate a set of defect repair results.

[0079] In some embodiments, the execution subject can perform defect repairing on the building contour fused point cloud to generate a defect repairing result set.

[0080] Here, the defect repairing result in the defect repairing result set can refer to the repaired point cloud result.

[0081] Optionally, the execution subject can perform defect repairing on the building contour fused point cloud to generate a defect repairing result set by the following steps:

[0082] Firstly, input the building contour fused point cloud into a defect identification model to obtain a building defect coordinate set.

[0083] Here, the input of the defect identification model is the building contour fused point cloud, and the output is the building defect coordinate set. The defect identification model is used to identify defects in the building contour fused point cloud. The defect identification model is a trained model with the building contour fused point cloud as input and the building defect coordinate set as output. The defect identification model can be used to represent the correspondence between the building contour fused point cloud and the building defect coordinate set. The defect identification model can compare the building contour fused point cloud with multiple groups of pre-set building contour fused point clouds in a pre-set scoring feature relationship table in turn. The pre-set scoring feature relationship table can be created based on analysis of a large number of pre-set building contour fused point clouds. Each group of pre-set building contour fused point cloud corresponds to a pre-set building defect coordinate set. The pre-set building defect coordinate set can be a pre-set building defect coordinate set. The defect identification model can refer to PointNet++ (a deep learning model for processing point cloud data), Real3D-AD, Markov Random Field (Markov Random Field).

[0084] Secondly, generate a defect repairing task job set according to the building defect coordinate set.

[0085] As an example, the execution subject can generate a defect repairing task for each building defect coordinate in the building defect coordinate set to generate a defect repairing task job, and obtain a defect repairing task job set. The repairing task can refer to a task of repairing the building defect coordinate.

[0086] Thirdly, repair each defect repairing task job in the defect repairing task job set to generate a defect repairing result, and obtain a defect repairing result set.

[0087] As an example, the execution subject can control the unmanned aerial vehicle spraying device to spray cement for repairing each defect repairing task job in the defect repairing task job set to generate a defect spraying repairing result, obtain a defect spraying repairing result set as the defect repairing result set.

[0088] In step 205, in response to determining that the defect repair result in the defect repair result set satisfies the preset defect repair condition, the wall surface of the building to be sprayed is divided to generate a building wall surface set to be sprayed.

[0089] In some embodiments, the execution subject can divide the wall surface of the building to be sprayed corresponding to the defect repair result set in response to determining that the defect repair result in the defect repair result set satisfies the preset defect repair condition to generate a building wall surface set to be sprayed.

[0090] Here, the building wall surface to be sprayed in the building wall surface set to be sprayed comprises a unique area and a unique number. For example, the building wall surface to be sprayed in the building wall surface set to be sprayed can be referred to as A area No. 11. The preset defect repair condition can be a pre-set building wall surface without holes or noise.

[0091] As an example, the execution subject can divide the wall surface of the building to be sprayed corresponding to the defect repair result set according to a preset area zone to generate a divided building wall surface set. Wherein the preset area zone is a pre-set area of 3x3. Then, each divided building wall surface in the divided building wall surface set located on the same plane is marked as the same area to obtain a plurality of same area wall surfaces, for example, the wall surface facing east is marked as A area. Then, each divided building wall surface of each same area wall surface in the plurality of same area wall surfaces is numbered to generate a numbered same area wall surface, to obtain a numbered same area wall surface set as a building wall surface set to be sprayed.

[0092] In step 206, the execution subject controls the unmanned aerial vehicle spraying device to perform a spraying operation on the building wall surface set to be sprayed.

[0093] In some embodiments, the execution subject can control the unmanned aerial vehicle spraying device to perform a spraying operation on the building wall surface set to be sprayed.

[0094] Here, the unmanned aerial vehicle spraying device is a device for spraying paint on the building wall surface to be sprayed.

[0095] Optionally, the execution subject can control the unmanned aerial vehicle spraying device to perform a spraying operation on the building wall surface set to be sprayed by the following steps:

[0096] First, for each building wall surface to be sprayed in the building wall surface set to be sprayed, the following operation steps are performed:

[0097] First, a plurality of initial spraying parameter determinations are performed on the building wall surface to be sprayed to generate an initial spraying parameter set.

[0098] Herein, the plurality of initial spraying parameters can include, but are not limited to, at least one of: a spraying flow rate, a spraying speed, a spraying standoff distance. The spraying flow rate can be 2 L / min. The spraying speed can be 20 square meters per minute. The spraying standoff distance can be 20 centimeters.

[0099] In response to determining that the initial spraying parameter set is less than the preset parameter error threshold, the UAV spraying device is controlled to spray the set of building walls to be sprayed according to the initial spraying parameter set.

[0100] Herein, the preset parameter error threshold can be the maximum value of the difference between the preset spraying flow rate of 2.3 L / min, the preset spraying speed of 20.78 square meters per minute, and the preset spraying standoff distance of 20.1 centimeters. For example, the preset parameter error threshold can be 0.8.

[0101] Optionally, after the step of controlling the UAV spraying device to spray the set of building walls to be sprayed according to the initial spraying parameter set in response to determining that the initial spraying parameter set is less than the preset parameter error threshold, the method further comprises:

[0102] Firstly, film thickness detection is performed on the set of sprayed building walls to generate a set of film thickness point clouds.

[0103] As an example, the execution subject can use a laser profilometer to scan the set of sprayed building walls at an interval of 5 cm to obtain the set of film thickness point clouds.

[0104] Secondly, in response to determining that there are film thickness point clouds in the set of film thickness point clouds that exceed a preset film thickness range, at least one film thickness point cloud that exceeds the preset film thickness range is marked as a set of abnormal film thickness point clouds.

[0105] Herein, the preset film thickness range can be a film thickness range in which the preset film thickness is less than 80 microns or greater than 120 microns. The marking can be a fluorescent marking.

[0106] Thirdly, spraying repair is performed on the set of abnormal film thickness point clouds to generate a set of repaired film thickness point clouds.

[0107] As an example, the execution subject can control the UAV spraying device to reduce the spraying flow rate to spray repair each abnormal film thickness point cloud in the set of abnormal film thickness point clouds that is greater than 120 microns, and control the UAV spraying device to increase the spraying flow rate to spray repair each abnormal film thickness point cloud in the set of abnormal film thickness point clouds that is less than 80 microns, to obtain the set of repaired film thickness point clouds.

[0108] Optionally, the execution subject can perform spraying repair on the set of abnormal film thickness point clouds to generate the set of repaired film thickness point clouds by the following steps:

[0109] In the first step, the abnormal film thickness boundary point cloud set is extracted to generate an abnormal film thickness boundary point cloud set.

[0110] Here, the abnormal film thickness boundary point cloud in the abnormal film thickness boundary point cloud set can refer to a boundary point cloud with a film thickness less than 80 microns or a film thickness greater than 120 microns.

[0111] As an example, the execution subject can extract the abnormal film thickness boundary of the abnormal film thickness point cloud set by an edge detection operator (canny operator) to generate an abnormal film thickness boundary point cloud set.

[0112] In the second step, the geometric features of the abnormal film thickness boundary point cloud set are determined to obtain an abnormal film thickness geometric feature group set.

[0113] Here, the geometric features can include area features and perimeter features.

[0114] Optionally, the execution subject can determine the geometric features of the abnormal film thickness boundary point cloud set to obtain an abnormal film thickness geometric feature group set by the following steps:

[0115] In the first sub-step, the graph structure of each abnormal film thickness boundary point cloud in the abnormal film thickness boundary point cloud set is generated to obtain an abnormal film thickness boundary point cloud graph. The nodes in the abnormal film thickness boundary point cloud graph represent the abnormal film thickness boundary point cloud, and the edges in the abnormal film thickness boundary point cloud graph represent the mutual connection between the nodes.

[0116] As shown in the abnormal film thickness boundary point cloud set {a, b, c, d, e, f, g} on the wall, each abnormal film thickness boundary point cloud is taken as a node, and the nodes are connected to each other to obtain an abnormal film thickness boundary point cloud graph. Figure 5

[0117] As an example, the execution subject can take each abnormal film thickness boundary point cloud in the abnormal film thickness boundary point cloud set as a node, and then connect each two nodes in the nodes to generate connected nodes to obtain a connected node set as an abnormal film thickness boundary point cloud graph.

[0118] In the second sub-step, the spraying path set is generated by traversing the abnormal film thickness boundary point cloud graph.

[0119] As an example, the execution subject can perform a depth traversal on the spraying path in the abnormal film thickness boundary point cloud graph to generate a spraying path set.

[0120] ​A third sub-step is to determine the geometric features of each of the abnormal film thickness boundary point clouds in the abnormal film thickness boundary point cloud set to generate an abnormal film thickness geometric feature group, thereby obtaining an abnormal film thickness geometric feature group set.

[0121] A third step is to generate a sprayed building wall surface set according to the abnormal film thickness geometric feature group set.

[0122] Optionally, the execution subject can generate a sprayed building wall surface set according to the abnormal film thickness geometric feature group set by the following steps:

[0123] A first sub-step is to classify the abnormal film thickness boundary point cloud set according to the abnormal film thickness geometric feature group set to generate an abnormal film thickness boundary point cloud level group set.

[0124] Here, the abnormal film thickness boundary point cloud level group in the abnormal film thickness boundary point cloud level group set can include an abnormal film thickness boundary point cloud light level, an abnormal film thickness boundary point cloud medium level, and an abnormal film thickness boundary point cloud heavy level.

[0125] As an example, the execution subject can sort the abnormal film thickness geometric feature group set from small to large to obtain an abnormal film thickness geometric feature sequence. Then, according to the abnormal film thickness geometric feature sequence, the film thickness interval of the abnormal film thickness boundary point cloud in the abnormal film thickness boundary point cloud set is determined to generate an abnormal film thickness boundary point cloud interval level group, thereby obtaining an abnormal film thickness boundary point cloud interval level group set as the abnormal film thickness boundary point cloud level group set.

[0126] A second sub-step is to adjust the multiple parameters of the unmanned aerial vehicle spraying equipment according to the abnormal film thickness boundary point cloud level group set.

[0127] As an example, the execution subject can adjust the flow rate and speed of the unmanned aerial vehicle spraying equipment for the abnormal film thickness boundary point cloud level group in the abnormal film thickness boundary point cloud level group set representing the light level. The flow rate and speed of the unmanned aerial vehicle spraying equipment are adjusted for the abnormal film thickness boundary point cloud level group in the abnormal film thickness boundary point cloud level group set representing the heavy level. The flow rate is adjusted to 2L / min and the speed is 20.79 square meters / minute for the light abnormal area. The flow rate is adjusted to 2.6L / min and the speed is 20.7 square meters / minute for the heavy abnormal area.

[0128] A third sub-step is to control the adjusted unmanned aerial vehicle spraying equipment to spray the building wall surface corresponding to the abnormal film thickness boundary point cloud set according to the spraying path set to generate a first sprayed building wall surface set.

[0129] As an example, the execution subject can control the adjusted unmanned aerial vehicle spraying device to spray the building wall surface corresponding to the abnormal film thickness boundary point cloud set according to each spraying path in the spraying path set to generate a first sprayed building wall surface, so as to obtain a first sprayed building wall surface set as the sprayed building wall surface set.

[0130] In the fourth step, the repaired film thickness point cloud set is generated according to the sprayed building wall surface set.

[0131] Optionally, the execution subject can generate the repaired film thickness point cloud set according to the sprayed building wall surface set by the following steps:

[0132] In the first sub-step, film thickness detection is performed on the first sprayed building wall surface set to generate a sprayed film thickness point cloud set, and in response to determining that the film thickness of the sprayed film thickness point cloud in the sprayed film thickness point cloud set is less than the preset film thickness threshold, a second sprayed building wall surface set is generated according to the adjusted unmanned aerial vehicle spraying device.

[0133] Here, the preset film thickness threshold can be 80 microns.

[0134] As an example, the execution subject can scan the first sprayed building wall surface set by a laser profiler at an interval of 5 cm to obtain a sprayed film thickness point cloud set. In response to determining that the film thickness of the sprayed film thickness point cloud in the sprayed film thickness point cloud set is less than the preset film thickness threshold, the spraying flow of the building wall surface is increased by the adjusted unmanned aerial vehicle spraying device to obtain a second sprayed building wall surface set.

[0135] In the second sub-step, film thickness detection is performed on the second sprayed building wall surface set to generate an adjusted film thickness point cloud set.

[0136] As an example, the execution subject can scan the second sprayed building wall surface set by a laser profiler at an interval of 5 cm to obtain an adjusted film thickness point cloud set.

[0137] In the third sub-step, the difference set of the adjusted film thickness point cloud set and the abnormal film thickness boundary point cloud set is determined as the repaired film thickness point cloud set.

[0138] The related content in the above first step to fourth step is an application point of the present disclosure, which solves the technical problem of "poor quality of wall spraying and low integrity of wall". The factors leading to poor quality of wall spraying and low integrity of wall are often as follows: during the spraying repair of abnormal film thickness point cloud, it is difficult to locate the abnormal area, which leads to poor quality of wall spraying and long time consumption of repair. In the spraying process, spraying path redundancy or omission may occur, which leads to poor reliability of repair and low integrity of wall. If the above factors are solved, the quality of wall spraying can be improved and the integrity of wall can be increased. In order to achieve this effect, first, the abnormal film thickness boundary point cloud is extracted and the graph structure is generated, so that the abnormal film thickness area can be accurately identified and located. Then, the spraying path set is generated through the graph structure, which can improve the integrity of the spraying path and avoid path redundancy and omission. Then, the abnormal film thickness boundary point cloud is divided into different levels through geometric feature extraction and level classification, so that the abnormal film thickness boundary point cloud can be repaired through different levels, which improves the quality of spraying. Then, through multiple film thickness detection and repair, it is ensured that the film thickness after repair meets the preset threshold, which improves the reliability of repair and the integrity of wall, and shortens the time consumption of repair.

[0139] Further reference Figure 3 , as an implementation of the method shown in the above figures, the present disclosure provides some embodiments of a building wall spraying device based on three-dimensional point cloud, which corresponds to the method embodiments shown in Figure 2 , the building wall spraying device based on three-dimensional point cloud can be applied to various electronic devices.

[0140] As Figure 3As shown, the three-dimensional point cloud-based building wall spraying device 300 of some embodiments includes a processing unit 301, a transformation unit 302, a generating unit 303, a repairing unit 304, a dividing unit 305, and a control unit 306. The processing unit 301 is configured to collect a three-dimensional target position coordinate set and a corresponding building site position coordinate set of the three-dimensional target position coordinate set for a building to be sprayed. The three-dimensional target position coordinate set is located on a concrete floor outside the building to be sprayed. The graph formed by connecting each three-dimensional target position coordinate in the three-dimensional target position coordinate set is a triangle. The building site position coordinates in the building site position coordinate set are real position coordinates of the building to be sprayed in a three-dimensional scene. The transformation unit 302 is configured to perform a similarity transformation on the building site position coordinate set and the three-dimensional target position coordinate set to generate a transformed building site position coordinate set. The generating unit 303 is configured to generate a building contour fusion point cloud according to the transformed building site position coordinate set. The repairing unit 304 is configured to repair defects in the building contour fusion point cloud to generate a defect repair result set. The dividing unit 305 is configured to divide the wall of the building to be sprayed according to the defect repair result set to generate a building wall set in response to determining that the defect repair result in the defect repair result set meets a preset defect repair condition. The control unit 306 is configured to control a UAV spraying device to perform a spraying operation on the building wall set.

[0141] It can be understood that the units described in the three-dimensional point cloud-based building wall spraying device 300 correspond to the respective steps in the method described above. Figure 2 Therefore, the operations, features, and advantages described above for the method also apply to the three-dimensional point cloud-based building wall spraying device 300 and the units included therein, which will not be described here.

[0142] Reference is made below to Figure 4 which shows a structural schematic diagram of an electronic device (e.g., a computing device) suitable for implementing some embodiments of the present disclosure. Figure 4 The electronic device shown is merely an example and should not impose any limitation on the functions and use range of embodiments of the present disclosure. As Figure 4As shown, the computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory can include a non-volatile storage medium and an internal memory. The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions which, when executed, can cause the processor to perform any of the above methods. The processor is used to provide computing and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the computer program in the non-volatile storage medium to run, which, when executed by the processor, can cause the processor to perform any of the above methods. The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand, Figure 4 The structure shown in the figure is only a block diagram of part of the structure related to the present disclosure, and does not constitute a limitation on the computer device to which the present disclosure is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0143] It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0144] In one embodiment, the processor is configured to run a computer program stored in the memory to implement the following steps: collecting a set of three-dimensional target position coordinates and a set of corresponding construction site position coordinates of the three-dimensional target position coordinates, wherein the set of three-dimensional target position coordinates is located on a concrete floor outside the building to be sprayed, the graph enclosed by the connection between each three-dimensional target position coordinate in the set of three-dimensional target position coordinates is a triangle, and the construction site position coordinates in the set of construction site position coordinates are real position coordinates of the building to be sprayed in a three-dimensional scene; performing a similarity transformation on the set of construction site position coordinates and the set of three-dimensional target position coordinates to generate a set of transformed construction site position coordinates; generating a building contour fused point cloud according to the set of transformed construction site position coordinates; performing defect repair on the building contour fused point cloud to generate a set of defect repair results; in response to determining that a defect repair result in the set of defect repair results meets a preset defect repair condition, performing wall division on the building to be sprayed corresponding to the set of defect repair results to generate a set of building walls to be sprayed; and controlling a UAV spraying device to perform a spraying operation on the set of building walls to be sprayed.

[0145] The embodiments of the present disclosure further provide a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program includes program instructions. When the program instructions are executed, the method can refer to each embodiment of the building wall spraying method based on a three-dimensional point cloud.

[0146] The computer readable storage medium can be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, and the like.

[0147] It should be noted that, in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that processes, methods, articles, or systems that include a series of elements not only include those elements, but also include other elements not explicitly listed, or include elements inherent to such processes, methods, articles, or systems. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article, or system including the element.

[0148] The above description is merely exemplary of some of the many possible embodiments of the present disclosure and of the principles thereof. It is to be understood that those skilled in the art will be able to devise various embodiments of the present disclosure without departing from the scope of the present disclosure, that the scope thereof is only limited by the claims and that the inventive concept is not limited to the specific features set out above but covers every novel matter falling within the scope of the claims.

Claims

1. A building wall spraying method based on three-dimensional point cloud, characterized in that: include: Collecting a three-dimensional target position coordinate set for the building to be sprayed and a building site position coordinate set corresponding to the three-dimensional target position coordinate set, wherein the three-dimensional target position coordinate set is located on the concrete ground outside the building to be sprayed, the figure formed by connecting the three-dimensional target position coordinates in the three-dimensional target position coordinate set is a triangle, and the building site position coordinates in the building site position coordinate set are the real position coordinates of the building to be sprayed in the three-dimensional scene; Performing a similarity transformation on the building site position coordinate set and the three-dimensional target position coordinate set to generate a transformed building site position coordinate set; generating a building outline fused point cloud according to the transformed building site position coordinate set; Performing defect repair on the building outline fusion point cloud to generate a defect repair result set, wherein the performing defect repair on the building outline fusion point cloud to generate the defect repair result set includes: inputting the building outline fusion point cloud into a defect recognition model to obtain a building defect coordinate set, wherein the defect recognition model sequentially compares the building outline fusion point cloud with a plurality of groups of preset building outline fusion point clouds in a preset scoring feature relationship table, wherein the preset scoring feature relationship table is created based on analysis of a large number of preset building outline fusion point clouds, and each group of preset building outline fusion point clouds corresponds to a preset building defect coordinate set; generating a defect to-be-repaired task operation set based on the building defect coordinate set; repairing each defect to-be-repaired task operation in the defect to-be-repaired task operation set to generate a defect repair result, thereby obtaining a defect repair result set; In response to determining that the defect repair result in the defect repair result set meets the preset defect repair condition, dividing the wall surface of the building to be painted corresponding to the defect repair result set to generate a wall surface set of the building to be painted; Control the drone spraying equipment to perform spraying operations on the building wall set to be sprayed.

2. The method according to claim 1, characterized in that The performing similarity transformation on the construction site position coordinate set and the three-dimensional target position coordinate set to generate a transformed construction site position coordinate set includes: performing data processing on the three-dimensional target position coordinate set and the construction site position coordinate set to generate a parameter data set; The three-dimensional target position coordinate set is transformed according to the parameter data set to generate a transformed building site position coordinate set.

3. The method according to claim 1, characterized in that Generating a building outline fused point cloud according to the transformed building site position coordinate set includes: According to the transformed building site position coordinate set, controlling the laser device to collect the building outline point cloud of the building to be sprayed; Generating a raster map of the building outline point cloud to obtain a building outline raster map; In response to determining that the building outline grid image satisfies a preset outline condition, controlling a camera device to collect a set of tilted images of the building to be painted in multiple directions; The building outline point cloud and the point cloud corresponding to the inclined image set of the building to be sprayed are aligned to obtain a building outline fusion point cloud.

4. The method according to claim 1, wherein The controlling the drone spraying equipment to perform a spraying operation on the building wall set to be sprayed includes: For each building wall surface to be sprayed in the set of building wall surfaces to be sprayed, the following steps are performed: Determining multiple initial spraying parameters for the building wall to be sprayed to generate an initial spraying parameter set; In response to determining that the initial spray parameter set is less than a preset parameter error threshold, the drone spraying equipment is controlled to perform a spraying operation on the set of building walls to be sprayed according to the initial spray parameter set.

5. The method according to claim 4, characterized in that The method further comprises: Perform film thickness detection on the sprayed building wall set to generate a film thickness point cloud set; In response to determining that a film thickness point cloud exceeding a preset film thickness range exists in the film thickness point cloud set, marking at least one film thickness point cloud exceeding the preset film thickness range as an abnormal film thickness point cloud set; The abnormal film thickness point cloud set is spray-repaired to generate a repaired film thickness point cloud set.

6. The method according to claim 5, characterized in that The spray repairing of the abnormal film thickness point cloud set to generate a repaired film thickness point cloud set includes: performing abnormal boundary extraction on the abnormal film thickness point cloud set to generate an abnormal film thickness boundary point cloud set; Determining geometric features of the abnormal film thickness boundary point cloud to obtain an abnormal film thickness geometric feature set; generating a spray-painted building wall surface set according to the abnormal film thickness geometric feature set; A point cloud set of film thickness after repair is generated based on the spray-painted building wall set.

7. A building wall spraying device based on a three-dimensional point cloud for implementing the method according to claim 1, characterized in that: include: a processing unit configured to collect a three-dimensional target position coordinate set for a building to be sprayed and a building site position coordinate set corresponding to the three-dimensional target position coordinate set, wherein the three-dimensional target position coordinate set is located on a concrete floor outside the building to be sprayed, a figure formed by connecting lines between the three-dimensional target position coordinates in the three-dimensional target position coordinate set is a triangle, and the building site position coordinates in the building site position coordinate set are the actual position coordinates of the building to be sprayed in the three-dimensional scene; a transformation unit configured to perform a similarity transformation on the construction site position coordinate set and the three-dimensional target position coordinate set to generate a transformed construction site position coordinate set; a generating unit configured to generate a building outline fused point cloud based on the transformed building site position coordinate set; The repair unit is configured to perform defect repair on the building outline fusion point cloud to generate a defect repair result set, wherein the performing defect repair on the building outline fusion point cloud to generate the defect repair result set includes: inputting the building outline fusion point cloud into a defect recognition model to obtain a building defect coordinate set, wherein the defect recognition model sequentially compares the building outline fusion point cloud with a plurality of groups of preset building outline fusion point clouds in a preset scoring feature relationship table, wherein the preset scoring feature relationship table is created based on an analysis of a large number of preset building outline fusion point clouds, and each group of preset building outline fusion point clouds corresponds to a preset building defect coordinate set; generating a defect to-be-repaired task operation set based on the building defect coordinate set; and repairing each defect to-be-repaired task operation in the defect to-be-repaired task operation set to generate a defect repair result, thereby obtaining a defect repair result set; a dividing unit configured to, in response to determining that a defect repair result in the defect repair result set satisfies a preset defect repair condition, divide the wall surface of the building to be painted corresponding to the defect repair result set to generate a wall surface set of the building to be painted; The control unit is configured to control the drone spraying equipment to perform a spraying operation on the set of building walls to be sprayed.

8. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable medium, characterized in that A computer program is stored thereon, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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