A positioning method and device for use in a three-dimensional spatial positioning system

Abstract

This application relates to the field of high-precision spatial three-dimensional positioning systems, specifically disclosing a positioning method, including: arranging n calibration rods within a system, and setting m scanning stations within the system; acquiring multiple rotation angles as the m scanning stations scan through the n calibration rods; and obtaining intrinsic parameter calibration results and extrinsic parameter calibration results based on the multiple rotation angles, the parameters of sensors on the n calibration rods, the parameters of laser scanning units on the m scanning stations, and the lengths of the n calibration rods. A positioning method is also disclosed, including: determining multiple different scanning station layout samples, each scanning station layout sample defining the coordinates of multiple scanning stations within the measurement space; and determining a target scanning station layout sample from the multiple scanning station layout samples according to a station layout optimization fitness function, wherein the target scanning station layout sample satisfies preset conditions. The solution of this application is beneficial for rapid, efficient, high-precision, and highly stable measurement of the overall configuration of a product.

Description

Technical Field

[0001] This application relates to the technical field of high-precision spatial three-dimensional positioning systems, and in particular to a positioning method and device applied to spatial three-dimensional positioning systems. Background Technology

[0002] The high-precision spatial 3D positioning system is a novel non-orthogonal coordinate measurement system that combines photoelectric theodolite spatial angle forward intersection measurement with GPS positioning principles. It can be applied to the assembly process of large equipment. Based on a multi-station network measurement mode, the high-precision spatial 3D positioning system realizes 3D coordinates and six-degree-of-freedom pose, possessing advantages such as real-time multi-tasking and dynamic high efficiency. It can meet the needs of multi-station, large-scale, multi-point synchronous online measurement of products, changing the current application situation where the measurement benchmark needs to be transferred and recalibrated as the product is moved. This provides important support for improving the transformation of flexible manufacturing models and equipment innovation for large products in my country. How to improve the accuracy of large-scale spatial 3D information perception for large equipment is a problem that needs to be solved. Summary of the Invention

[0003] This application provides a positioning method for a spatial three-dimensional positioning system, aiming to solve the problem of low accuracy in three-dimensional model construction caused by factors such as variable speed and height instability in traditional manual scanning, and to achieve fast, efficient, high-precision, and highly stable measurement of the overall configuration of the product.

[0004] Firstly, a positioning method for use in a three-dimensional spatial positioning system is provided, including:

[0005] n calibration rods are arranged in the system, and m scanning stations are set in the system;

[0006] Obtain multiple rotation angles at which the m scanning stations scan the n calibration rods respectively;

[0007] Based on the multiple rotation angles, the parameters of the sensors on the n calibration rods, the parameters of the laser scanning units on the m scanning stations, and the lengths of the n calibration rods, the internal parameter calibration results and external parameter calibration results are obtained.

[0008] Compared with the prior art, the solution provided in this application has at least the following beneficial technical effects: it solves the problem of uniformity of global measurement field accuracy uncertainty, and at the same time achieves consistency of positioning accuracy error over a large range, avoiding the increase of error as the range increases, thereby improving the positioning accuracy of the entire measurement system.

[0009] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes:

[0010] Based on the internal parameter calibration results and the external parameter calibration results, the objects within the system are located.

[0011] In conjunction with the first aspect, in some implementations of the first aspect, obtaining the intrinsic parameter calibration results and extrinsic parameter calibration results includes:

[0012] according to The minimum value is used to determine the calibration results of the intrinsic and extrinsic parameters, where,

[0013] —The square of the distance from the upper end point P1 of the calibration rod at the i-th rod position to the laser plane 1 of the j-th scanning station;

[0014] —The square of the distance from the upper end point P1 of the calibration rod at the i-th rod position to the laser plane 2 of the j-th laser scanning device;

[0015] —The square of the distance from the upper end point P2 of the calibration rod at the i-th rod position to the laser plane 1 of the j-th laser scanning device;

[0016] —The square of the distance from the upper end point P2 of the calibration rod at the i-th rod position to the laser plane 2 of the j-th scanning station.

[0017] —The square of the residual of the i-th rod length.

[0018] Based on the rod length constraint, a target point intersection accuracy constraint is introduced. The minimum distance from the laser plane of each scanning station to the target point is used as another constraint condition. This constraint, along with the rod length constraint, acts on the internal and external parameters to be optimized, so that all parameters meet certain accuracy requirements. This provides high-precision internal and external parameters for the entire system, ensuring the measurement accuracy of the system.

[0019] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes:

[0020] Determine multiple different scanning station layout samples, and each scanning station layout sample defines the coordinates of multiple scanning stations in the measurement space;

[0021] Based on the site layout optimization fitness function, a target scanning station layout sample is determined from the plurality of scanning station layout samples, and the target scanning station layout sample satisfies preset conditions.

[0022] It can quickly and automatically calculate the optimal location of scanning stations based on actual scenarios and environmental constraints, achieving the optimal solution for measurement cost, system complexity, and measurement accuracy. It avoids redundancy in the number of scanning stations, solves the problem of uniformity in global measurement field accuracy uncertainty, and achieves consistency in positioning accuracy error over a large area, preventing the error from increasing with the range. It supports 3D graphical display, scene parameter input, import of scene and object model, and constraint parameter setting.

[0023] In conjunction with the first aspect, in certain implementations of the first aspect, determining different multiple scanning station layout samples includes:

[0024] Mutation operations are performed on existing scanning station layout samples, including:

[0025] For the scanning station layout sample X i (g) Select 3 scanning station layout samples X from the existing scanning station layout samples. p1 (g), X p2 (g), X p3 (g), and p1≠p2≠p3≠i, the mutated scanning station layout sample H i (g) is:

[0026] H i (g)=X p1 (g)+F·(X p2 (g)-X p3 (g)), where F is the scaling factor.

[0027] Mutation operations can increase the population size. Controlling the F-value can adjust the algorithm's convergence speed and prevent it from getting trapped in local optima.

[0028] In conjunction with the first aspect, in certain implementations of the first aspect, determining different multiple scanning station layout samples includes:

[0029] Perform a cross-operation on existing scanning station layout samples; the resulting cross-operated scanning station layout sample V i (g) satisfies:

[0030]

[0031] In the formula, cr∈[0,1] is the crossover probability, and rand(0,1) is a random number that follows a uniform distribution on [0,1].

[0032] Crossover operations can increase population diversity.

[0033] In conjunction with the first aspect, in some implementations of the first aspect, the fitness function satisfies:

[0034]

[0035] Where, ε′ i (X) represents the maximum uncertainty of the i-th measurement space, and M is the number of measurement spaces.

[0036] In conjunction with the first aspect, in some implementations of the first aspect, the number of the plurality of scanning station layout samples is (5~10)*m*s, where m is the number of scanning stations in the system and s is the external parameter variable of the scanning station.

[0037] The size of the population affects the convergence speed and reliability of the algorithm. A smaller population size speeds up convergence but is more prone to local convergence or evolution stalling; a larger population size increases the search capability of the solution space and the probability of finding the optimal solution, but it increases the computational load and reduces the convergence speed. Generally, the population size is set between 5 and 10 times the number of parameters to be solved.

[0038] Secondly, a positioning method for use in a three-dimensional spatial positioning system is provided, including:

[0039] Determine multiple different scanning station layout samples, and each scanning station layout sample defines the coordinates of multiple scanning stations in the measurement space;

[0040] Based on the site layout optimization fitness function, a target scanning station layout sample is determined from the plurality of scanning station layout samples, and the target scanning station layout sample satisfies preset conditions.

[0041] In conjunction with the second aspect, in some implementations of the second aspect, the method further includes:

[0042] According to the target scanning station layout sample, multiple scanning stations are deployed within the system, and objects within the system are located.

[0043] Thirdly, an electronic device is provided, the electronic device being used in a three-dimensional spatial positioning system, the electronic device comprising:

[0044] One or more processors;

[0045] One or more memory units;

[0046] The one or more memories store one or more computer programs, the one or more computer programs including instructions that, when executed by the one or more processors, cause the electronic device to perform the method as described in any of the implementations of the first to second aspects above. Attached Figure Description

[0047] Figure 1 This is a schematic structural diagram of a high-precision spatial three-dimensional positioning instrument system software provided in an embodiment of this application.

[0048] Figure 2 This is a schematic structural diagram of the overall framework of a system data integration and processing software provided in an embodiment of this application.

[0049] Figure 3 This is a schematic flowchart illustrating an internal and external parameter calibration method provided in an embodiment of this application.

[0050] Figure 4 This is a schematic flowchart illustrating an internal and external parameter calibration method provided in an embodiment of this application.

[0051] Figure 5 This is a schematic flowchart illustrating a method for optimizing the layout of scanning stations provided in an embodiment of this application.

[0052] Figure 6 This is a schematic flowchart illustrating a method for optimizing the layout of scanning stations provided in an embodiment of this application.

[0053] Figure 7 This is a schematic flowchart of a positioning method applied to a spatial three-dimensional positioning system provided in an embodiment of this application. Detailed Implementation

[0054] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0055] Figure 1 This diagram illustrates a schematic structure of a high-precision spatial three-dimensional positioning system software according to an embodiment of this application. The high-precision spatial three-dimensional positioning system software consists of two parts: system data integration and processing software and an embedded signal acquisition and data processing unit. The system data integration and processing software mainly runs on a data processing and display unit (tablet computer), and its main functions include initial scanning station scene modeling and layout optimization, visualization display; calibration of the scanning station's internal and external parameters; calculation of measurement and scanning results; and communication with the embedded signal acquisition unit. The embedded signal acquisition and data processing software mainly runs on an embedded signal processor, and its main functions include laser plane identification, signal amplification, modulation and filtering, analysis of laser plane time parameters into position parameters, calculation of measurement results, and communication with the system data integration and processing software.

[0056] The system data integration and processing software runs on a tablet computer and includes a data processing display interface, a coordinate integration and calculation module, a parameter calibration module, a system configuration module, and a system database module. It primarily handles the acquisition and calculation of internal and external calibration parameters, receiver information acquisition and 3D coordinate value calculation, communication with external devices, parameter database storage, operational status data monitoring, and graphical point cloud display, thereby ensuring ease of use for operators and real-time monitoring of measurement information. Simultaneously, based on actual scenarios and environmental constraints, it performs rapid and automatic calculation of the optimal location for scanning station layout, resolving the issue of uniformity in global measurement field accuracy uncertainty, and achieving consistency in positioning accuracy error over a large area, preventing errors from increasing with the range.

[0057] For the wireless communication protocol, TCP / IP is adopted. Since TCP / IP is connection-oriented and operates end-to-end, a three-way handshake is required during the connection establishment process between the system data integration and processing software and the data acquisition and processing unit. This makes the connection more reliable, ensures data transmission stability, and better guarantees the accuracy of the data acquired during pose measurement, thus providing better assurance for the stability of the entire measurement system. The wireless communication process and the main functions of each process are shown in the following figure. The sub-functional modules are as follows:

[0058] (1) Communication initialization: Complete the IP address information configuration of the embedded processor corresponding to each photoelectric sensor and start the listening thread.

[0059] (2) Establish connection: Enable command communication between the system data integration and processing software and the embedded processor corresponding to each photoelectric sensor, realize the sending of start and stop commands for data acquisition to the embedded processor, and realize automatic retransmission of commands when the connection is broken, so as to ensure the reliability of the measurement process.

[0060] (3) Data reception: Each thread receives and stores the pulse timing data sent by each embedded signal processor, realizing the traceability of the original data.

[0061] The display module primarily serves to intuitively present the operating status and measurement results of the system data integration and processing software to the user, while also facilitating user operation. The main interface of the system data integration and processing software is logically laid out, as shown in the figure below. The tree diagram on the left side of the interface allows users to view and edit the parameters of each scanning station or embedded module by right-clicking. The menu bar buttons correspond to different sub-windows, enabling the entire system data integration and processing software to perform necessary tasks such as calibrating and setting internal and external parameters, establishing wireless communication, and calculating the spatial pose of the points to be measured in the measurement network. The central image display control is used to display the real-time position information of the target in space. The text box at the bottom of the software is an information prompt window, providing real-time interaction with the user and feedback on the software's operating status and command completion. To enhance the intuitiveness of the coordinate display, the software provides a coordinate line graph display function to show the changes in coordinate values ​​over a period of time.

[0062] To improve the ease of data collection, "Cancel Collection" and "Remove Data" function buttons have been added to the interface. An information prompt bar has also been added at the bottom of the interface to provide real-time feedback on the collection process status to the user.

[0063] In addition, the display module provides an interface for setting the IP address and port number of the system data integration and processing software and the data acquisition and processing unit. After the wireless communication module is running, the system data integration and processing software opens a new thread to continuously listen for connection requests from the data acquisition and processing unit. Once a connection is established with the data acquisition and processing unit, the software opens a new thread specifically responsible for receiving and processing data such as pulse signals transmitted from this data acquisition and processing unit.

[0064] Figure 2 This diagram illustrates a schematic structural diagram of the overall framework of a system data integration and processing software provided in an embodiment of this application. The overall software framework can adopt a three-layer architecture. The presentation layer mainly interacts with the user, accessing corresponding modules such as system intrinsic and extrinsic parameter calibration and coordinate point calculation according to user needs. The business logic layer is the core of the entire system, processing user requests, completing corresponding calculations, and feeding the results back to the presentation layer and establishing a connection with the data access layer. The data access layer implements the saving and reading of important data such as intrinsic and extrinsic parameters and target point coordinate values.

[0065] As the system's measurement principle indicates, the accuracy of internal and external parameter calibration is a key factor affecting the overall measurement accuracy. After all scanning stations are installed, internal and external parameter calibration is required. Internal parameters reflect the structural parameters of each scanning station, describing the initial positions of the two laser planes in each station's coordinate system and providing the initial normal vector of the laser planes. External parameters describe the relative positional relationships between the coordinate systems of each scanning station, unifying all scanning stations to the same world coordinate system. The accuracy of both internal and external parameters directly affects the positioning accuracy of the entire measurement system.

[0066] Figure 3 This is a schematic flowchart of an internal and external parameter calibration method provided in an embodiment of this application. The parameter calibration method can be applied to the positioning of a spatial three-dimensional positioning system. Figure 3 The method shown can use the length of a fixed-length calibration rod as a constraint to achieve joint calibration of the intrinsic and extrinsic parameters of a high-precision spatial three-dimensional positioning instrument. In one possible scenario, the intrinsic and extrinsic parameter calibration can be performed simultaneously, completing the solution of the intrinsic and extrinsic parameters of all scanning stations within the system in a single data acquisition operation.

[0067] In some embodiments, Figure 3 The method shown can be executed through an application. Specifically, the system's intrinsic and extrinsic parameter joint calibration algorithm is packaged into a callable DLL (Dynamic Link Library) and added to the application. During application runtime, the corresponding intrinsic and extrinsic parameter calibration or coordinate calculation functions are called, and the values ​​of the required variables for each function are input to obtain the desired calibration results.

[0068] 110. Arrange n calibration rods in a system with multiple scanning stations.

[0069] 120, obtain multiple rotation angles of m scanning stations scanning n calibration rods respectively.

[0070] The scanning station can form a laser plane using the laser scanning unit mounted on it. Sensors can be installed at both ends of the calibration rod to receive laser timing pulse signals emitted by the laser scanning unit on the scanning station, thereby completing the scanning of the calibration rod by the scanning station. In some embodiments, the signals acquired by the sensors are processed using methods such as "cancel acquisition" and "data removal" to avoid unexpected situations during the acquisition process and to eliminate erroneous data.

[0071] 130. Based on multiple rotation angles, the parameters of sensors on n calibration rods, the parameters of laser scanning units on m scanning stations, and the lengths of n calibration rods, obtain the internal parameter calibration results and external parameter calibration results.

[0072] 130. For example, this can be achieved through a calibration algorithm. The calibration algorithm performs nonlinear iterative optimization on the collected data, obtains the system's intrinsic and extrinsic parameters, and calculates the calibration residuals. In other words, the rotation matrix and translation vector of each scanning station relative to the system coordinate system can be automatically calculated by software.

[0073] In some embodiments, after step 140, the calibration results and calibration residuals can be displayed intuitively in the interface. The calibration results and calibration residuals can be used to evaluate the quality of the calibration results.

[0074] The following is combined Figure 3 and Figure 4 This paper describes a specific implementation method for calibrating intrinsic and extrinsic parameters.

[0075] In the measurement system, each scanning unit introduces nine variables: three intrinsic parameters and six extrinsic parameters. Given the large number of parameters to be optimized, the rod length constraint alone is insufficient to guarantee that all intrinsic and extrinsic parameters converge to a level that meets measurement accuracy requirements. Therefore, in addition to the rod length constraint, a target point intersection accuracy constraint is introduced. This constraint minimizes the distance from the laser plane at each scanning station to the target point as it passes through the laser plane. This constraint, along with the rod length constraint, applies to the intrinsic and extrinsic parameters to ensure that all parameters meet certain accuracy requirements. This provides high-precision intrinsic and extrinsic parameters for the entire system, guaranteeing its measurement accuracy.

[0076] This calibration requires determining the intrinsic and extrinsic parameters of m scanning stations, with n different locations for the calibration poles. To characterize the reachability of each calibration pole position to a scanning station, an n×m marking matrix is ​​introduced. Each row of the matrix represents a calibration pole position during the calibration data acquisition process, and each column represents a different scanning station. The {i,j}-th element of the matrix represents whether the j-th scanning station covers the i-th calibration pole position during the calibration data acquisition process; if it covers it, the element has a value of 1, otherwise it has a value of 0. Let there be k pole positions at the i-th calibration pole position. i The scanning station can cover the area. Since there are two target points to be measured, and each target point has two distance constraints to the laser plane under one scanning station, a single pole position will have 2×2×k. i There are four distance constraints from the point to the laser plane and one rod length constraint. For scanning stations that cannot cover the calibrated rod position, the distance constraints from the four points to the plane are directly set to 0, thus rendering them ineffective and not included in the calculation of the rod length constraint.

[0077] Let the length of the calibration rod be l bar At the i-th calibration point, the coordinates of the two endpoints of the calibration point in the world coordinate system are P1 and P2. Therefore, the residual length of the calibration point can be easily obtained as:

[0078] d res,i =norm(P1-P2)-lbar

[0079] When two laser planes f1 and f2 at any scanning station sweep across any spatial point P, the distances from point P to the two laser planes can be given as follows:

[0080] (1) Solve for the coordinates of point P in the scanning station coordinate system:

[0081] p = R -1 (PT)=[p x p y p z ] T

[0082] (2) Solve for the normal vectors N'1 and N'2 of the laser planes in their own coordinate system when the two laser planes of the scanning station sweep past point P:

[0083] N′1=R θ1 N1=[n′ 1x n′ 1y n′ 1z ] T

[0084] N′2=R θ2 N2=[n′ 2x n′ 2y n′ 2z ] T

[0085] Where N1 and N2 are the normal vectors of the laser plane at the initial position, and R θ1 R θ2 Let be the rotation matrix when the laser plane rotates from its initial position to coincide with point P.

[0086] (3) Calculate the distance from point P to the two laser planes in the scanning station coordinate system:

[0087]

[0088]

[0089] Therefore, the set of constraint equations that can be established at a single calibration rod position is as follows:

[0090]

[0091] Where: i—calibrated pole position number; d 11 ,d 12 ,d 21 ,d 22 — These represent the residual distances from the point to the laser plane when the plane of scanning station 2 sweeps across the two ends of the calibration rod.

[0092] Based on the above analysis, we know that there are 9×m system internal and external parameters and 2×3×n calibration rod endpoint coordinate values, and a total of constraint equations. There are n distance constraints from the point to the laser plane and n rod length constraints. It is easy to see that when the conditions are met... When the number of constraint equations is greater than the number of unknowns, the solution to the equations will converge to a unique solution.

[0093] In some embodiments provided in this application, the iterative optimization process for intrinsic and extrinsic parameters can be a nonlinear least squares optimization process. The Levenberg-Marquardt optimization algorithm is employed. This algorithm combines the advantages of the Gauss-Newton algorithm and gradient descent by modifying the step size factor, while mitigating their shortcomings, resulting in high algorithm stability. The extremum condition of the Levenberg-Marquardt optimization algorithm is:

[0094] Among them, the extreme value condition can be taken as the minimum value, and then substituted into the above formula to obtain the scanning station.

[0095] In the formula: —The square of the distance from the upper end point P1 of the calibration rod at the i-th rod position to the laser plane 1 of the j-th scanning station; —The square of the distance from the upper end point P1 of the calibration rod at the i-th rod position to the laser plane 2 of the j-th laser scanning device; —The square of the distance from the upper end point P2 of the calibration rod at the i-th rod position to the laser plane 1 of the j-th laser scanning device; —The square of the distance from the upper end point P2 of the calibration rod at the i-th rod position to the laser plane 2 of the j-th scanning station.

[0096] Based on the obtained formulas, and substituting them into the formulas in (1) to (3) above, the three intrinsic parameters and three extrinsic parameters of the scanning unit can be calculated. The three intrinsic parameters are the normal directions of the two laser planes of the scanning unit and the angle between the two normal directions. The three extrinsic parameters are the X, Y, and Z coordinates of the scanning unit in the world coordinate system or the system coordinate system.

[0097] To determine the remaining three extrinsic parameters (rotation angles around the X, Y, and Z axes) of the scanning unit, one possible implementation is to place the calibration rod in four different spatial orientations and measure the coordinates of eight different matching points on the two laser planes of the scanning unit. This allows for the calibration of the remaining three extrinsic parameters of the scanning unit. In another possible implementation, the parameters can be solved approximatingly, incorporating constraints such as the front-rear orientation of the calibration rod relative to the scanning unit and minimizing the distance from the calibration point to the epipolar line. Solutions with large errors are then eliminated, ultimately yielding the remaining three extrinsic parameters of the scanning unit.

[0098] Through the above iterative optimization, based on the principle of beam adjustment, and taking the minimum residual of the calibration rod length and the minimum distance from the laser plane to the target point when each laser plane sweeps through the target point as constraints, the internal and external parameters of the system can be determined.

[0099] Figure 5 This is a schematic flowchart illustrating a method for optimizing the layout of scanning stations provided in an embodiment of this application. Figure 5 The method shown can quickly and automatically calculate the layout and position of scanning stations based on actual scenarios and environmental constraints, achieving the optimal solution for measurement cost, system complexity, and measurement accuracy. It avoids redundancy in the number of scanning stations, solves the problem of uniformity in the accuracy uncertainty of the global measurement field, and achieves consistency in positioning accuracy error over a large area, preventing the error from increasing with the range. It supports 3D graphical display, scene parameter input, import of scene and object-under-measure models, and constraint parameter settings.

[0100] 210. Determine multiple different scanning station layout samples, each scanning station layout sample defining the coordinates of multiple scanning stations in the measurement space.

[0101] 220. Based on the site layout optimization fitness function, a target scanning station layout sample is determined from multiple scanning station layout samples. The target scanning station layout sample meets the preset conditions.

[0102] In some embodiments, multiple different scanning station layout samples can be obtained by random generation. Each station layout sample is randomly generated within a defined range, and each scanning station layout sample can represent a station layout scheme.

[0103] In some embodiments, a greater number of scanning station layout samples can be obtained by performing operations such as mutation and / or crossover on existing scanning station layout samples.

[0104] In some embodiments, when the number of scanning station layout samples is too large, multiple scanning station layout samples can be initially screened. Multiple scanning station layout samples with lower fitness values ​​can be selected from the existing scanning station layout samples.

[0105] In some embodiments, the optimal scanning station layout sample can be used as the target scanning station layout sample. In other embodiments, it can be determined whether the maximum measurement uncertainty of the measurement space meets the usage requirements. If so, the target scanning station layout sample is determined.

[0106] The working conditions of the task are optimized by setting the values ​​of control parameters such as sample size, scaling factor, and crossover probability, and by setting an appropriate fitness function. Evolutionary algorithms can effectively explore the feasible solution space probabilistically to obtain optimal solutions. Differential evolutionary algorithm (DEA) is a population-based iterative evolutionary algorithm that uses real-number encoding, has fewer design parameters, and is easy to implement. To effectively solve the scanning station deployment problem using DEA, the deployment problem model needs to be rationally organized according to DEA.

[0107] The following is combined Figure 5 and Figure 6 This paper describes a specific implementation method for calibrating intrinsic and extrinsic parameters.

[0108] Based on the analysis of scanning station layout parameters, the five extrinsic parameter variables of each scanning station can be directly used as a scanning station layout sample for encoding. Thus, each scanning station layout sample X consists of 5N variables from N laser scanning devices, forming a vector of length 5N:

[0109] X = [x1, y1, z1, α1, β1, ..., x i ,y i ,z i ,α i ,β i ,...,x N ,y N ,z N ,α N ,β N ] T

[0110] In optimization computation, the population size affects the convergence speed and reliability of the algorithm. A smaller population size speeds up convergence but is more prone to local convergence or evolution stalling; a larger population size increases the search capability of the solution space and the probability of finding the optimal solution, but it increases the computational load and reduces the convergence speed. Generally, the population size is set between 5 and 10 times the number of parameters to be solved.

[0111] The population update process includes three operations: mutation, crossover, and selection, which update the layout parameters of all scanning station layout samples within the population.

[0112] First, there is the mutation. In the g-th iteration, the scanning station layout sample X is... i (g) Randomly select 3 scanning station layout samples X from the existing scanning station layout samples. p1 (g), X p2 (g), X p3 (g), and p1≠p2≠p3≠, i, then the mutated scanning station layout sample H i (g) is:

[0113] H i (g)=X p1 (g)+F·(X p2 (g)-X p3 (g))

[0114] In the formula, F is a scaling factor used to control the influence of the difference vector. A smaller F value will accelerate the convergence of the algorithm, but it is easy to get trapped in local optima.

[0115] Crossover operations can increase population diversity, resulting in a crossover-prepared scanning station layout sample V. i (g) is as follows:

[0116]

[0117] In the formula, cr∈[0,1] represents the crossover probability, and rand(0,1) is a random number uniformly distributed on [0,1]. The scanning station layout sample V is selected based on the evaluation function. i (g) or X i (g) Sample X for next-generation scanning station layout i (g+1).

[0118] The evaluation function F(X) is as follows:

[0119]

[0120] Where ε'm represents the maximum uncertainty of the m-th measurement space. When the measurement uncertainties of all M subspaces meet the required uncertainty, F(X) is less than 1; when the measurement uncertainty of any subspace does not meet the requirement, F(X) is greater than 1. It is also stipulated that when an individual causes the layout to be located outside the effective installation area, the fitness of that individual is directly set to F(X) = 1e6. When the R-station fails to guarantee the coverage of the target measurement space, the measurement accuracy ε'm = 1e6 of the corresponding measurement subspace is set.

[0121] In population iteration, the search is stopped based on the convergence of the solution to obtain the optimal solution. Two stopping criteria are set here: (1) Stop when the maximum number of iterations Kmax is met. If the current optimal scanning station layout sample does not meet the accuracy requirements of the measurement space, the iteration optimization can be carried out again, or the number of scanning stations can be increased to solve the problem again; (2) Stop the search when the fitness value F≤1 of the optimal scanning station layout sample remains unchanged for K consecutive generations. This scanning station layout sample ensures that the measurement accuracy of all measurement subspaces meets the requirements. This scanning station layout sample is the optimized scanning station layout solution.

[0122] Figure 7This is a schematic flowchart illustrating a positioning method applied to a spatial three-dimensional positioning system, provided in an embodiment of this application. Figure 7 In the illustrated embodiment, before locating objects within the spatial three-dimensional positioning system, the following steps can be performed first: Figure 3 or Figure 4 The internal and external parameter calibration methods shown, and Figure 5 and Figure 6 The method for optimizing the scanning station layout is shown. You can first execute... Figure 5 and Figure 6 The optimization method for the scanning station layout shown is then implemented. Figure 3 or Figure 4 The internal and external parameter calibration method is shown. In some other embodiments, before locating an object within the spatial three-dimensional positioning system, only the internal and external parameter calibration method or only the scanning station layout optimization method may be performed. After layout optimization and / or parameter calibration, the coordinates of the object within the spatial three-dimensional positioning system can be obtained by rotating the scanning station and performing coordinate calculation on the signals collected by the scanning station. A spatial positioning network is formed by laser spatial scanning unit stations. The scanning station emits two fan-shaped light planes, which scan the entire measurement space. The signal processing and calculation are realized through a developed heterogeneous specific photoelectric receiving device, thereby realizing the positioning of the specific target to be measured.

[0123] This application also provides an electronic device, which includes: one or more processors; one or more memories; the one or more memories storing one or more computer programs, the one or more computer programs including instructions, which, when executed by the one or more processors, cause the electronic device to perform the following actions: Figures 3 to 7 The method shown.

[0124] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope defined in the claims of the present invention.

Claims

1. A positioning method applied to a spatial three-dimensional positioning system, characterized in that, The positioning method comprises: arranging n calibration rods in a system, wherein m scanning stations are arranged in the system; obtaining a plurality of rotation angles at which the m scanning stations scan the n calibration rods respectively; obtaining an internal parameter calibration result and an external parameter calibration result according to the plurality of rotation angles, parameters of sensors on the n calibration rods, parameters of laser scanning units on the m scanning stations, and lengths of the n calibration rods; the method further comprises: determining a plurality of different scanning station layout samples, each scanning station layout sample defining coordinates of a plurality of scanning stations in a measurement space; determining a target scanning station layout sample from the plurality of scanning station layout samples according to a station layout optimization fitness function, the target scanning station layout sample satisfying a preset condition; the determining of the plurality of different scanning station layout samples comprises: Perform mutation operations on existing scanning station layout samples, including: mutating the scanning station layout samples. Select 3 scanning station layout samples from the existing scanning station layout samples. , , ,and The mutated scanning station layout sample for: F is a scaling factor; the determining of the plurality of different scanning station layout samples comprises: The existing scanning station layout samples are crossed, and the crossed scanning station layout samples satisfy: wherein is the cross probability, is is a random number subject to a uniform distribution; the fitness function satisfies: wherein, represents the maximum uncertainty of the i-th measurement space, and M is the number of measurement spaces. the obtaining of the internal parameter calibration result and the external parameter calibration result comprises: According to the minimum value, the internal parameter calibration result and the external parameter calibration result are determined, wherein, - the square of the distance from the end point P1 of the i-th bar at the i-th bar position to the laser plane 1 of the j-th scanning station; - the square of the distance from the end point P1 of the i-th rod at the i-th rod position to the laser plane 2 of the j-th laser scanning unit; - the square of the distance from the end point P2 of the i-th rod to the laser plane 1 of the j-th laser scanning unit at the i-th rod position; - the square of the distance from the end point P2 of the i-th bar to the laser plane 2 of the j-th scanning station at the i-th bar position; - square of the i-th stick length residual.

2. The positioning method according to claim 1, characterized in that, the method further comprises: positioning an object in the system according to the internal parameter calibration result and the external parameter calibration result.

3. The positioning method of claim 1, wherein, The number of the plurality of scanning station layout samples is (5-10)×m×s, m is the number of scanning stations in the system, and s is an external parameter variable of a scanning station.

4. An electronic device, comprising: The electronic device is applied to a spatial three-dimensional positioning system, and the electronic device comprises: one or more processors; one or more memories; the one or more memories store one or more computer programs, and the one or more computer programs comprise instructions, which, when executed by the one or more processors, cause the electronic device to perform the method in any one of claims 1 to 3.

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