A measurement viewpoint planning method, device, equipment and storage medium

Abstract

The application provides a kind of measurement viewpoint planning method, device, equipment and medium, solve the technical problems of low efficiency in prior art.Method comprising: according to the three-dimensional model of the object to be measured, obtain a plurality of discrete measurement points;According to the distribution of the discrete measurement points, the plurality of discrete measurement points is divided into several measurement point subsets;According to each measurement subset, create a corresponding bounding box, wherein the bounding box includes all the discrete measurement points in the corresponding measurement subset;According to the depth of field and field of view range of the measuring instrument, the bounding box is divided into several measurement subspaces;According to the measurement subspaces and the accuracy constraint model of the measuring instrument, obtain the target measurement point and the corresponding target measurement viewpoint that meet the preset accuracy requirement.The method of the application can realize the planning of measurement viewpoint through a simple method, and improve the efficiency of measurement viewpoint planning.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automation measurement technology, and in particular to a measurement viewpoint planning method, device, equipment and storage medium. BACKGROUND

[0002] In recent years, with the continuous progress of measurement equipment and technology, visual-based measurement methods play an increasingly important role in the fields of aviation, aerospace, ships, etc., and are widely used in scenes such as part size, joint gap, surface connector concave-convex amount, and part aperture detection. For visual measurement, the stability of the measurement system is required to be high, and the measurement accuracy relying on manual operation is difficult to guarantee, and it also brings the problems of repeated measurement and poor measurement integrity. Therefore, using a robot to carry a visual measurement terminal for automatic measurement is a relatively ideal solution, and robot measurement viewpoint planning is the key to ensuring the measurement accuracy and integrity of the system, and in the prior art, the robot measurement viewpoint planning has the problem of low efficiency. SUMMARY

[0003] Therefore, the embodiments of the present application provide a measurement viewpoint planning method, device, equipment and storage medium to solve the problem of low efficiency of the PIU subsystem parameter correlation analysis method in the prior art.

[0004] To solve the above technical problems, the present application provides a measurement viewpoint planning method, which comprises:

[0005] According to the three-dimensional model of the object to be measured, a plurality of discrete measurement points are obtained;

[0006] According to the distribution of the discrete measurement points, the plurality of discrete measurement points are divided into a plurality of measurement point subsets;

[0007] According to each measurement subset, a corresponding bounding box is created, wherein the bounding box includes all the discrete measurement points in the corresponding measurement subset;

[0008] According to the depth of field and the field of view range of the measuring instrument, the bounding box is divided into a plurality of measurement subspaces;

[0009] According to the measurement subspaces and the accuracy constraint model of the measuring instrument, target measurement points and corresponding target measurement viewpoints that meet the preset accuracy requirements are obtained.

[0010] As some optional embodiments of the present application, the step of dividing the plurality of discrete measurement points into a plurality of measurement point subsets according to the distribution of the discrete measurement points comprises:

[0011] Obtain the first distance between each pair of the discrete measurement points;

[0012] According to the first distance, all the discrete measurement points are divided into several measurement point subsets, wherein the distance between a first measurement point and a second measurement point is greater than a second distance, the first measurement point and the second measurement point are discrete measurement points in different measurement point subsets respectively, and the second distance is determined according to the field of view range of the measuring instrument.

[0013] As some optional embodiments of the present application, the step of dividing the bounding box into several measurement subspaces according to the depth of field and the field of view range of the measuring instrument comprises:

[0014] According to the depth of field and the field of view range of the measuring instrument, the length of the edge of the cube is determined.

[0015] According to the cube, the bounding box is divided into several measurement subspaces.

[0016] As some optional embodiments of the present application, the step of obtaining the target measurement point and the corresponding target measurement viewpoint satisfying the preset accuracy requirement according to the measurement subspaces and the accuracy constraint model of the measuring instrument comprises:

[0017] A vector of the measurement direction of the measurement subspace is obtained, denoted as a first vector.

[0018] According to the first vector and the measurement distance of the measuring instrument, a candidate viewpoint constraint condition is obtained.

[0019] According to each measurement point subset and the candidate viewpoint constraint condition, a candidate viewpoint set is obtained.

[0020] According to the candidate viewpoint set and the accuracy constraint model, a target measurement point satisfying the preset accuracy requirement is obtained.

[0021] According to the target measurement point and the candidate viewpoint set, a target measurement viewpoint is obtained.

[0022] As some optional embodiments of the present application, the step of obtaining the vector of the measurement direction of the measurement subspace, denoted as a first vector, comprises:

[0023] According to the measurement point subset, a first matrix is obtained.

[0024] The first matrix is subjected to mean value processing to obtain a second matrix.

[0025] According to the second matrix, a corresponding covariance matrix is obtained.

[0026] According to the eigenvalue of the covariance matrix, the first vector is obtained.

[0027] As some optional embodiments of the present application, the step of obtaining target measurement points satisfying a preset accuracy requirement according to the candidate viewpoint set and the accuracy constraint model comprises:

[0028] According to the accuracy constraint model, the candidate viewpoint set is divided into a first set and a second set, wherein the discrete measurement points in the first set satisfy the accuracy constraint model, and the discrete measurement points in the second set do not satisfy the accuracy constraint model;

[0029] According to the discrete measurement points in the second set, the step of dividing a plurality of the discrete measurement points into a plurality of measurement point subsets according to the distribution of the discrete measurement points is returned until all the discrete measurement points in the second set satisfy the accuracy constraint model.

[0030] As some optional embodiments of the present application, the step of obtaining a plurality of discrete measurement points according to a three-dimensional model of an object to be measured comprises:

[0031] Obtaining a measurement feature of the object to be measured;

[0032] Obtaining a plurality of discrete measurement points according to the measurement feature and the three-dimensional model.

[0033] To solve the above technical problems, the present application further provides a measurement viewpoint planning device, which comprises:

[0034] A first obtaining module is configured to obtain a plurality of discrete measurement points according to a three-dimensional model of an object to be measured;

[0035] A first dividing module is configured to divide a plurality of the discrete measurement points into a plurality of measurement point subsets according to the distribution of the discrete measurement points;

[0036] A creating module is configured to create a corresponding bounding box according to each of the measurement subsets, wherein the bounding box comprises all the discrete measurement points in the corresponding measurement subset;

[0037] A second dividing module is configured to divide the bounding box into a plurality of measurement subspaces according to the depth of field and the field of view range of a measurement instrument;

[0038] A second obtaining module is configured to obtain target measurement points satisfying a preset accuracy requirement and corresponding target measurement viewpoints according to the measurement subspaces and an accuracy constraint model of the measurement instrument.

[0039] To solve the above technical problems, the present application further provides an electronic device, which comprises at least one processor, at least one memory, and computer program instructions stored in the memory, wherein when the computer program instructions are executed by the processor, the method of the first aspect in the above embodiments is implemented.

[0040] To solve the above technical problems, the application further provides a storage medium having computer program instructions stored thereon, which implement the method of the first aspect in the above embodiments when executed by a processor.

[0041] In summary, the application has the following advantages:

[0042] The application discloses a measurement viewpoint planning method, which can automatically obtain discrete measurement points representing a to-be-measured object by obtaining a plurality of discrete measurement points according to a three-dimensional model of the to-be-measured object, thereby improving the planning efficiency of measurement viewpoints; the plurality of discrete measurement points are divided into a plurality of measurement point subsets according to the distribution of the discrete measurement points, thereby reducing the calculation amount of each measurement point subset and improving the planning efficiency of measurement viewpoints; a corresponding bounding box is created according to each measurement subset, wherein the bounding box includes all the discrete measurement points in the corresponding measurement subset, a simple bounding box shape is used to approximate the shape of a complex geometric body, the amount of operation data is reduced, the operation efficiency is improved, and the planning efficiency of subsequent measurement viewpoints is improved; the bounding boxes are divided into a plurality of measurement subspaces according to the depth of field and the field of view range of a measurement instrument; and target measurement points and corresponding target measurement viewpoints meeting a preset accuracy requirement are obtained according to the measurement subspaces and an accuracy constraint model of the measurement instrument, so that the accuracy of the obtained target measurement points is ensured by considering the accuracy constraint requirement of the measurement instrument. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments of the application. For those skilled in the art, other drawings can also be obtained without creative labor on the premise of not deviating from the protection scope of the application.

[0044] Figure 1 FIG. 1 is a flowchart of a measurement viewpoint planning method according to an embodiment of the application.

[0045] Figure 2 FIG. 2 is a structural diagram of an aircraft skin according to an embodiment of the application.

[0046] Figure 3 FIG. 3 is a diagram of bounding box space division according to an embodiment of the application.

[0047] Figure 4 FIG. 4 is a diagram of an accuracy constraint relationship of a measurement instrument according to an embodiment of the application.

[0048] Figure 5 FIG. 5 is a structural diagram of a measurement viewpoint planning device according to an embodiment of the application.

[0049] Figure 6 is a structural schematic diagram of an electronic device of an embodiment of the present application.

[0050] wherein 1 is a surface connector, 2 is an enclosing box, 3 is a measurement sub-space, 4 is a first discrete measurement point, 5 is a measurement instrument, 6 is a measurement viewpoint, and 7 is a centroid. DETAILED DESCRIPTION

[0051] The features and exemplary embodiments of various aspects of the present application will be described below in detail, in order to make the purposes, technical solutions and advantages of the present application more clear and apparent, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only configured to explain the present application, and are not configured to limit the present application. The present application can be implemented without some of these specific details for those skilled in the art. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0052] It should be noted that, in this document, relational terms such as first and second and the like can only be used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a list of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or apparatus. Without more limitations, the elements defined by the statement "comprising" do not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the elements defined by the statement "comprising".

[0053] In recent years, with the continuous progress of measurement equipment and technology, visual-based measurement methods play an increasingly important role in the fields of aviation, aerospace, ships and the like, and are widely used in scenarios such as part size, joint gap clearance, surface connector concave-convex amount, and part aperture detection. For visual measurement, the stability of the measurement system is required to be high, and the measurement accuracy relying on manual operation is difficult to guarantee, and it will also bring the problems of repeated measurement and poor measurement integrity. Therefore, using a robot to carry a visual measurement terminal for automatic measurement is a relatively ideal solution, and robot measurement viewpoint planning is the key to ensuring the measurement accuracy and integrity of the measurement results of the system.

[0054] In the prior art, the robot measurement viewpoint planning is often performed on the whole part, which results in a large number of candidate measurement viewpoints, increases the calculation amount, wastes resources, and reduces the planning efficiency of the measurement viewpoint.

[0055] To solve the above technical problems, referring to Figure 1 To solve the above technical problems, the present application provides a measurement viewpoint planning method, which comprises the following steps:

[0056] S1, obtaining a plurality of discrete measurement points according to a three-dimensional model of an object to be measured;

[0057] Specifically, in this step, first, a three-dimensional model of an object to be measured is obtained, and a plurality of discrete measurement points are obtained according to the three-dimensional model, wherein the object to be measured can be an aircraft part, including but not limited to a fuselage, a wing, a wing tip, an outboard aileron, an inboard aileron, a skin, a rudder, a spoiler, etc., and the discrete measurement points can be obtained by setting a plurality of marker points on the surface of the object to be measured, and then obtaining the discrete measurement points according to the marker points on the three-dimensional model.

[0058] As some optional embodiments of the present application, the step of obtaining a plurality of discrete measurement points according to a three-dimensional model of an object to be measured comprises:

[0059] S11, obtaining a measurement feature of the object to be measured;

[0060] Specifically, first, a measurement feature of the object to be measured is obtained, which can be a hole, a nail head, a joint, etc. distributed on the object to be measured. Characterizing these features by discrete measurement points can greatly reduce the data amount and is easy to implement, thereby improving the planning efficiency of the measurement viewpoint. In a specific embodiment, as shown in Figure 2 the object to be measured is an aircraft skin, and the measurement feature is the center point of the surface connector 1 of the aircraft skin.

[0061] S12, obtaining a plurality of discrete measurement points according to the measurement feature and the three-dimensional model.

[0062] Specifically, after obtaining the measurement feature of the object to be measured, the spatial three-dimensional coordinates of the measurement feature can be obtained according to the three-dimensional model, thereby obtaining a plurality of discrete measurement points. By simplifying the measurement feature to discrete measurement points for measurement viewpoint planning, the calculation process is simple, and the planning efficiency of the measurement viewpoint can be improved.

[0063] S2, divide the plurality of discrete measurement points into a plurality of measurement point subsets according to the distribution of the discrete measurement points;

[0064] Specifically, the discrete measurement points are divided into a plurality of discrete measurement point subsets according to the spatial distribution of the discrete measurement points, and the discrete measurement point subsets are represented as Γ = {Γ1, Γ2, Γ3…, Γ n By dividing the discrete measurement points into a plurality of measurement point subsets, the data amount of each measurement point subset is reduced, the subsequent calculation amount is reduced, and the planning efficiency of the measurement viewpoint is improved.

[0065] As some optional embodiments of the present application, the step of dividing the plurality of discrete measurement points into a plurality of measurement point subsets according to the distribution of the discrete measurement points comprises:

[0066] S21, obtain a first distance between each two of the discrete measurement points;

[0067] Specifically, the distance between each two of the discrete measurement points is obtained through the three-dimensional spatial coordinates of the discrete measurement points, and the distance is recorded as the first distance;

[0068] S22, divide all the discrete measurement points into a plurality of measurement point subsets according to the first distance, wherein the distance between a first measurement point and a second measurement point is greater than a second distance, the first measurement point and the second measurement point are discrete measurement points in different measurement point subsets respectively, and the second distance is determined according to the field of view range of the measurement instrument.

[0069] Specifically, after obtaining the first distance, all the discrete measurement points are divided into a plurality of measurement point subsets, and the first distance between any two discrete measurement points in different discrete measurement point subsets is greater than the second distance, wherein the second distance is determined according to the field of view range of the measurement instrument, and specifically, the length and width of the field of view range of the measurement instrument are recorded as a and b respectively, and the second distance is calculated by the following formula:

[0070]

[0071] Since the distance between the first measurement point and the second measurement point is greater than the second distance, the first measurement point and the second measurement point are discrete measurement points in different measurement point subsets respectively, the field of view overlap when measuring the discrete measurement points in each subset by the measurement instrument is reduced, the problem of low measurement efficiency caused by repeated measurement is avoided, and the efficiency of measurement is higher.

[0072] S3, create a corresponding bounding box according to each measurement subset, wherein the bounding box comprises all the discrete measurement points in the corresponding measurement subset;

[0073] Specifically, for each measurement subset, a corresponding bounding box is created. The bounding box includes the discrete measurement points in the corresponding measurement subset. The bounding box is an algorithm for solving the optimal bounding space of a discrete point set. The basic idea is to use a geometric object with a slightly larger volume and simpler characteristics (called a bounding box) to approximate a complex geometric object. By using a simple bounding box shape to approximate the shape of a complex geometric object, the amount of computational data is reduced, the computational efficiency is improved, and thus the planning efficiency of subsequent measurement viewpoints is improved.

[0074] S4. Based on the depth of field and field of view of the measuring instrument, the bounding box is divided into several measuring subspaces;

[0075] Specifically, in order to further improve the efficiency of viewpoint division, this step further divides the created bounding box according to the depth of field and field of view of the measuring instrument. The measuring instrument to the discrete measuring points is regarded as a straight line during subsequent measurements. Since the bounding box includes multiple discrete measuring points, the intersection of the straight line with the discrete measuring points in the bounding box is slow, while the intersection of the straight line with the measurement subspace obtained after division is faster. This avoids the straight line intersecting with the discrete measuring points multiple times, thereby reducing the amount of calculation and increasing the efficiency of viewpoint planning.

[0076] As some optional embodiments of this application, dividing the bounding box into several measurement subspaces according to the depth of field and field of view of the measuring instrument includes:

[0077] S41. Determine the side length of the cube based on the depth of field and field of view of the measuring instrument;

[0078] Specifically, firstly, based on the depth of field and field of view of the measuring instrument, the side length of the cube is determined. Let the length and width of the field of view of the measuring instrument be a and b, respectively, and let the depth of field of the measuring instrument be h. Then, a, b, and h are used as the side lengths of the cube. By using the associated parameters of the measuring instrument as the side lengths of the cube, the subsequent division of the measurement subspace is associated with the actual situation of the measuring instrument, which can improve the accuracy of the planned viewpoint.

[0079] S42. Based on the cube, divide the bounding box into several measurement subspaces.

[0080] Specifically, in order to further improve the efficiency of measuring viewpoint segmentation, such as Figure 3 As shown, in this step, the bounding box is uniformly divided according to the cube obtained above to obtain several measurement subspaces. When the measurement subspaces are too sparse to determine which measurement subspaces have discrete measurement points, multiple intersections are required. Dividing the bounding box using the cube above can avoid the situation of multiple intersections and increase the efficiency of viewpoint planning.

[0081] S5, acquire target measurement points and corresponding target measurement viewpoints satisfying preset accuracy requirements according to the measurement subspaces and the accuracy constraint model of the measurement instrument.

[0082] Specifically, after the division of the measurement subspaces is completed, the accuracy constraint model of the measurement instrument is acquired, and whether the discrete measurement points included in each measurement subspace satisfy the constraint conditions of the accuracy constraint model can be determined according to the accuracy constraint model of the measurement instrument. The discrete measurement points satisfying the constraint conditions are taken as target measurement points, and finally the corresponding target measurement viewpoints can be acquired according to the target measurement points. Since the target measurement points satisfy the accuracy constraint requirements of the measurement instrument, the accuracy of the acquired target measurement points under the current measurement instrument conditions is ensured, and the measurement accuracy of each discrete measurement point can meet the technical requirements.

[0083] As some optional embodiments of the present application, the step of acquiring target measurement points and corresponding target measurement viewpoints satisfying preset accuracy requirements according to the measurement subspaces and the accuracy constraint model of the measurement instrument comprises:

[0084] S51, acquire a vector of a measurement direction of the measurement subspace, denoted as a first vector;

[0085] Specifically, the measurement direction is the direction in which the discrete measurement points in the measurement subspace have the minimum distribution density, and this direction is the direction in which the measurement instrument points to the object to be detected, denoted as a first vector. By acquiring the first vector, as some optional embodiments of the present application, the step of acquiring a vector of a measurement direction of the measurement subspace, denoted as a first vector, comprises:

[0086] S511, acquire a first matrix according to the measurement point subset;

[0087] Specifically, a first matrix is acquired according to the measurement point subset, wherein the first matrix corresponds to a measurement subspace. Each first matrix includes all discrete measurement points of the corresponding measurement subspace, and the kth measurement subspace∏ k contains a discrete measurement point set denoted as:

[0088] p={p j |p j =[x j ,y j ,z j ],j=1,2,3...,m}

[0089] Then a first matrix with a dimension of 3*m is constructed according to the set p, denoted as M, wherein the expression of M is as follows:

[0090]

[0091] S512, mean value processing is performed on the first matrix to obtain a second matrix;

[0092] Specifically, after obtaining the first matrix, mean value processing is performed on the first matrix to obtain a second matrix. The covariance matrix formed by the index data processed by the mean value processing method can reflect the differences in the variation degrees of the original data and also contains information about the differences in the mutual influence degrees of the indexes. The mean value processing belongs to the prior art and will not be described here.

[0093] S513, a corresponding covariance matrix is obtained according to the second matrix;

[0094] The second matrix is denoted as M u The covariance matrix corresponding to the second matrix is calculated by the following formula:

[0095]

[0096] In the formula, C is the covariance matrix, Mu is the second matrix, and m is the number of discrete measurement points in the corresponding measurement subspace.

[0097] S514, the first vector is obtained according to the eigenvalue of the covariance matrix.

[0098] Specifically, after obtaining the covariance matrix, the first vector can be obtained according to the eigenvector corresponding to the minimum eigenvalue in the eigenvalues of the covariance matrix. In a specific embodiment, the eigenvalues of the covariance matrix are λ1, λ2 and λ3, the corresponding eigenvectors are E1, E2 and E3, and λ3 is the minimum eigenvalue. Therefore, E3 is taken as the first vector, which is the direction with the smallest point cloud density, i.e., the measurement direction of the measurement subspace.

[0099] S52, a candidate viewpoint constraint condition is obtained according to the first vector and the measurement distance of the measuring instrument;

[0100] Specifically, as shown in Figure 4 for each measurement subspace Let the measurement centroid of the measurement subspace be the measurement viewpoint is The measurement viewpoint set is denoted as:

[0101]

[0102] Therefore, p v satisfies the following relationship:

[0103]

[0104] In the formula, dM is the optimal measurement distance of the measuring instrument, the first vector;

[0105] S53, obtaining a candidate viewpoint set according to each measurement point subset and the candidate viewpoint constraint condition;

[0106] Specifically, each measurement point subset is traversed, and a candidate viewpoint is obtained according to the candidate viewpoint constraint condition, so as to obtain a candidate viewpoint corresponding to each measurement subspace, so as to obtain a candidate viewpoint set. The accuracy of the discrete measurement points can be improved by screening the discrete measurement points according to the candidate viewpoint constraint condition, so as to improve the efficiency of subsequent measurement.

[0107] S54, obtaining a target measurement point meeting a preset accuracy requirement according to the candidate viewpoint set and the accuracy constraint model.

[0108] Specifically, after obtaining the candidate viewpoint set, the candidate viewpoint set is further screened according to the accuracy constraint model of the measuring instrument, and the discrete measurement points meeting the constraint condition are taken as the target measurement points. Since the accuracy constraint requirement of the measuring instrument is considered, the accuracy of the obtained target measurement points under the current measuring instrument condition is ensured, so that the obtained target measurement points are more in line with the actual situation. In a specific embodiment, as shown in FIG. 4, the object to be detected in this example is an aircraft skin, and the distance d between the discrete measurement points 4 on the aircraft skin and the measuring viewpoint 6 and the size of the angle β between the connecting line of the two points and the measuring direction are used to judge, so as to obtain a target measurement point meeting a preset accuracy requirement. The accuracy constraint model is as follows: Figure 4

[0109]

[0110] The values of the threshold values d1, d2 and β1 are related to the measurement accuracy distribution of the instrument and the accuracy requirement of the discrete measurement points.

[0111] As some optional embodiments of the present application, the step of obtaining a target measurement point meeting a preset accuracy requirement according to the candidate viewpoint set and the accuracy constraint model comprises:

[0112] S541, dividing the candidate viewpoint set into a first set and a second set according to the accuracy constraint model, wherein the discrete measurement points in the first set meet the accuracy constraint model, and the discrete measurement points in the second set do not meet the accuracy constraint model;

[0113] Specifically, first, the discrete measurement points in the candidate viewpoint set meeting the accuracy constraint model are added to the first set, and the discrete measurement points not meeting the accuracy constraint model are added to the second set.

[0114] ​S542, according to the second set of discrete measurement points, return the distribution of the discrete measurement points, divide a plurality of the discrete measurement points into a plurality of measurement point subsets until all discrete measurement points in the second set meet the accuracy constraint model.

[0115] Specifically, in this step, according to the second set of discrete measurement points, the distribution of the discrete measurement points is returned, and a plurality of the discrete measurement points are divided into a plurality of measurement point subsets until all discrete measurement points in the second set meet the measurement accuracy requirement, which guarantees the number of discrete measurement points and further guarantees the integrity of the measurement.

[0116] S55, according to the target measurement point and the candidate view point set, obtaining a target measurement view point;

[0117] Specifically, after obtaining the target measurement point, the target measurement view point can be obtained by outputting the measurement view point at this time according to the candidate view point set. Since the target measurement point considers the accuracy distribution of the measuring instrument in the geometric space, the measurement accuracy of each discrete measurement point can meet the technical requirements, thereby ensuring the accuracy and efficiency of subsequent measurement.

[0118] In summary, the present application discloses a measurement view point planning method, which can automatically obtain discrete measurement points representing the object to be measured by obtaining a plurality of discrete measurement points according to a three-dimensional model of the object to be measured, thereby improving the planning efficiency of the measurement view point. According to the distribution of the discrete measurement points, a plurality of the discrete measurement points are divided into a plurality of measurement point subsets, and the computational load of each measurement point subset can be reduced by dividing the discrete measurement points, thereby improving the planning efficiency of the measurement view point. According to each measurement subset, a corresponding bounding box is created, wherein the bounding box includes all the discrete measurement points in the corresponding measurement subset. The shape of the complex geometric body is replaced by a simple bounding box shape, which reduces the amount of operation data and improves the efficiency of operation, thereby improving the planning efficiency of the subsequent measurement view point. According to the depth of field and the field of view range of the measuring instrument, the bounding box is divided into a plurality of measurement subspaces. According to the measurement subspaces and the accuracy constraint model of the measuring instrument, a target measurement point and a corresponding target measurement view point meeting the preset accuracy requirement are obtained, which considers the accuracy constraint requirement of the measuring instrument and guarantees the accuracy of the obtained target measurement view point.

[0119] To solve the above technical problems, the present application further provides a measurement view point planning device, which comprises:

[0120] A first obtaining module is configured to obtain a plurality of discrete measurement points according to a three-dimensional model of an object to be measured.

[0121] The first dividing module is configured to divide the plurality of discrete measurement points into a plurality of measurement point subsets according to a distribution of the discrete measurement points.

[0122] The creating module is configured to create a corresponding bounding box according to each measurement subset, wherein the bounding box comprises all the discrete measurement points in the corresponding measurement subset.

[0123] The second dividing module is configured to divide the bounding boxes into a plurality of measurement subspaces according to a depth of field and a field of view range of the measurement instrument.

[0124] The second obtaining module is configured to obtain target measurement points and corresponding target measurement viewpoints that satisfy a preset accuracy requirement according to the measurement subspaces and an accuracy constraint model of the measurement instrument.

[0125] It should be noted that the modules in the measurement viewpoint planning device of the present embodiment are one-to-one corresponding to the steps in the measurement viewpoint planning method of the foregoing embodiments, and therefore the specific implementation and the achieved technical effects of the present embodiment can refer to the implementation of the foregoing measurement viewpoint planning method, which will not be described herein again.

[0126] In addition, the measurement viewpoint planning method of the embodiments of the present application can be implemented by an electronic device. Figure 1 The measurement viewpoint planning method of the embodiments of the present application described above can be implemented by an electronic device. Figure 6 A hardware structure schematic diagram of an electronic device provided by the embodiments of the present application is shown.

[0127] The electronic device can include at least one processor 301, at least one memory 302, and computer program instructions stored in the memory 302, which, when executed by the processor 301, implement the method described in the above embodiments.

[0128] Specifically, the processor 301 described above can include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or can be configured to implement one or more integrated circuits of the embodiments of the present application.

[0129] The memory 302 can include mass storage for data or instructions. By way of example, and not limitation, the memory 302 can include a hard disk drive (HDD), floppy disk drive, flash memory, compact disk (CD) drive, digital versatile disk (DVD) drive, or tape drive, or a combination of two or more of these. The memory 302 can be removable or non-removable (or fixed), as appropriately called. The memory 302 can be internal or external, as appropriately called. In certain embodiments, the memory 302 is a nonvolatile solid-state memory. In certain embodiments, the memory 302 includes read-only memory (ROM). The ROM can be mask- programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM), or flash memory, or a combination of two or more of these, as appropriate.

[0130] The processor 301 implements any of the measurement viewpoint planning methods described above by reading and executing computer program instructions stored in the memory 302.

[0131] In one example, the measurement viewpoint planning device can further include a communication interface and a bus. As shown, the processor 301, the memory 302, and the communication interface 303 are connected through the bus 310 and complete communication with each other. The communication interface 303 is mainly used to realize the communication between various modules, devices, units, and / or equipment in the embodiments of the present application. Figure 6

[0132] The bus includes hardware, software, or both, that couples components of an electronic device to each other in a communicative manner. By way of example, and not limitation, the bus can include an accelerated graphics port (AGP) or other graphics bus, an enhanced industry standard architecture (EISA) bus, a front-side bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (ISA) bus, an infiniband interconnect, a low pin count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standards association local (VLB) bus, or another suitable bus or interconnect, or a combination of two or more of these. Where appropriate, the bus can include one or more buses. Although the present application is described and shown with respect to particular buses, the present application contemplates any suitable bus or interconnect.

[0133] ​In addition, in combination with the measurement viewpoint planning method in the above-mentioned embodiments, a computer readable storage medium can be provided to implement the embodiments. The computer readable storage medium stores computer program instructions. The computer program instructions are executed by a processor to implement any one of the measurement viewpoint planning methods in the above-mentioned embodiments.

[0134] It should be understood that the application is not limited to the particular configurations and processes described above and shown in the drawings. For the sake of brevity and clarity, detailed descriptions of well-known methods are omitted. In the above-mentioned embodiments, several specific steps are described and shown as examples. However, the method processes of the application are not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications and additions, or change the order of the steps, after understanding the spirit of the application.

[0135] The functional blocks shown in the above-described structural block diagrams can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, functional cards, etc. When implemented in software, the elements of the application are program or code segments used to perform the required tasks. The program or code segments can be stored in a machine readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. The "machine readable medium" can include any medium capable of storing or transmitting information. Examples of the machine readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via a computer network such as the Internet, an intranet, etc.

[0136] It should also be noted that the exemplary embodiments mentioned in the application are described based on a series of steps or devices for some methods or systems. However, the application is not limited to the order of the above-mentioned steps, that is, the steps can be performed in the order mentioned in the embodiments, or in an order different from the embodiments, or several steps can be performed simultaneously.

[0137] The above description is only a specific implementation of the application. Those skilled in the art can clearly understand that, for the sake of brevity and simplicity, the specific working processes of the above-described systems, modules and units can refer to the corresponding processes in the above-mentioned method embodiments, which will not be described here. It should be understood that the protection scope of the application is not limited thereto, and any skilled person in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the application, which should be covered by the protection scope of the application.

Claims

1. A measurement viewpoint planning method characterized by, The method comprises: According to the three-dimensional model of the object to be measured, a plurality of discrete measurement points are obtained; According to the distribution of the discrete measurement points, the plurality of discrete measurement points are divided into a plurality of measurement point subsets; According to each of the measurement subsets, a corresponding bounding box is created, wherein the bounding box includes all of the discrete measurement points in the corresponding measurement subset; According to the depth of field and the field of view range of the measuring instrument, the bounding box is divided into a plurality of measurement subspaces; According to the measurement subspaces and the accuracy constraint model of the measuring instrument, target measurement points and corresponding target measurement viewpoints that meet the preset accuracy requirements are obtained; According to the depth of field and the field of view range of the measuring instrument, the bounding box is divided into a plurality of measurement subspaces, comprising: According to the depth of field and the field of view range of the measuring instrument, the length of the side of the cube is determined; According to the cube, the bounding box is divided into a plurality of measurement subspaces; The step of obtaining target measurement points and corresponding target measurement viewpoints that meet the preset accuracy requirements according to the measurement subspaces and the accuracy constraint model of the measuring instrument, comprising: Obtain the vector of the measurement direction of the measurement subspace, denoted as the first vector; According to the first vector and the measurement distance of the measuring instrument, a candidate viewpoint constraint condition is obtained; According to each of the measurement point subsets and the candidate viewpoint constraint condition, a candidate viewpoint set is obtained; According to the candidate viewpoint set and the accuracy constraint model, target measurement points that meet the preset accuracy requirements are obtained; According to the target measurement points and the candidate viewpoint set, target measurement viewpoints are obtained; The step of obtaining target measurement points that meet the preset accuracy requirements according to the candidate viewpoint set and the accuracy constraint model, comprising: According to the accuracy constraint model, the candidate viewpoint set is divided into a first set and a second set, wherein the discrete measurement points in the first set meet the accuracy constraint model, and the discrete measurement points in the second set do not meet the accuracy constraint model; According to the discrete measurement points in the second set, return to the step of dividing the plurality of discrete measurement points into a plurality of measurement point subsets according to the distribution of the discrete measurement points, until all the discrete measurement points in the second set meet the accuracy constraint model.

2. The measurement viewpoint planning method of claim 1, wherein, The step of dividing the plurality of discrete measurement points into a plurality of measurement point subsets according to the distribution of the discrete measurement points, comprising: Obtain the first distance between each of the discrete measurement points; According to the first distance, all the discrete measurement points are divided into a plurality of measurement point subsets, wherein the distance between the first measurement point and the second measurement point is greater than the second distance, the first measurement point and the second measurement point are discrete measurement points in different measurement point subsets, and the second distance is determined according to the field of view range of the measuring instrument.

3. The measurement viewpoint planning method of claim 1, wherein, The step of obtaining the vector of the measurement direction of the measurement subspace, denoted as the first vector, comprising: According to the measurement point subset, a first matrix is obtained; The first matrix is processed by mean value to obtain a second matrix; According to the second matrix, a corresponding covariance matrix is obtained; The first vector is obtained according to eigenvalues of the covariance matrix.

4. The measurement viewpoint planning method of claim 1, wherein, The plurality of discrete measurement points are obtained according to a three-dimensional model of the object to be measured, including: a measurement feature of the object to be measured is obtained; the plurality of discrete measurement points are obtained according to the measurement feature and the three-dimensional model.

5. A measurement viewpoint planning apparatus for implementing the measurement viewpoint planning method according to any one of claims 1 to 4, characterized by The device includes: a first obtaining module configured to obtain a plurality of discrete measurement points according to a three-dimensional model of an object to be measured; a first dividing module configured to divide the plurality of discrete measurement points into a plurality of measurement point subsets according to a distribution of the discrete measurement points; a creating module configured to create a corresponding bounding box according to each of the measurement subsets, wherein the bounding box includes all of the discrete measurement points in the corresponding measurement subset; a second dividing module configured to divide the bounding boxes into a plurality of measurement subspaces according to a depth of field and a field of view range of a measurement instrument; a second obtaining module configured to obtain target measurement points and corresponding target measurement viewpoints that satisfy a preset accuracy requirement according to the measurement subspaces and an accuracy constraint model of the measurement instrument.

6. An electronic device, comprising: including: at least one processor, at least one memory, and computer program instructions stored in the memory that, when executed by the processor, implement the method of any one of claims 1-4.

7. A storage medium having stored thereon computer program instructions, characterized in that, when the computer program instructions are executed by the processor, the method of any one of claims 1-4 is implemented.

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