Public transit point optimized layout method based on combined measurement of laser tracking system and electronic theodolite system

Abstract

The invention discloses a public transfer point optimization layout method based on combined measurement of a laser tracking system and an electronic theodolite system. The method comprises the following steps: acquiring an initial candidate point set; screening the initial candidate point set to obtain a total-station common-view candidate point set; based on the intersection angle geometric constraint and robust estimation theory, performing geometric configuration robustness evaluation on the total-station common-view candidate point set, eliminating potential error sensitive points, and obtaining a robust candidate point set; performing precision evaluation on the robust candidate point set to obtain a high-precision candidate point set; and according to a hierarchical optimization strategy, performing hierarchical processing on the high-precision candidate point set, and determining an optimal public transfer point set. According to the method, the coordinate conversion quality can be improved, error accumulation is effectively inhibited, the robustness of a combined measurement system is improved, and efficient point distribution guidance is provided for field collaborative measurement.

Description

Technical Field

[0001] This invention belongs to the field of large-size measurement technology, and in particular relates to a method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system. Background Technology

[0002] When laser tracking systems and electronic theodolite systems are used for collaborative measurement and data sharing in the assembly of large components, in order to achieve stable interoperability of measurement data under different coordinate systems, it is necessary to set up reasonable common transfer stations in the measurement field to ensure the accuracy and stability of three-dimensional coordinate transformation.

[0003] Currently, many problems exist in achieving stable data exchange: at large component assembly sites, the tooling fixtures and the shape of the components themselves can cause complex physical obstructions, resulting in the loss of some common viewpoints; the layout of points is too concentrated, approximately collinear, or approximately coplanar, leading to unstable and erroneous calculation transformation parameters; electronic theodolite systems are very sensitive to intersection angles, and it is easy to overlook whether the layout points are in the instrument's error-sensitive zone, leading to the introduction of gross errors and affecting the coordinate transformation results; the differences in measurement uncertainty of the measuring instrument at different locations in space are not fully considered, and even if the measurement points are evenly distributed in space, once the target point falls into an area with high measurement uncertainty, it will still lead to a decrease in the overall accuracy of the measurement network.

[0004] To address these issues, academia and industry have proposed several methods for selecting common points. Some methods utilize area analysis, but these are inefficient and struggle to guarantee coordinate transformation accuracy when the number of common points is small. Other methods employ quadrant distribution-based selection, which, while offering a wide and uniform distribution of selected common points, neglects the impact of measurement uncertainty. Furthermore, existing technologies have significant limitations: they fail to consider physical obstructions, exhibit uneven accuracy, and have limited applicability, making it difficult to achieve a balance among multiple key constraints. Therefore, current technology lacks a systematic method for deploying common transfer stations that simultaneously considers measurement accessibility (tooling obstruction), measurement accuracy, and spatial distribution of points, ensuring the accuracy and stability of transfer stations in the measurement field. Summary of the Invention

[0005] To address the aforementioned technical issues, this invention proposes an optimized layout method for common transfer stations based on a combination of laser tracking system and electronic theodolite system. This method can improve coordinate transformation quality, effectively suppress error accumulation, enhance the robustness of the combined measurement system, and provide efficient point layout guidance for on-site collaborative measurement.

[0006] To achieve the above objectives, this invention provides a method for optimizing the layout of public transit points based on a combination of laser tracking system and electronic theodolite system measurements, comprising:

[0007] Obtain the initial set of candidate points;

[0008] The initial candidate point set is filtered to obtain a set of candidate points that are visible to the entire site.

[0009] Based on the intersection angle geometric constraint and robust estimation theory, the geometric configuration robustness assessment and potential gross error screening of the set of common-view candidate points of the whole station are carried out to obtain a robust candidate point set.

[0010] The robust candidate point set is subjected to accuracy evaluation to obtain a high-precision candidate point set;

[0011] According to the hierarchical optimization strategy, the high-precision candidate point set is processed in a hierarchical manner to determine the optimal common transfer station set.

[0012] Optionally, obtaining the initial candidate point set includes:

[0013] Based on the three-dimensional geometric model of the object under test, the outer envelope of the three-dimensional geometric model is discretized with high density to obtain a dataset of discrete points representing the shape of the object as the initial candidate point set.

[0014] Optionally, filtering the initial candidate point set to obtain a set of candidate points for the entire site's common view includes:

[0015] Based on the geometric mapping principle of the HPR algorithm, the points in the initial candidate point set are mapped to the visible space of each measurement station to obtain the independent visible point set of each station.

[0016] Calculate the spatial geometric distance between different independent viewpoint sets and compare it with a preset tolerance threshold to obtain the set of candidate viewpoints for the entire station.

[0017] Optionally, based on intersection angle geometric constraints and robust estimation theory, the geometric configuration robustness assessment and potential gross error screening are performed on the set of common-view candidate points across the entire station to obtain a robust candidate point set, including:

[0018] Based on the geometric relationship of the bi-station intersection measurement of the electronic theodolite, calculate the intersection angle of each point in the set of candidate points for common view of the whole station;

[0019] The error-sensitive area of ​​the electronic theodolite system is determined based on the intersection angle;

[0020] Based on the robust estimation theory, points within the error-sensitive region are assigned low weights or removed to obtain the robust candidate point set.

[0021] Optionally, the accuracy of the robust candidate point set is evaluated to obtain a high-precision candidate point set, including:

[0022] Accurate measurement error models for the laser tracker and the electronic theodolite were established respectively;

[0023] Based on the precise measurement error model, the measurement uncertainty of each point in the robust candidate point set is calculated according to the Monte Carlo simulation method to obtain the uncertainty index of each point;

[0024] The uncertainty index is compared with a preset threshold, and points that meet the accuracy requirements are retained to form a high-precision candidate point set.

[0025] Optionally, according to a hierarchical optimization strategy, the high-precision candidate point set is processed in a hierarchical manner to determine the optimal common transfer station set, including:

[0026] Based on the number of shared measurement stations, the points in the high-precision candidate point set are divided into primary points and secondary points. Primary points are points that are shared by three or more laser tracker stations, and secondary points are points that are shared by two laser tracker stations.

[0027] Prioritize the deployment of primary points to construct a global measurement network. When the number of primary points is insufficient, supplement with secondary points.

[0028] Based on the connection requirements of the electronic theodolite system, common points for coordinate unification should be set up in the global measurement network, and at least three common points should be set up.

[0029] Based on the deployment results, the optimal set of public transfer stations is determined.

[0030] Compared with the prior art, the present invention has the following advantages and technical effects:

[0031] This invention addresses the shortcomings of traditional methods that neglect tooling obstruction and component shape, leading to "unmeasurable" points, by introducing a Hidden Point Removal (HPR) algorithm for measurement visibility analysis in laser tracking and electronic theodolite systems used in large component assembly processes. It utilizes robust estimation theory for data processing to eliminate points with potential gross errors, compensating for the gross error problem inherent in electronic theodolite systems due to their sensitivity to intersection angles. Independent error models for both the laser tracker and the electronic theodolite are established, and uncertainty assessment is performed using the Monte Carlo method, enabling the selection of high-precision common points. Compared to traditional layout methods relying on manual experience, this method, through a hierarchical optimization strategy, effectively ensures coordinate transformation quality and suppresses error accumulation in the common point layout. Attached Figure Description

[0032] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0033] Figure 1 This is a flowchart of a method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system according to an embodiment of the present invention;

[0034] Figure 2 This is a schematic diagram illustrating the measurement principle of an embodiment of the present invention;

[0035] Figure 3 This is a schematic diagram of the point measurement principle of the electronic theodolite system according to an embodiment of the present invention;

[0036] Figure 4 This is a schematic diagram of the optimal set of common transfer stations in an embodiment of the present invention, wherein (a) is a common transfer station for dual-station laser trackers, (b) is a common transfer station for 3-station / 5-station laser trackers, and (c) is a common transfer station for laser trackers and electronic theodolites. Detailed Implementation

[0037] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0038] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0039] This embodiment proposes an optimized layout method for public transfer stations based on a combination of laser tracking system and electronic theodolite system measurements, such as... Figure 1 As shown, the specific steps include:

[0040] Obtain the initial set of candidate points;

[0041] The initial candidate point set is filtered to obtain the set of candidate points that are visible to the entire site;

[0042] Based on the geometric constraints of intersection angles and robust estimation theory, the geometric configuration robustness of the set of common-view candidate points of the whole station is evaluated and screened to obtain a robust candidate point set.

[0043] The accuracy of the robust candidate point set is evaluated to obtain the high-precision candidate point set.

[0044] Based on the hierarchical optimization strategy, the high-precision candidate point set is processed in a hierarchical manner to determine the optimal common transfer station set.

[0045] Specifically, to address the issue of physical occlusion, gross errors, and network accuracy affecting coordinate transformation quality in a combined collaborative measurement field, point cloud screening is performed by integrating measurement visibility analysis (HPR algorithm), robust estimation (eliminating gross errors), and measurement uncertainty constraints to achieve a high-precision and highly robust optimized layout of public transfer stations.

[0046] Furthermore, obtaining the initial candidate point set includes:

[0047] Based on the three-dimensional geometric model of the object under test, the outer envelope of the three-dimensional geometric model is discretized with high density to obtain a dataset of discrete points representing the shape of the object as the initial candidate point set.

[0048] Specifically, the initial candidate point set is obtained by importing the theoretical model of the large component and related tooling fixtures, and then performing high-density discretization on its shape envelope to obtain a complete dataset of original discrete points representing the object's shape. This dataset serves as the data foundation for subsequent visibility analysis, gross error removal, and accuracy optimization, and is thus the initial candidate point set. The theoretical model is a three-dimensional geometric model, essentially a three-dimensional geometric model based on the large component and workpiece, whose shape is then processed.

[0049] Furthermore, the initial candidate point set is filtered to obtain the set of candidate points that are visible across the entire site, including:

[0050] Based on the geometric mapping principle of the HPR algorithm, the points in the initial candidate point set are mapped to the visible space of each measurement station to obtain the independent visible point set of each station;

[0051] Calculate the spatial geometric distance between different independent viewpoint sets and compare it with a preset tolerance threshold to obtain a set of candidate viewpoints for the entire site.

[0052] Specifically, a set of candidate points visible across the entire station is obtained through screening: Based on the established dataset of instrument station locations and component shape points, i.e., the initial candidate point set, the Hidden Point Removal (HPR) algorithm is used to transform the 3D visibility problem into a convex hull calculation problem through spherical flip transformation, thereby calculating the independent set of visible points for each station. Subsequently, by calculating the spatial geometric distance between different point sets and comparing it with a preset tolerance threshold (in this embodiment, the threshold is preset to 0.01 mm), a set of candidate points observable by all stations is selected.

[0053] More specifically, using the Hidden Point Removal (HPR) algorithm, the 3D visibility problem is transformed into a convex hull calculation problem through a spherical flip transformation, thereby calculating the independent set of visible points for each station, including:

[0054] Assume there are within the measurement field The measuring instrument has the following measurement station: The geometric shape of the object being measured is composed of a set of points in three-dimensional space. Discretized representation, the geometric mapping formula of the HPR algorithm can be expressed as:

[0055] ;

[0056] In the formula, For Let O be the set of coordinates of points translated from the origin. For measurement station Point of view The unit observation vector, For a set of points greater than the set of points in space The circumradius of the sphere is a constant. Based on this formula, the set of points can be... From the measurement station "Flip" along the observation direction to a radius of The region outside the sphere is mapped to form a set of points. .

[0057] Geometric mapping point set The three-dimensional convex hull Defined as:

[0058] ;

[0059] A set of vertices and a set of triangular facets Composition, in which:

[0060] ;

[0061] If the original data points From the measurement station It can be seen that the mapping point convex hull A vertex Therefore, the measurement station set of viewpoints for:

[0062] ;

[0063] Let the set of spatially visible points of all survey stations be . To determine any To find the common viewpoint set among k stations, we need to calculate the intersection of their corresponding viewpoint sets. For a given set of k stations, the index set is... Their common viewpoint set It consists of the intersection of these visible point sets. To determine a specific shared viewpoint, the candidate point set is traversed. Each point in and calculate the points To the rest The nearest point in the set of visible points of each measurement station geometric distance :

[0064] ;

[0065] set up This is a preset tolerance threshold. If point The shortest distance to the set of points of the other measurement stations all satisfy the following conditions. Then, this point is determined to be the common viewpoint of k stations:

[0066] ;

[0067] By traversing all possible... By combining these elements, we can obtain different sets of shared viewpoints from multiple stations, which together form a complete spatial shared view relationship network. .

[0068] Based on intersection angle geometric constraints and robust estimation theory, the geometric robustness of the common-view candidate point set of the entire station is evaluated and potential gross errors are screened, resulting in a robust candidate point set including:

[0069] Based on the geometric relationship of the bi-station intersection measurement of the electronic theodolite, calculate the intersection angle of each point in the set of candidate points for common view of the whole station;

[0070] Determine the error-sensitive area of ​​the electronic theodolite system based on the intersection angle;

[0071] Based on robust estimation theory, points within the error-sensitive region are assigned low weights or removed to obtain a robust candidate point set.

[0072] Specifically, a robust set of candidate points is selected and eliminated after removing geometric gross errors; geometric constraints on the intersection angle are introduced, that is, the actual intersection angle is required to be... Must be within a reasonable threshold range To avoid a sharp amplification of errors caused by excessively small intersection angles (parallel lines of sight) or excessively large intersection angles (shortened baseline), robust estimation theory (such as the Huber function) is introduced to suppress the influence of outliers. Observations in error-sensitive regions (close to or exceeding a threshold) are weighted or removed, thereby eliminating unreliable data points caused by the specific limitations of electronic theodolites. This results in a robust candidate point set, ensuring high reliability of the point set for the next step.

[0073] More specifically, the HPR algorithm solves the workpiece occlusion problem, ensuring that all points in the resulting candidate point set are observable from the relevant instrument stations. Addressing the geometric accuracy issue of bi-station intersection measurements with electronic theodolites, points that are visible but may lead to significant measurement errors due to poor intersection angles are eliminated. To ensure point visibility, the measurement geometry is further robust within this set of visible points, resulting in a visible and reliable candidate point set. The intersection angle is introduced to identify unreliable data, while robust estimation theory handles this unreliable data to ensure robust results.

[0074] Furthermore, the accuracy of the robust candidate point set is evaluated to obtain a high-precision candidate point set, including:

[0075] Accurate measurement error models for the laser tracker and the electronic theodolite were established respectively;

[0076] Based on the accurate measurement error model, the measurement uncertainty of each point in the robust candidate point set is calculated according to the Monte Carlo simulation method, and the uncertainty index of each point is obtained.

[0077] The uncertainty index is compared with a preset threshold, and points that meet the accuracy requirements are retained to form a high-precision candidate point set.

[0078] Specifically, a set of available candidate points that meet the accuracy constraints is selected. After satisfying visibility requirements and eliminating gross errors, the remaining point cloud is further refined and optimized. The point cloud is voxelized to improve computational efficiency, resulting in a set of candidate points. Then, precise measurement error models for both the laser tracker and the electronic theodolite are established. Using the Monte Carlo method, numerous repeated simulation measurements are performed based on the error models to calculate the measurement uncertainty of each candidate point. Finally, based on preset accuracy thresholds (in this embodiment, the uncertainty of the tracker's measurement points is less than 0.05 mm, and the uncertainty of the theodolite's measurement points is less than 0.1 mm), a high-precision candidate point set is obtained by selecting a set of points that simultaneously meet the accuracy requirements of both systems.

[0079] More specifically, voxelization of the point cloud is performed to improve computational efficiency, resulting in a candidate point set including:

[0080] Let the set of common point clouds among all stations be . The 3D space containing the point cloud is divided into a uniformly sized voxel mesh, with voxel side lengths of... Establish a voxelized mathematical model:

[0081] ;

[0082] In the formula: Is the index as The set of points contained within a voxel unit. Let be the integer index of the voxel on the three coordinate axes. The center point of the voxel unit. This is a set of voxelized points. By using... As The method of selecting candidate points for the interior point set, which uses a single point to represent a partial point cloud, improves computational efficiency to some extent.

[0083] Establishing accurate measurement error models for laser trackers and electronic theodolites includes:

[0084] The laser tracker uses a spherical coordinate measurement model; the instrument measures the target point... The observed values ​​include distance Horizontal angle and vertical angle , forming polar coordinates The measurement principle is as follows Figure 2 As shown.

[0085] In coordinate measurement systems, measured values ​​are generally given based on Cartesian coordinates, therefore they need to be calculated using the above formula. Measurements in Cartesian coordinate system .

[0086] ;

[0087] Based on the measurement principle of distance and angle in laser trackers, a suitable probability distribution function is assigned to the uncertainty characteristics of each sensor. This paper assumes that each sensing unit is independent of each other and follows a normal distribution with a mean of 0. Therefore, the normal distribution model of the random error measured by each sensor unit can be obtained as follows:

[0088] ;

[0089] in, The standard deviation of the distance measurement error is the reference component. This represents the linear variation component of the standard deviation of the distance measurement error; and The standard deviations of the measurement errors for horizontal and vertical angles are respectively... In summary, the measurement model for the laser tracker can be obtained as follows:

[0090] ;

[0091] The basic measurements of an electronic theodolite only include the horizontal angle. with vertical angle The instrument itself does not provide a length reference. Its length reference is indirectly established by measuring the two endpoints of a standard reference scale using a dual-station electronic theodolite system and performing geometric calculations. After establishing the length reference, the electronic theodolite system performs spatial point measurements using the dual-station skew intersection method. Let the projected distance between the mutual aiming axes of the two theodolites T1 and T2 on the horizontal plane be b, the height difference between the two stations be h, and the observed value for target point P be... The point measurement principle of the electronic theodolite system is as follows: Figure 3 As shown, the electronic theodolite system is established with the coordinates of electronic theodolite T1 as the origin, the mutual projection direction of T1-T2 as the x-axis, and the horizontal and vertical upward direction as the z-axis. The measurement coordinate system is established using the right-hand rule. .

[0092] Using the method of non-plane intersection measurement, through Calculate the coordinates of the target point P in the measurement coordinate system using known quantities:

[0093] ;

[0094] The measurement errors of an electronic theodolite mainly include systematic errors inherent to the instrument, operational errors, and errors from other factors. The systematic errors inherent to the instrument mainly include angle indication errors and horizontal axis tilt errors. These systematic errors follow a normal distribution, and during the measurement process, they manifest as angular measurement error components in the horizontal and pitch directions. The angular error components of the collimation axis in actual measurement are:

[0095] ;

[0096] The operational error of a theodolite mainly stems from the aiming error of the human eye. Typically, the limit of human eye resolution is... When the distance between the theodolite and the target varies, the visual magnification of the theodolite system also changes accordingly. Let the visual magnification of the theodolite system be A, where A is the tangent of the angle subtended by the image of the object formed by the theodolite's visual magnification system at the human eye. The tangent of the angle subtended by the object by the human eye when the object is directly observed. The ratio is calculated using the following formula:

[0097] ;

[0098] In the formula The limit of human eye resolution is Where d is the minimum resolution of the target object, and L is the distance from the theodolite to the target. Therefore, the aiming error of the line of sight in actual measurement is:

[0099] ;

[0100] Besides the instrument's systematic and operational errors, there are other factors that cause errors, such as those influenced by environmental factors. Environmental compensation deviation errors are caused by the unevenness or fluctuation of temperature, pressure, and humidity. .

[0101] The above errors are independent of each other. According to the law of error propagation, the total error of the electronic theodolite is:

[0102] ;

[0103] Using the Monte Carlo method, a large number of repeated simulation measurements were performed based on the error model to calculate the measurement uncertainty for each candidate point, including:

[0104] In this paper, the Monte Carlo method is used to evaluate the measurement uncertainty. Let the number of repeated measurements be N=1000, and the result of a single measurement be denoted as... The mean of the measurements can be expressed as:

[0105] ;

[0106] The measurement uncertainty can be calculated using the root mean square (RMS) based on the residuals between the mean and each measurement.

[0107] ;

[0108] in, This is the measurement uncertainty index obtained from Monte Carlo simulation. In multi-system collaborative measurements, its judgment criteria are as follows:

[0109] ;

[0110] and These are the point uncertainty thresholds for the two systems, respectively. To meet the measurement uncertainty requirements, a laser tracking system can measure the set of candidate points. The set of selectable points that can be measured by an electronic theodolite system to meet the measurement uncertainty requirements.

[0111] Furthermore, based on the hierarchical optimization strategy, the high-precision candidate point set is processed in a hierarchical manner to determine the optimal set of common transfer stations, which includes:

[0112] Based on the number of shared measurement stations, the points in the high-precision candidate point set are divided into primary points and secondary points. Primary points are points that are shared by three or more laser tracker stations, and secondary points are points that are shared by two laser tracker stations.

[0113] Prioritize the deployment of primary points to construct a global measurement network. When the number of primary points is insufficient, supplement with secondary points.

[0114] Based on the connection requirements of the electronic theodolite system, common points for coordinate unification should be set up in the global measurement network, and at least three common points should be set up.

[0115] Based on the deployment results, the optimal set of public transit points is determined, as illustrated in the diagram below. Figure 4 As shown in (a)-(c).

[0116] Specifically, the optimal set of common relocation points is determined; the remaining points are then processed in a hierarchical manner: First, points that can be viewed by three or more laser tracker base stations are selected to build a robust global network and avoid error accumulation; second, when there are insufficient first-level points, points that are only observed by two stations are introduced to ensure the complete construction of the laser tracking system network; finally, after the global network is built, common points for connecting the electronic theodolite system are deployed, and at least three points are used for coordinate unification, ultimately determining the optimal set of common relocation points.

[0117] More specifically, the remaining points refer to the set of points retained after the original discrete point dataset has been processed by "visual filtering", "gross error filtering" and "high precision filtering" in sequence, that is, the set of public transfer stations to be selected.

[0118] Primary points are the highest priority points in the hierarchical processing, meaning points that can be seen by three or more laser tracker base stations. These points are preferred because they can be used to build the most robust global network and effectively "avoid error accumulation." Only when the number of these primary points is insufficient will secondary points (e.g., points seen by only two stations) be introduced as a supplement.

[0119] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system, characterized in that, include: Obtain the initial set of candidate points; The initial candidate point set is filtered to obtain a set of candidate points that are visible to the entire site. Based on the intersection angle geometric constraint and robust estimation theory, the geometric configuration robustness assessment and potential gross error elimination of the set of common-view candidate points of the whole station are carried out to obtain a robust candidate point set. The robust candidate point set is subjected to accuracy evaluation to obtain a high-precision candidate point set; According to the hierarchical optimization strategy, the high-precision candidate point set is processed in a hierarchical manner to determine the optimal common transfer station set.

2. The method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system as described in claim 1, characterized in that, Obtaining the initial candidate point set includes: Based on the three-dimensional geometric model of the object under test, the outer envelope of the three-dimensional geometric model is discretized with high density to obtain a dataset of discrete points representing the shape of the object as the initial candidate point set.

3. The method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system as described in claim 1, characterized in that, Filtering the initial candidate point set to obtain the site-wide common-view candidate point set includes: Based on the geometric mapping principle of the HPR algorithm, the points in the initial candidate point set are mapped to the visible space of each measurement station to obtain the independent visible point set of each station. Calculate the spatial geometric distance between different independent viewpoint sets and compare it with a preset tolerance threshold to obtain the set of candidate viewpoints for the entire station.

4. The method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system as described in claim 1, characterized in that, Based on intersection angle geometric constraints and robust estimation theory, the geometric configuration robustness of the set of common-view candidate points across the entire station is evaluated and screened to obtain a robust candidate point set including: Based on the geometric relationship of the bi-station intersection measurement of the electronic theodolite, calculate the intersection angle of each point in the set of candidate points for common view of the whole station; The error-sensitive area of ​​the electronic theodolite system is determined based on the intersection angle; Based on the robust estimation theory, points within the error-sensitive region are assigned low weights or removed to obtain the robust candidate point set.

5. The method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system as described in claim 1, characterized in that, The accuracy evaluation of the robust candidate point set to obtain a high-precision candidate point set includes: Accurate measurement error models for the laser tracker and the electronic theodolite were established respectively; Based on the precise measurement error model, the measurement uncertainty of each point in the robust candidate point set is calculated according to the Monte Carlo simulation method to obtain the uncertainty index of each point; The uncertainty index is compared with a preset threshold, and points that meet the accuracy requirements are retained to form a high-precision candidate point set.

6. The method for optimizing the layout of public transfer stations based on a combination of laser tracking system and electronic theodolite system as described in claim 1, characterized in that, According to the hierarchical optimization strategy, the high-precision candidate point set is processed in a hierarchical manner to determine the optimal set of public transfer stations, including: Based on the number of shared measurement stations, the points in the high-precision candidate point set are divided into primary points and secondary points. Primary points are points that are shared by three or more laser tracker stations, and secondary points are points that are shared by two laser tracker stations. Prioritize the deployment of primary points to construct a global measurement network. When the number of primary points is insufficient, supplement with secondary points. Based on the connection requirements of the electronic theodolite system, common points for coordinate unification should be set up in the global measurement network, and at least three common points should be set up. Based on the deployment results, the optimal set of public transfer stations is determined.

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