Large component measuring system based on six-dimensional sensor and calibration method thereof

Abstract

The invention belongs to the technical field of visual inspection, and particularly discloses a large component measuring system based on a six-dimensional sensor and a calibration method of the large component measuring system. According to the measuring system, the laser tracker and the six-dimensional sensor serve as external tracking equipment, and compared with an external tracking device based on a laser target ball, the measuring system has the advantages of being high in measuring precision, high in measuring efficiency and the like. In addition, the measurement system obtains relative poses of two adjacent times of scanning of the scanner in a mode that sphere centers obtained by two adjacent times of measurement and calibration of a sphere array are rigidly matched, constructs a relational expression of calibration parameters to be solved and the relative poses, and solves the calibration parameters in the relational expression through a total least square method based on a Kronecker product; the calibration result of the measurement system calibration method is more accurate.

Description

Technical Field

[0001] This application belongs to the technical field of visual inspection, and more specifically, relates to a large component measurement system based on a six-dimensional sensor and its calibration method. Background Art

[0002] In order to check whether the external dimensions of a product meet the design requirements, measurement is an essential and important link in the production process. Therefore, modern industry has put forward high requirements for measurement technology. At present, manufacturing enterprises are actively promoting the application of digital measurement technology.

[0003] At present, the measurement methods for large-sized components mainly include: manual measurement with plug gauges and feeler gauges, measurement with large coordinate measuring machines, structured light three-dimensional scanner measurement based on the splicing of fiducial points, etc. Among them, manual measurement has low efficiency, poor accuracy and consistency; coordinate measuring machines have high measurement accuracy, but low measurement efficiency, large occupied space and poor expansion ability; structured light three-dimensional scanner measurement based on the splicing of fiducial points has high acquisition efficiency and high measurement accuracy, but it takes a long time to arrange fiducial points, and they need to be removed after measurement, resulting in insufficient overall efficiency. There are also many measurement methods that combine tracking devices with three-dimensional scanners, such as combining a binocular camera as an external tracking device with a three-dimensional scanner, but a relatively large device such as a constant velocity joint is required, and its tracking accuracy is low; for another example, combining a laser as an external tracking device with a three-dimensional scanner, but it is limited by the viewing angle of the laser target ball and the measurement efficiency of multiple target balls. Summary of the Invention

[0004] In view of the above defects or improvement requirements of the prior art, this application provides a large component measurement system based on a six-dimensional sensor and its calibration method, aiming to solve the technical problem of insufficient measurement efficiency of existing large components.

[0005] To achieve the above object, in a first aspect, this application provides a large component measurement system based on a six-dimensional sensor, including: a laser tracker, a six-dimensional sensor, a three-dimensional scanner, an adapter fixture, and a calibration ball array; The laser tracker is used to emit laser to track the six-dimensional sensor and obtain the position of the six-dimensional sensor; The six-dimensional sensor is used to reflect the detection laser emitted by the laser tracker and detect its own attitude; The three-dimensional scanner is used to scan the calibration ball array or the component to be measured to obtain point cloud data; The adapter fixture is used to fix the six-dimensional sensor and the three-dimensional scanner together; The positions of the calibration ball array and the laser tracker are relatively stationary, and are used to calibrate the conversion relationship between the six-dimensional sensor and the three-dimensional scanner.

[0006] In a second aspect, the present application provides a calibration method for a large component measurement system based on a six-dimensional sensor, including: Changing the scanning pose of the three-dimensional scanner and scanning a calibration sphere array to obtain multiple sets of sphere array point clouds. At the same time, the laser tracker measures the pose of the six-dimensional sensor at each scanning pose; Obtaining the relative pose of the six-dimensional sensor between any two adjacent scanning poses and forming a set A ; Performing rigid matching on the centers of the spheres in two adjacent sets of sphere array point clouds to obtain the relative pose of the three-dimensional scanner between any two adjacent scanning poses and forming a set B ; Taking the relative pose between the three-dimensional scanner and the six-dimensional sensor as the calibration parameter to be solved X ; constructing a relationship between the set A , the set B and the parameter X ; Linearizing the relationship, solving the linearized relationship using the total least squares method, and orthogonalizing the rotation matrix in the solution to obtain the linear solution of the parameter X .

[0007] Preferably, performing rigid matching on the centers of the spheres in two adjacent sets of sphere array point clouds to obtain the relative pose of the three-dimensional scanner between any two adjacent scanning poses specifically includes: Performing sphere segmentation and sphere center fitting on the sphere array point cloud to obtain the centers of the spheres in the sphere array point cloud; Performing rigid matching on the centers of the spheres in two adjacent sets of sphere array point clouds to obtain the relative pose of the three-dimensional scanner between adjacent scanning poses.

[0008] Preferably, performing sphere segmentation and sphere center fitting on the sphere array point cloud specifically includes: Filtering and denoising the sphere array point cloud, and using the random sample consensus algorithm to identify and remove the planes in the sphere array point cloud; Using the random sample consensus algorithm to fit the spheres in the remaining sphere array point cloud to obtain the inliers of the spheres; Performing optimal sphere fitting on the inliers by the least squares method to obtain the sphere centers.

[0009] Preferably, the set A specifically is:

[0010] where is the pose of the six-dimensional sensor in the laser tracker coordinate system at the th scan, where the subscripts and represent adjacent scan numbers.

[0011] Preferably, the set B Specifically:

[0012] wherein, represents the pose of the calibration ball array in the coordinate system of the 3D scanner during the -th scan, where the subscripts and represent adjacent scan numbers.

[0013] Preferably, construct the relational expression between the set A , the set B and the parameter X : .

[0014] Preferably, it is characterized in that the relational expression is linearized based on the Kronecker product:

[0015] wherein, is the coefficient matrix:

[0016] wherein, and respectively represent the rotation matrix and the translation amount of the relative pose of the six-dimensional sensor; and respectively represent the rotation matrix and the translation amount of the relative pose of the 3D scanner; the superscript represents the transpose, the symbol represents the Kronecker product, the subscript represents adjacent scan numbers, represents the identity matrix; is the constant term vector:

[0017] is X in its linearized form:

[0018] wherein, and respectively represent the rotation matrix and the translation amount of the relative pose between the 3D scanner and the six-dimensional sensor, and the function , where the subscript represents the -th row and the -th column in the matrix.

[0019] Preferably, based on the measurement errors of the 3D scanner and the 6D sensor, is written as:

[0020] wherein, and are and 's observed values, i.e., measurement values; and are error correction numbers, and are and 's adjusted values.

[0021] In a third aspect, the present application provides an electronic device, including: at least one memory for storing a 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 used to execute the method described in any possible implementation manner of the second aspect.

[0022] Generally speaking, compared with the prior art through the above technical solutions conceived by the present application, the following beneficial effects are obtained: (1) The present application uses a laser tracker and a 6D sensor as external tracking devices, which have the advantages of high measurement accuracy and high measurement efficiency compared with the external tracking device based on a laser target ball; it can meet the measurement requirements of large range, high precision and high efficiency.

[0023] (2) The present application obtains the relative pose of two adjacent scans of the scanner by rigidly matching the sphere centers obtained from two adjacent measurements. Compared with the existing methods, it reduces the influence of the sphere fitting error when establishing a local coordinate system through a sphere array, and avoids the interference of the sphere array background point cloud on the registration result when directly registering through point clouds.

[0024] (3) The present application linearizes the relational expression based on the Kronecker product and uses the total least squares method to solve the calibration parameters in the linearized relational expression. This calibration parameter solving method considers more sensor error sources compared with ordinary least squares, and the calibration result is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a schematic diagram of the composition of the large component measurement system provided by the embodiment of the present application.

[0026] Figure 2 is a schematic diagram of the connection of the adapter fixture, 6D sensor and 3D scanner provided by the embodiment of the present application.

[0027] Figure 3 is a flowchart of the calibration method of the large component measurement system provided by the embodiment of the present application.

[0028] Figure 4 It is a schematic diagram of the spherical array point cloud obtained by the 3D scanner provided in the embodiment of the present application.

[0029] Figure 5 It is a schematic diagram of the sphere obtained after fitting the spherical array point cloud provided in the embodiment of the present application.

[0030] Figure 6 It is a schematic diagram of the 3D scanner changing the scanning pose for continuous scanning provided in the embodiment of the present application.

[0031] Figure 7 It is a schematic diagram of the structure of an electronic device provided in the embodiment of the present application.

[0032] In all the drawings, the same reference numerals are used to represent the same elements or structures, where: 1 is a laser tracker; 2 is a six-dimensional sensor; 3 is a 3D scanner; 4 is an adapter fixing part; 5 is a calibration spherical array. Detailed implementation manners

[0033] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0034] The terms "first", "second", etc. in the description and claims of this application are used to distinguish different objects, rather than to describe a specific order of the objects. For example, the first response message and the second response message are used to distinguish different response messages, rather than to describe a specific order of the response messages.

[0035] In the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0036] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" refers to two or more. For example, a plurality of spheres refers to two or more spheres; a plurality of elements refers to two or more elements, etc.

[0037] First, the technical terms involved in the embodiments of the present application are introduced.

[0038] The Kronecker product is a special tensor product in matrix operations and is used to expand two matrices into a larger matrix.

[0039] Random Sample Consensus (Ransac) is an algorithm that calculates the mathematical model parameters of data based on a sample data set containing abnormal data to obtain valid sample data. It was first proposed by Fischler and Bolles in 1981.

[0040] The embodiments of the present application will be described below in conjunction with the accompanying drawings in the embodiments of the present application.

[0041] The embodiments of the present application provide a large component measurement system based on a six - dimensional sensor, as Figure 1 shown, including a laser tracker 1, a six - dimensional sensor 2, a three - dimensional scanner 3, an adapter fixture 4, and a calibration ball array 5. Among them: The three - dimensional scanner 3 is used to scan the calibration ball array or the component to be measured to obtain point cloud data; during the calibration process of the measurement system, the calibration ball array 5 serves as the scanning object of the three - dimensional scanner 3, and the three - dimensional scanner 3 continuously changes its pose to scan the calibration ball array 5 to obtain the ball array point cloud under different scanning poses.

[0042] As Figure 2 shown, the six - dimensional sensor 2 is fixed to the three - dimensional scanner 3 through the adapter fixture 4 and changes its pose together with the three - dimensional scanner 3 during the scanning process of the three - dimensional scanner 3. The adapter fixture 4 is provided with fixed interfaces for the three - dimensional scanner 3 and the six - dimensional sensor 2.

[0043] The laser tracker 1 is set at a position relatively stationary with respect to the calibration ball array 5 and is used to track the six - dimensional sensor 2 with a continuously changing pose and calculate the pose of the six - dimensional sensor 2 relative to the laser tracker 1.

[0044] As Figure 3 shown, the calibration method of the large component measurement system in the embodiments of the present application includes the following steps: S1. Continuously change the scanning pose of the three - dimensional scanner 3 to scan the calibration ball array 5 to obtain the ball array point cloud as Figure 4 shown, assuming that n + 1 groups of ball array point clouds are obtained.

[0045] At the same time, use the laser tracker 1 to obtain the poses of the six - dimensional sensor 2 under different scanning poses, assuming that n + 1 groups of poses are obtained.

[0046] S2. For the above n + 1 groups of poses of the six - dimensional sensor 2 and nProcess a group of spherical array point clouds, specifically as follows: S21. Calculate the relative transformation pose of the six-dimensional sensor 2 between two adjacent measurements, and obtain a total of n groups of relative poses, which form a set A , A . The expression of

[0047] is as follows: is the pose of the six-dimensional sensor in the laser tracker coordinate system during the th scan, where the subscripts and represent adjacent scan numbers; and represent the rotation matrix and translation amount of the relative pose of the six-dimensional sensor, respectively.

[0048] S22. Automatically segment and identify the spherical surfaces in the spherical array point cloud, and fit the sphere centers to obtain n +1 group of spherical array sphere center data. The algorithm for obtaining the spherical array sphere centers from the spherical array point cloud is as follows: Figure 5 S221. Filter and denoise the spherical array point cloud, and remove the planes in the background through Ransac plane recognition; to avoid misidentifying the cross-section of the sphere as a plane, auxiliary judgments such as the number of inliers and normal consistency are required; S222. Use Ransac to fit all the spheres in the remaining spherical array point cloud to obtain the inliers of the spheres; S223. Use the least squares method to perform the best sphere fitting on the above inliers to obtain the spherical array sphere centers.

[0049] S23. Calculate the relative transformation pose of the three-dimensional scanner 3 between two adjacent measurements. Process the above-obtained n +1 group of spherical array sphere centers. Rigidly match the spherical array sphere centers obtained from the+1st measurement of the three-dimensional scanner 3 with the spherical array sphere centers obtained from the i th measurement. The finally obtained transformation matrix is used as the relative pose of the three-dimensional scanner 3, and a total of i +1 group of spherical array sphere centers. A total of n groups of relative poses are obtained, which form a set B :

[0050] Among them, represents the pose of the calibration spherical array in the three-dimensional scanner coordinate system during the th scan, where the subscripts and represent adjacent scan numbers; and They respectively represent the rotation matrix and the translation amount of the relative pose of the 3D scanner.

[0051] S3. As Figure 6 shown, it is a schematic diagram of performing two scans by changing the pose of the 3D scanner. In adjacent two measurements, 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 constitute n a set of the following relational expressions:

[0052] Among them, represents the relative pose between the 3D scanner 3 and the six-dimensional sensor 2, and is set as the calibration parameter to be solved X , then the above formula can be expressed as:

[0053] Among them, and respectively represent the rotation matrix and the translation amount of the relative pose between the 3D scanner 3 and the six-dimensional sensor 2, Expand it to get:

[0054] Use the properties of the Kronecker product to linearize it. Define the function , where the subscript represents the th row and the th column in the matrix. According to the properties of the Kronecker product, there is:

[0055] Among them, the superscript represents the transpose, represents the Kronecker product. Then the formula ([[]] a )( b ) is transformed into:

[0056] Write the formula ([[]] a )( b ) in matrix form:

[0057] Among them, is the coefficient matrix:

[0058] Among them, and respectively represent the rotation matrix and the translation amount of the relative pose of the six-dimensional sensor; and respectively represent the rotation matrix and translation vector of the relative pose of the 3D scanner; the superscript represents transpose, and the symbol represents the Kronecker product. The subscript represents the adjacent scan numbers, represents the identity matrix is a constant term vector:

[0059] is X 's linearized form:

[0060] where, and respectively represent the rotation matrix and translation vector of the relative pose between the 3D scanner and the 6D sensor. The function .

[0061] Based on the measurement errors of the 3D scanner and the 6D sensor, is written as:

[0062] where, and are and 's observed values, i.e., measurement values; and are error corrections, and are and 's adjusted values.

[0063] Using the total least squares method to solve the above relationship, it is rewritten as:

[0064] where, .

[0065] Setting the weight matrix as the identity matrix, the adjustment criterion can be expressed as:

[0066] where, represents calculating the Frobenius norm; represents the matrix 's error in the -th row and the -th column, represents groups of measurement data; the function represents the trace of the matrix; Combined with SVD decomposition, its solution method is as follows: Step 1, construct the matrix

[0067] Step 2, calculate the eigenvalues and eigenvectors of Step 3, select the eigenvector corresponding to its minimum eigenvalue

[0068] Step 4, the solution can be expressed as

[0069] The solution obtained by the above method The rotation matrix part of does not satisfy the orthogonality constraint. Use Schmidt orthogonalization to orthogonalize it to obtain the pose transformation relationship between the 3D scanner 3 and the 6D sensor 2, and complete the calibration.

[0070] Based on the method in the above embodiments, an embodiment of the present application provides an electronic device, as Figure 7 shown. The electronic device includes: a processor (Processor), a communication interface (Communications Interface), a memory (Memory), and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus. The processor can call the logical instructions in the memory to execute the method in the above embodiments.

[0071] In addition, when the logical instructions in the above memory are implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

[0072] Based on the method in the above embodiments, an embodiment of the present application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program runs on the processor, it causes the processor to execute the method in the above embodiments.

[0073] Based on the method in the above embodiments, an embodiment of the present application provides a computer program product. When the computer program product runs on the processor, it causes the processor to execute the method in the above embodiments.

[0074] It can be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), or may also be 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. The general-purpose processor may be a microprocessor or any conventional processor.

[0075] The method steps in the embodiments of the present application may be implemented in a hardware manner or by a processor executing software instructions. The software instructions may be composed of corresponding software modules, and the software modules may be stored in a random access memory (RAM), flash memory, read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), registers, hard disks, removable hard disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may be located in the ASIC.

[0076] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of 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, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. 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 in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0077] It can be understood that the various digital numbers involved in the embodiments of the present application are only for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0078] Those skilled in the art can easily understand that the above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A large component measurement system based on a six-dimensional sensor, characterized in that: include: Laser tracker, six-dimensional sensor, three-dimensional scanner, adapter fixture and calibration ball array; The laser tracker is used to emit laser to track the six-dimensional sensor and obtain the position of the six-dimensional sensor; The six-dimensional sensor is used to reflect the detection laser emitted by the laser tracker and detect its own posture; The three-dimensional scanner is used to scan the calibration spherical array or the component to be measured to obtain point cloud data; The adapter fixture is used to fix the six-dimensional sensor and the three-dimensional scanner together; The positions of the calibration ball array and the laser tracker are relatively static and are used to calibrate the conversion relationship between the six-dimensional sensor and the three-dimensional scanner.

2. A calibration method for a large component measurement system according to claim 1, characterized in that: include: The scanning posture of the 3D scanner is transformed and the calibration spherical array is scanned to obtain multiple sets of spherical array point clouds. At the same time, the laser tracker measures the posture of the 6D sensor under each scanning posture. Get the relative position of the six-dimensional sensor between any adjacent scanning positions and form a set A ; Perform rigid matching on the sphere centers of two adjacent sets of spherical point clouds to obtain the relative position of the 3D scanner between any adjacent scanning positions and form a set B ; The relative position between the 3D scanner and the 6D sensor is used as the calibration parameter to be solved. X ; Build a collection A ,gather B and parameters X The relationship between Linearize the relationship, use the total least squares method to solve the linearized relationship, and orthogonalize the rotation matrix in the solution to obtain the parameters X Linear solution of .

3. The calibration method according to claim 2, characterized in that: The sphere centers of two adjacent groups of spherical point clouds are rigidly matched to obtain the relative position of the 3D scanner between any adjacent scanning positions, specifically: Performing sphere segmentation and sphere center fitting on the spherical lattice point cloud to obtain the sphere center in the spherical lattice point cloud; The sphere centers in two adjacent groups of spherical array point clouds are rigidly matched to obtain the relative posture of the 3D scanner between adjacent scanning postures.

4. The calibration method according to claim 3, characterized in that: The spherical point cloud is segmented and fitted with the sphere center, specifically: Filtering and denoising the spherical point cloud, using a random sampling consensus algorithm to identify and remove planes in the spherical point cloud; The sphere in the remaining spherical lattice point cloud is fitted using a random sampling consensus algorithm to obtain the inner points of the sphere; The sphere center is obtained by performing the best sphere fitting on the interior points using the least square method.

5. The calibration method according to claim 2, characterized in that: The collection A Specifically: in, For the The position and posture of the six-dimensional sensor in the laser tracker coordinate system during the scan, where the subscript and Indicates adjacent scan numbers.

6. The calibration method according to claim 2, characterized in that: The collection B Specifically: in, Indicates The position and posture of the spherical array in the 3D scanner coordinate system are calibrated during the scan. and Indicates adjacent scan numbers.

7. The calibration method according to claim 2, characterized in that: Building a collection A ,gather B and parameters X The relationship between: .

8. The calibration method according to claim 2, characterized in that: Linearize the relationship based on the Kronecker product: in, is the coefficient matrix: in, and They represent the rotation matrix and translation of the relative position of the six-dimensional sensor respectively; and Respectively represent the rotation matrix and translation of the relative position of the 3D scanner; Indicates transposition, symbol represents the Kronecker product, the subscript Indicates adjacent scan numbers. represents the unit matrix; is a constant term vector: for X The linearized form of is: in, and Respectively represent the rotation matrix and translation of the relative position between the 3D scanner and the 6D sensor, and the function , where the subscript Indicates the matrix Row and List.

9. The calibration method according to claim 8, characterized in that: Based on the measurement error between the 3D scanner and the 6D sensor, writing: in, and for and The observed value, i.e. the measured value; and is the error correction number, and for and The adjustment value of .

10. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 2 to 10.

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