A large component measurement system based on a six-dimensional sensor and its calibration method

Abstract

This application belongs to the field of visual inspection technology, specifically disclosing a large component measurement system and its calibration method based on a six-dimensional sensor. The measurement system of this application uses a laser tracker and a six-dimensional sensor as external tracking devices, which has advantages such as high measurement accuracy and high measurement efficiency compared to external tracking devices based on laser target spheres. Furthermore, the measurement system of this application obtains the relative pose of two adjacent scans of the scanner by rigidly matching the centers of the spheres obtained from two adjacent measurements of the calibration sphere array, and constructs a relationship between the calibration parameters to be solved and the relative pose. The calibration parameters in the relationship are solved using the total least squares method based on the Kronecker product. The calibration results of the calibration method of this application are more accurate.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of visual detection, and more particularly relates to a large component measurement system based on a six-dimensional sensor and a calibration method thereof. BACKGROUND

[0002] In order to check whether the product size meets the design requirements, measurement is an important link in the production process. Therefore, modern industry has made great demands on measurement technology. At present, manufacturing enterprises are actively promoting the application of digital measurement technology.

[0003] At present, the measurement methods of large-size components mainly include: manual plug gauge measurement, large three-coordinate measuring machine measurement, structure light three-dimensional scanner measurement based on landmark point splicing, etc. Among them, manual measurement is low in efficiency, poor in accuracy and consistency; three-coordinate measuring machine measurement has high measurement accuracy, but is low in measurement efficiency, large in space occupation and poor in expansion capability; structure light three-dimensional scanner measurement based on landmark point splicing has high collection efficiency and high measurement accuracy, but it takes a long time to arrange the landmark points, and the whole efficiency is insufficient after the measurement is completed. There are still many measurement methods using tracking devices combined with three-dimensional scanners, such as binocular cameras as external tracking devices combined with three-dimensional scanners, but they need large devices such as ball cages, and their tracking accuracy is low; for example, lasers as external tracking devices combined with three-dimensional scanners, but they are limited by the visible angle of the laser target ball and the measurement efficiency of multiple target balls. SUMMARY

[0004] In view of the above defects or improvement needs of the prior art, the present application provides a large component measurement system based on a six-dimensional sensor and a calibration method thereof, which aims to solve the technical problem of insufficient measurement efficiency of the existing large component.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present application provides a large component measurement system based on a six-dimensional sensor, comprising: a laser tracker, a six-dimensional sensor, a three-dimensional scanner, an adapter fixing part and a calibration ball array.

[0006] The laser tracker is used to emit laser tracking six-dimensional sensor to obtain the position of the six-dimensional sensor.

[0007] The six-dimensional sensor is used to reflect the detection laser emitted by the laser tracker and detect its own attitude.

[0008] The three-dimensional scanner is used to scan the calibration ball array or the measured component to obtain point cloud data.

[0009] The adapter fixing part is used to fix the six-dimensional sensor and the three-dimensional scanner together.

[0010] The calibration sphere and laser tracker are relatively stationary and are used to calibrate the conversion relationship between the six-dimensional sensor and the three-dimensional scanner.

[0011] Secondly, this application provides a calibration method for a large component measurement system based on a six-dimensional sensor, comprising:

[0012] The scanning pose of the 3D scanner is changed and the calibration sphere array is scanned to obtain multiple sets of sphere array point clouds. At the same time, the laser tracker measures the pose of the six-dimensional sensor under each scanning pose.

[0013] Obtain the relative poses of the six-dimensional sensors between any two adjacent scan poses, and form a set. A ;

[0014] Rigid matching is performed on the centers of two adjacent sets of spherical point clouds to obtain the relative poses of the 3D scanners between any adjacent scanning poses, forming a set. B ;

[0015] The relative pose between the 3D scanner and the 6D sensor is used as the calibration parameter to be solved. X ; Construct a collection A ,gather B and parameters X Relationships;

[0016] Linearize the relation, solve the linearized relation using the total least squares method, and orthogonalize the rotation matrix in the solution to obtain the parameters. X The linear solution.

[0017] Preferably, rigid matching is performed on the centers of two adjacent sets of spherical array point clouds to obtain the relative pose of the 3D scanner between any adjacent scanning poses, specifically:

[0018] The sphere array point cloud is segmented into spheres and its center is fitted to obtain the center of each sphere in the sphere array point cloud.

[0019] Rigid matching is performed on the centers of the spheres in two adjacent sets of sphere array point clouds to obtain the relative pose of the 3D scanner between adjacent scanning poses.

[0020] Preferably, the point cloud of the spherical array is segmented into spheres and its center is fitted, specifically as follows:

[0021] The spherical point cloud is filtered and denoised, and the planes in the spherical point cloud are identified and removed using the random sampling consensus algorithm;

[0022] The random sampling consensus algorithm is used to fit the spheres in the remaining sphere array point cloud to obtain the interior points of the spheres;

[0023] The center of the sphere is obtained by performing an optimal sphere fit on the interior points using the least squares method.

[0024] Preferably, the set A Specifically:

[0025]

[0026] in, For the first The pose of the six-dimensional sensor in the coordinate system of the laser tracker during the next scan, where the subscript... and Indicates the adjacent scan sequence number.

[0027] Preferably, the set B Specifically:

[0028]

[0029] in, Indicates the first During the second scan, the pose of the sphere array in the 3D scanner coordinate system is calibrated, where the subscript... and Indicates the adjacent scan sequence number.

[0030] Preferably, construct a set A ,gather B and parameters X Relationship between them: .

[0031] Preferably, the relation is linearized based on the Kronecker product:

[0032]

[0033] in, Here is the coefficient matrix:

[0034]

[0035] in, and These represent the rotation matrix and translation amount relative to the pose of the six-dimensional sensor, respectively. and These represent the rotation matrix and translation amount relative to the pose of the 3D scanner, respectively; superscript Indicates transpose, symbol Indicates the Kronecker product, subscript Indicates the adjacent scan sequence number. Represents the identity matrix;

[0036] A vector of constant terms:

[0037]

[0038] for X Linearized form:

[0039]

[0040] in, and Represent the rotation matrix and translation amount of the relative pose between the 3D scanner and the 6D sensor, respectively. subscript Represents the first in the matrix row and number List.

[0041] Preferably, based on the measurement errors of the 3D scanner and the 6D sensor, writing:

[0042]

[0043] in, and for and The observed value, i.e. the measured value; and This is the error correction value. and for and The adjusted value.

[0044] Thirdly, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in any possible implementation of the second aspect.

[0045] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art:

[0046] (1) This application uses a laser tracker and a six-dimensional sensor as external tracking devices, which have the advantages of high measurement accuracy and high measurement efficiency compared with external tracking devices based on laser target balls; it can meet the measurement needs of large range, high precision and high efficiency.

[0047] (2) This application obtains the relative pose of the scanner in two adjacent scans by rigid matching of the center of the sphere obtained from two adjacent measurements. Compared with the existing methods, this reduces the influence of the sphere fitting error when establishing a local coordinate system through the sphere array and avoids the interference of the sphere array background point cloud with the registration result when directly registering through the point cloud.

[0048] (3) This application adopts the linearization of the relation based on the Kronecker product and uses the total least squares method to solve the calibration parameters in the linearized relation. Compared with ordinary least squares, this calibration parameter solution method considers more sensor error sources and the calibration results are more accurate. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the composition of the large component measurement system provided in the embodiments of this application.

[0050] Figure 2 This is a schematic diagram showing the connection of the adapter, six-dimensional sensor, and three-dimensional scanner provided in the embodiments of this application.

[0051] Figure 3 This is a flowchart of the calibration method for the large component measurement system provided in the embodiments of this application.

[0052] Figure 4 This is a schematic diagram of a spherical point cloud obtained by a 3D scanner according to an embodiment of this application.

[0053] Figure 5 This is a schematic diagram of a sphere obtained by fitting the point cloud of the spherical array provided in the embodiments of this application.

[0054] Figure 6 This is a schematic diagram of a 3D scanner performing continuous scanning by changing its scanning pose, as provided in an embodiment of this application.

[0055] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0056] In all the accompanying drawings, the same reference numerals are used to denote the same elements or structures, wherein:

[0057] 1 is a laser tracker; 2 is a six-dimensional sensor; 3 is a three-dimensional scanner; 4 is a mounting bracket; 5 is a calibration sphere. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0059] The terms "first" and "second," etc., used in the specification and claims herein are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0060] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0061] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more, for example, multiple spheres means two or more spheres, multiple elements means two or more elements, etc.

[0062] First, the technical terms involved in the embodiments of this application will be introduced.

[0063] The Kronecker product is a special type of tensor product in matrix operations, used to expand two matrices into a larger matrix.

[0064] Random Sample Consensus (Ransac) is an algorithm that calculates mathematical model parameters of a dataset containing outliers to obtain valid sample data. It was first proposed by Fischler and Bolles in 1981.

[0065] The embodiments of this application are described below with reference to the accompanying drawings.

[0066] This application provides a large component measurement system based on a six-dimensional sensor, such as... Figure 1 As shown, it includes a laser tracker 1, a six-dimensional sensor 2, a three-dimensional scanner 3, a mounting bracket 4, and a calibration sphere array 5. Among them:

[0067] The 3D scanner 3 is used to scan the calibration sphere array or the component under test to obtain point cloud data. During the calibration process of the measurement system, the calibration sphere array 5 is used as the scanning object of the 3D scanner 3. The 3D scanner 3 continuously changes its pose to scan the calibration sphere array 5 and obtains the sphere array point cloud under different scanning poses.

[0068] like Figure 2 As shown, the six-dimensional sensor 2 is fixed together with the three-dimensional scanner 3 via the adapter 4, and changes its pose along with the three-dimensional scanner 3 during the scanning process. The adapter 4 has a pre-installed fixing interface for the three-dimensional scanner 3 and the six-dimensional sensor 2.

[0069] The laser tracker 1 is set at a position that is stationary relative to the calibration sphere array 5. It is used to track the six-dimensional sensor 2, which is constantly changing its pose, and to calculate the pose of the six-dimensional sensor 2 relative to the laser tracker 1.

[0070] like Figure 3 As shown, the calibration method for the large component measurement system in this application embodiment includes the following steps:

[0071] S1. Continuously change the scanning pose of the 3D scanner 3 to scan the calibration sphere array 5, and obtain the following: Figure 4 The spherical point cloud shown is assumed to have been acquired. n +1 group of spherical point clouds.

[0072] Simultaneously, the pose of the six-dimensional sensor 2 under different scanning poses is acquired using laser tracker 1. Let the acquired poses be... n +1 group pose.

[0073] S2, regarding the above n +1 group of six-dimensional sensors 2 pose and n +1 group of spherical point clouds are processed, specifically as follows:

[0074] S21. Calculate the relative pose transformation of the six-dimensional sensor 2 between two adjacent measurements, and obtain a total of n Group relative poses to form a set A , A The expression is:

[0075]

[0076] in, For the first The pose of the six-dimensional sensor in the coordinate system of the laser tracker during the next scan, where the subscript... and Indicates the sequence number of adjacent scans; and These represent the rotation matrix and translation amount of the relative pose of the six-dimensional sensor, respectively.

[0077] S22. Automatically segment and identify spheres in the spherical point cloud, and fit the center of each sphere to obtain... n +1 set of ball center data. This data is obtained from the ball array point cloud, such as... Figure 5 The algorithm for determining the center of the spheres in the array shown is as follows:

[0078] S221. Filter and denoise the point cloud of the sphere array, and remove the planes in the background by Ransac plane recognition; in order to avoid the cross-section of the sphere being misidentified as a plane, auxiliary judgments such as the number of interior points and the consistency of normals are required.

[0079] S222. Use Ransac to fit all the spheres in the remaining sphere array point cloud and obtain the interior points of the spheres.

[0080] S223. Use the least squares method to perform the best sphere fitting on the above interior points to obtain the center of the sphere array.

[0081] S23. Calculate the relative pose transformation of the 3D scanner 3 between two adjacent measurements. (The above results are used to calculate the pose transformation of the scanner 3.) n +1 group of spheres' centers are processed, and the 3D scanner 3rd... i The center of the sphere obtained from the second measurement is the same as the first measurement. i The centers of the spheres obtained from +1 measurements are rigidly matched, and the resulting transformation matrix is ​​used as the relative pose of the 3D scanner 3. A total of [number missing] measurements are obtained. n Groups of relative poses, forming a set B :

[0082]

[0083] in, Indicates the first During the second scan, the pose of the sphere array in the 3D scanner coordinate system is calibrated, where the subscript... and Indicates the sequence number of adjacent scans; and These represent the rotation matrix and translation amount of the 3D scanner relative to its pose, respectively.

[0084] S3, such as Figure 6 The diagram illustrates two scans performed by changing the pose of the 3D scanner. The pose transformation matrix from the spherical array coordinate system to the 3D scanner 3 coordinate system, the pose matrix of the six-dimensional sensor 2 in the laser tracker 1 coordinate system, and the relative pose transformation between the 3D scanner 3 and the six-dimensional sensor 2 in two adjacent measurements constitute the following: n Group the following relations:

[0085]

[0086] in, The relative pose between the 3D scanner 3 and the 6D sensor 2 is represented by the calibration parameters to be solved. X Then the above formula can be expressed as:

[0087]

[0088] in, and These represent the rotation matrix and translation amount of the relative pose between the 3D scanner 3 and the 6D sensor 2, respectively.

[0089] Expand it as follows:

[0090]

[0091] Linearize it using the properties of the Kronecker product, and define the function. subscript Represents the first in the matrix row and number According to the properties of the Kronecker product, we have:

[0092]

[0093] Among them, superscript Indicates transpose. Let the Kronecker product be expressed as ( ). a ()( b Transformed into:

[0094]

[0095] The formula ( a ()( b Writing matrix format:

[0096]

[0097] in, Here is the coefficient matrix:

[0098]

[0099] in, and These represent the rotation matrix and translation amount relative to the pose of the six-dimensional sensor, respectively. and These represent the rotation matrix and translation amount relative to the pose of the 3D scanner, respectively; superscript Indicates transpose, symbol Indicates the Kronecker product, subscript Indicates the adjacent scan sequence number. Represents the unit array

[0100] A vector of constant terms:

[0101]

[0102] for X Linearized form:

[0103]

[0104] in, and Represent the rotation matrix and translation amount of the relative pose between the 3D scanner and the 6D sensor, respectively. .

[0105] Based on the measurement errors of 3D scanners and six-dimensional sensors, writing:

[0106]

[0107] in, and for and The observed value, i.e. the measured value; and This is the error correction value. and For and The adjusted value.

[0108] Solving the above relation using the total least squares method, we can rewrite it as follows:

[0109]

[0110] in, .

[0111] If the weight matrix is ​​set to the identity matrix, then the adjustment criterion can be expressed as:

[0112]

[0113] in, This indicates the search for the F-norm; Representation matrix The Middle row and number The error of the column, express Group measurement data; function Represents the trace of a matrix;

[0114] Combining SVD decomposition, the solution method is as follows:

[0115] Step 1: Construct the matrix

[0116] Step 2, Calculation eigenvalues ​​and eigenvectors

[0117] Step 3: Select the eigenvector corresponding to its smallest eigenvalue.

[0118] Step 4, the solution can be expressed as

[0119] The solution obtained by the method The rotation matrix does not satisfy the orthogonality constraint. It is orthogonalized by Schmidt orthogonalization to obtain the pose transformation relationship between the 3D scanner 3 and the 6D sensor 2, and complete the calibration.

[0120] Based on the methods in the above embodiments, this application provides an electronic device, such as... Figure 7 As shown, the electronic device includes a processor, a communications interface, a memory, and a communication bus, wherein the processor, communications interface, and memory communicate with each other via the communication bus. The processor can invoke logical instructions stored in the memory to execute the methods described in the above embodiments.

[0121] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0122] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0123] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0124] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0125] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0126] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0127] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

[0128] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method of calibrating a large component measurement system, the method comprising: The large component measurement system comprises a laser tracker, a six-dimensional sensor, a three-dimensional scanner, an adapter fixture and a calibration sphere array; The laser tracker is configured to emit laser tracking the six-dimensional sensor and acquire a position of the six-dimensional sensor; The six-dimensional sensor is configured to reflect the detection laser emitted by the laser tracker and detect an attitude of the six-dimensional sensor; The three-dimensional scanner is configured to scan the calibration sphere array or a component to be measured to acquire point cloud data; The adapter fixture is configured to fix the six-dimensional sensor and the three-dimensional scanner together; The calibration sphere array and the laser tracker are relatively static in position, and are configured to calibrate a conversion relationship between the six-dimensional sensor and the three-dimensional scanner; The calibration method comprises: transforming a scanning pose of the three-dimensional scanner and scanning the calibration sphere array to obtain a plurality of groups of sphere array point clouds, while the laser tracker measures the pose of the six-dimensional sensor at each scanning pose; acquiring the relative pose of the six-dimensional sensor between any adjacent scan poses, to form a set A ; The centers of the adjacent two groups of ball array point clouds are rigidly matched to obtain the relative pose of the three-dimensional scanner between any adjacent scanning poses, and a set is formed B ; To take the relative pose between the three-dimensional scanner and the six-dimensional sensor as calibration parameters to be solved X ; construct a set A , a set B , and a parameter X between the relationship: ; linearizing the relation, solving the linearized relation by total least squares, and obtaining the parameters from the solution of the rotation matrix X linearized solution Based on the Kron linearization of the relationship , we obtain: wherein is the coefficient matrix: where and denote the rotation matrix and the translation of the six-dimensional sensor relative pose, respectively; and denote the rotation matrix and the translation of the three-dimensional scanner relative pose, respectively; the superscript denotes the transpose, the symbol denotes the Kronecker product, the subscript denotes the consecutive scan index, denotes the identity matrix; is the constant term vector: is X linearized form: in, and Represent the rotation matrix and translation amount of the relative pose between the 3D scanner and the 6D sensor, respectively. subscript Represents the first in the matrix row and number List.

2. The calibration method of claim 1, wherein performing rigid matching on sphere centers of two adjacent groups of sphere array point clouds to obtain a relative pose of the three-dimensional scanner between any adjacent scanning poses, specifically as follows: performing sphere segmentation and sphere center fitting on the sphere array point clouds to obtain sphere centers in the sphere array point clouds; performing rigid matching on the sphere centers in two adjacent groups of sphere array point clouds to obtain the relative pose of the three-dimensional scanner between adjacent scanning poses.

3. The calibration method of claim 2, wherein, Performing sphere segmentation and sphere center fitting on the sphere array point clouds, specifically as follows: performing filtering and denoising on the sphere array point clouds, and identifying and removing planes in the sphere array point clouds by using a random sample consensus algorithm; fitting spheres in the remaining sphere array point clouds by using the random sample consensus algorithm to obtain inliers of the spheres; performing optimal sphere fitting on the inliers by using a least square method to obtain sphere centers.

4. The calibration method of claim 1, wherein The set A Specifically: wherein, is the first is the pose of the six-dimensional sensor in the laser tracker coordinate system at the and indicate the adjacent scan number.

5. The calibration method of claim 1, wherein The set B Specifically: wherein, denotes the pose of the calibration sphere in the coordinate system of the three-dimensional scanner at the and denotes the adjacent scan number.

6. The calibration method of claim 1, wherein Based on the measurement error of the three-dimensional scanner and the six-dimensional sensor, the following is written: Written: wherein and are and observed values, i.e. measured values; and are error corrections, and are and adjusted values.

7. An electronic device, comprising: The method comprises: at least one memory for storing a computer program; at least one processor for executing the program stored in the memory, and when the program stored in the memory is executed, the processor is configured to execute the method according to any one of claims 1-6.

Images