A method and system for acquiring the overall spatial pose of a bridge erecting machine

Abstract

The method and system for acquiring the overall spatial pose of a bridge erecting machine provided by this invention establishes a global coordinate system with the line connecting the theoretical center points of any two adjacent piers as the origin. Reflective materials are installed on piers of different structures to enhance their reflective characteristics. Two-dimensional point cloud data of piers of different structures within the construction area are collected using a current lidar sensor. After filtering and clustering, the actual center points of the piers of different structures are obtained. The actual center points are matched with the theoretical center points to obtain the pose of the current lidar in the global coordinate system. Then, based on the preset front outrigger reference point and the installation relationship of the lidar outrigger assembly, the dynamic poses of the front, middle, and rear outriggers are determined. Based on the three-point configuration relationship and the displacement of the bridge erecting machine's path, the overall spatial pose of the bridge erecting machine is obtained. Compared to existing technologies, this invention achieves precise positioning through the cooperation of a two-dimensional lidar and reflective structures, improving universality, positioning accuracy, and mapping efficiency while reducing positioning costs.

Description

Technical Field

[0001] This invention relates to the field of engineering machinery positioning technology, and in particular to a method and system for obtaining the overall spatial pose of a bridge erecting machine. Background Technology

[0002] A bridge erecting machine is a device that places prefabricated bridge beams onto prefabricated bridge piers. Bridge erecting machines fall under the category of cranes because their main function is to lift the bridge beams, transport them to their designated positions, and then lower them.

[0003] Currently, the positioning of traditional bridge erecting machines is achieved through intelligent control. One such method is a machine vision-based intelligent construction control method and system for bridge erecting machines. This system uses multiple high-definition cameras mounted on the bridge erecting machine to collect image information from the construction site, constructs a digital twin model of the construction scene, and generates a construction strategy. However, this system has a long preparation phase and is costly.

[0004] The current positioning method has the following drawbacks: High equipment cost: Existing automated positioning equipment is expensive. An automated system includes multiple laser sensors, reflectors, and encoders, with an overall equipment cost of approximately 500,000-600,000 RMB, which is unaffordable for small and medium-sized construction companies. Low mapping efficiency: Existing automated methods rely on manual measurement or specific modeling. Positioning requires pre-deployment of information collection at the construction site, which is time-consuming and cannot directly utilize bridge design CAD drawings for mapping. Poor environmental adaptability: Existing methods are easily affected by the construction environment. Laser sensors may experience signal weakening in low light or dusty environments, leading to decreased positioning accuracy. Errors may exceed 3cm, making it difficult to meet high-precision requirements. This invention uses a reflective structure and dual-radar fusion, combined with Kalman filtering to remove dynamic obstacle interference, achieving millimeter-level positioning accuracy, unaffected by the environment. Limited positioning accuracy: Existing methods cannot meet high-precision requirements. Laser ranging is affected by installation errors, making it difficult to achieve millimeter-level accuracy; while mechanical limit positioning can stabilize the outriggers, it cannot quantify spatial coordinates, and accuracy depends on mechanical tolerances.

[0005] Therefore, providing a method and system for obtaining the overall spatial pose of a bridge erecting machine to solve the above problems is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method for obtaining the overall spatial pose of a bridge erecting machine. This method is logically clear, safe, effective, reliable and easy to operate. It can achieve accurate positioning by using a two-dimensional lidar and a reflective structure in combination, which improves universality, positioning accuracy and mapping efficiency while reducing positioning costs.

[0007] Based on the above objectives, the technical solution provided by the present invention is as follows:

[0008] A method for obtaining the overall spatial pose of a bridge erecting machine includes the following steps:

[0009] Based on the bridge design drawings, obtain the theoretical center point of any two adjacent piers, establish a global coordinate system with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, obtain the theoretical center point of all piers accordingly, and set the front support leg reference point in the global coordinate system.

[0010] Reflective materials were installed on bridge piers of different structures respectively;

[0011] Two-dimensional point cloud data of bridge piers with different structures are collected within the construction area. The two-dimensional point cloud data is then filtered and clustered. The actual center points of the bridge piers with different structures are obtained based on the processed two-dimensional point cloud data.

[0012] The pose of the current lidar sensor in the global coordinate system is obtained by matching the actual center point of the bridge pier with the theoretical center point of the bridge pier for different structures.

[0013] Based on the current pose of the lidar sensor in the global coordinate system, the reference point of the front outrigger, and the preset geometric installation relationship of the lidar outrigger, the dynamic poses of the front, middle, and rear outriggers in the global coordinate system are obtained.

[0014] Based on the dynamic poses of the front, middle, and rear outriggers in the global coordinate system, a three-point configuration relationship and the path displacement of the bridge erecting machine are used to obtain the overall spatial pose of the bridge erecting machine.

[0015] Preferably, the step of obtaining the theoretical center points of any two adjacent piers based on the bridge design drawings, establishing a global coordinate system with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, and setting the front outrigger reference point in the global coordinate system includes the following steps:

[0016] Based on the analysis of the bridge design drawings using the AutoCAD platform, multiple theoretical bridge pier locations were obtained.

[0017] Define the midpoint of the line connecting any two adjacent theoretical center points as the origin of the coordinate system, define the line connecting the theoretical center points as the X-axis, and define the direction perpendicular to the line connecting the theoretical center points as the Y-axis to establish the global coordinate system.

[0018] Convert all bridge pier positions to theoretical coordinates in the global coordinate system, and obtain the theoretical center point of all bridge piers accordingly;

[0019] A reference point for the front outrigger is preset in the global coordinate system.

[0020] Preferably, the installation of reflective materials on bridge piers with different structural structures specifically includes:

[0021] Flexible, highly reflective materials are used to achieve curved surface fitting of cylindrical bridge piers through arc-shaped slots or modular sheaths;

[0022] Highly reflective material was affixed to the front of the rectangular bridge pier and its two sides.

[0023] Preferably, the process of collecting two-dimensional point cloud data of bridge piers with different structures within the construction area, and then filtering and clustering the two-dimensional point cloud data, includes the following steps:

[0024] Two-dimensional point cloud data of the rectangular bridge piers within the construction area are collected. Points with light reflection intensity values ​​higher than the preset reflection intensity threshold are selected based on the light reflection intensity value of each point to construct an initial set of high-reflectivity area points.

[0025] The DBSCAN algorithm is used to perform unsupervised clustering based on the spatial density distribution characteristics of the point cloud in the initial high reflectivity region point set, and to extract multiple high reflectivity region point cloud clusters.

[0026] Preferably, obtaining the actual center points of bridge piers with different structures based on the processed two-dimensional point cloud data includes the following steps:

[0027] Collect the horizontal and vertical coordinates of all points in each highly reflective point cloud cluster, calculate the extreme points of each highly reflective point cloud cluster, form each rectangle aligned with the coordinate axes of the global coordinate system, and take the midpoint of the diagonal of each rectangle as the geometric center point of each highly reflective point cloud cluster.

[0028] By performing two-dimensional straight line fitting on all points in each high-reflectivity point cloud cluster, the main direction vector of each high-reflectivity point cluster is obtained. Taking the geometric center point of each high-reflectivity point cloud cluster as a reference point, a vector pointing from all points in each high-reflectivity point cloud cluster to the center point is constructed. Based on the angle between the main direction vector of each high-reflectivity point cluster and the vector pointing from all points in each high-reflectivity point cloud cluster to the center point, and a preset condition, the spatial affiliation of the high-reflectivity points is determined.

[0029] Traverse the angle between the main direction vectors of any two highly reflective point clusters belonging to the same spatial domain to determine the adjacent sides of the rectangular pier. Enhance the stability of the adjacent sides of the rectangular pier according to the preset dual-column joint constraint strategy, and obtain the intersection point of the adjacent sides of the rectangular pier after the stability enhancement.

[0030] Based on the intersection of the adjacent sides of the rectangular pier after the stability enhancement and the preset standard pier size parameters, the theoretical center point of the rectangular pier is obtained. According to the external parameter calibration of the coordinate system of the lidar and the bridge erecting machine, the coordinate transformation of the theoretical center point of the rectangular pier is performed to obtain the actual center point of the rectangular pier.

[0031] Preferably, the step of collecting two-dimensional point cloud data of bridge piers with different structures within the construction area, filtering and clustering the two-dimensional point cloud data, and obtaining the actual center points of bridge piers with different structures based on the processed two-dimensional point cloud data further includes the following steps:

[0032] Two-dimensional point cloud data of the cylindrical bridge piers in the construction area are collected. Points with light reflection intensity values ​​higher than the preset reflection intensity threshold are selected based on the light reflection intensity value of each point to construct an initial high-reflectivity area point set.

[0033] A linear continuity clustering strategy was adopted to extract multiple high-reflectivity area point cloud clusters based on the continuity of scan line numbers in the initial high-reflectivity area point set.

[0034] The azimuth angles of all points in each point cloud cluster of the high reflectivity area are collected. The average azimuth angle of each point in the point cloud cluster of the high reflectivity area is calculated. The reference azimuth angle of each point in the point cloud cluster of the high reflectivity area is obtained according to the RANSAC algorithm. The measured distance is projected onto the direction of the line connecting the centers of the cylinder based on the average azimuth angle and the reference azimuth angle of each point to obtain the straight-line distance between each point and the center of the cylinder. According to the preset standard pier size parameters, the average azimuth angle of each point, the measured distance and the preset formula, the straight-line distance between each point and the center of the cylinder is compensated to obtain the center distance of each point.

[0035] The center distances of all points are weighted or simply averaged to obtain an estimated value for the center distance of the cylindrical pier. The estimated center distance and the reference azimuth are then converted into Cartesian coordinates to obtain the actual center point of the cylindrical pier.

[0036] Preferably, the step of matching the actual center point of the different structural piers with the theoretical center point of the piers to obtain the current pose of the lidar sensor in the global coordinate system includes the following steps:

[0037] The actual center point of the bridge piers with the theoretical center point of the bridge piers are initially matched according to a preset order.

[0038] An improved ICP algorithm is used to perform a secondary matching between the actual center point of the unmatched bridge piers and the theoretical center point of the bridge piers. Specifically, based on the preset distribution pattern of the bridge piers and the spatial rigid structure, the SVD algorithm is used to obtain the optimal rotation matrix and displacement vector so that the actual center point of the bridge piers with different structures is aligned with the theoretical center point of the bridge piers after the steel body transformation.

[0039] The optimal rotation matrix and displacement vector are defined as the pose of the current lidar sensor in the global coordinate system.

[0040] Preferably, the step of obtaining the dynamic poses of the front, middle, and rear outriggers in the global coordinate system based on the current pose of the lidar sensor, the reference point of the front outrigger, and the preset geometric installation relationship of the lidar outriggers includes the following steps:

[0041] Based on the preset geometric installation relationship of the radar outriggers, the steel body is transformed to obtain the pose of the front outrigger in the radar coordinate system. Based on the pose of the current lidar sensor in the global coordinate system and the pose of the front outrigger in the radar coordinate system, the static pose of the front outrigger in the global coordinate system is obtained.

[0042] Based on the static geometric relationship between the front outrigger, middle outrigger and rear outrigger, the static pose of the middle outrigger and rear outrigger in the global coordinate system is obtained using the static pose of the front outrigger in the global coordinate system as the reference point.

[0043] The path displacement of the bridge erecting machine is collected, and the static pose of the front outrigger in the global coordinate system is dynamically updated and then error compensation is performed to obtain the dynamic pose of the front outrigger, middle outrigger and rear outrigger in the global coordinate system.

[0044] Preferably, the step of obtaining the overall spatial pose of the bridge erecting machine based on the dynamic poses of the front, middle, and rear outriggers in the global coordinate system using a three-point configuration relationship and the path displacement of the bridge erecting machine includes the following steps:

[0045] Using the outrigger as a reference point, the forward direction of the bridge erecting machine is the X-axis, and the direction perpendicular to the forward direction of the bridge erecting machine is the Y-axis. A coordinate system for the entire bridge erecting machine is established, and the coordinate system of the entire bridge erecting machine is converted into the global coordinate system.

[0046] Based on the dynamic pose of the front outrigger, middle outrigger and rear outrigger in the global coordinate system, the coordinates of any component point of the whole machine in the global coordinate system are obtained accordingly, and the orientation angle of the whole machine is obtained based on the path displacement of the bridge erecting machine.

[0047] The coordinates of any component point of the entire machine in the global coordinate system and the orientation angle of the entire machine are defined as the overall spatial pose of the bridge erecting machine.

[0048] A bridge erecting machine overall spatial pose acquisition system includes:

[0049] The global coordinate system module is used to obtain the theoretical center point of any two adjacent piers according to the bridge design drawings, establish a global coordinate system with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, obtain the theoretical center point of all piers accordingly, and set the front support leg reference point in the global coordinate system.

[0050] Reflective material installation module, used to install reflective materials on bridge piers of different structures respectively;

[0051] The actual center point module is used to collect two-dimensional point cloud data of bridge piers with different structures within the construction area, filter and cluster the two-dimensional point cloud data, and obtain the actual center points of bridge piers with different structures based on the processed two-dimensional point cloud data.

[0052] The lidar pose acquisition module is used to match the actual center point of the bridge pier with the theoretical center point of the bridge pier according to the different structural piers, so as to obtain the pose of the current lidar sensor in the global coordinate system.

[0053] The outrigger dynamic pose acquisition module is used to acquire the dynamic poses of the front, middle, and rear outriggers in the global coordinate system based on the pose of the current lidar sensor, the front outrigger reference point, and the preset geometric installation relationship of the lidar outriggers.

[0054] The overall spatial pose acquisition module of the bridge erecting machine is used to obtain the overall spatial pose of the bridge erecting machine by adopting the three-point configuration relationship and the path displacement of the bridge erecting machine based on the dynamic pose of the front, middle and rear outriggers in the global coordinate system.

[0055] The method for obtaining the overall spatial pose of a bridge erecting machine provided by this invention establishes a global coordinate system with the line connecting any two adjacent piers' theoretical center points as the origin, and enhances the reflective characteristics of piers with different structures by installing reflective materials. Two-dimensional point cloud data of piers with different structures are collected from the construction area using a current lidar sensor. After filtering and clustering, the actual center points of the piers with different structures are obtained. The actual center points are matched with the theoretical center points to obtain the pose of the current lidar in the global coordinate system. Then, the dynamic poses of the front, middle, and rear outriggers are determined based on the preset front outrigger reference point and the installation relationship of the lidar outrigger assembly. Based on the three-point configuration relationship and the bridge erecting machine's path displacement, the overall spatial pose of the bridge erecting machine is obtained.

[0056] Compared to existing technologies, this invention achieves precise positioning by combining two-dimensional lidar and reflective structures, improving universality, positioning accuracy, and mapping efficiency while reducing positioning costs.

[0057] The present invention also provides a system for obtaining the overall spatial pose of a bridge erecting machine. Since it belongs to the same technical concept as the method and solves the same technical problem, it should have the same beneficial effects, and will not be described in detail here. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A flowchart illustrating a method for acquiring the overall spatial pose of a bridge erecting machine, as provided in an embodiment of the present invention;

[0060] Figure 2 A flowchart of step S1 provided in an embodiment of the present invention;

[0061] Figure 3 This is a flowchart of step S3 for obtaining the actual center point of the rectangular bridge pier, provided in an embodiment of the present invention.

[0062] Figure 4 This is a flowchart of step S3 for obtaining the actual center point of the cylindrical bridge pier, provided in an embodiment of the present invention.

[0063] Figure 5 A flowchart of step S4 provided in an embodiment of the present invention;

[0064] Figure 6 A flowchart of step S5 provided in an embodiment of the present invention;

[0065] Figure 7 A flowchart of step S6 provided in an embodiment of the present invention;

[0066] Figure 8 This is a schematic diagram of the overall spatial pose acquisition system for a bridge erecting machine provided in an embodiment of the present invention. Detailed Implementation

[0067] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0068] The embodiments of this invention are written in a progressive manner.

[0069] This invention provides a method and system for acquiring the overall spatial pose of a bridge erecting machine. It primarily addresses the technical problems of traditional bridge erecting machines, such as reliance on mechanical tolerances for positioning, the need for manual calibration, high equipment costs, and inaccurate positioning.

[0070] like Figure 1 As shown, a method for obtaining the overall spatial pose of a bridge erecting machine includes the following steps:

[0071] S1. Obtain the theoretical center point of any two adjacent piers according to the bridge design drawings, establish a global coordinate system with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, obtain the theoretical center point of all piers accordingly, and set the front support leg reference point in the global coordinate system.

[0072] S2. Install reflective materials on bridge piers of different structures respectively;

[0073] S3. Collect two-dimensional point cloud data of bridge piers with different structures in the construction area, filter and cluster the two-dimensional point cloud data, and obtain the actual center point of bridge piers with different structures according to the processed two-dimensional point cloud data.

[0074] S4. Match the actual center point of the bridge pier with the theoretical center point of the bridge pier according to different structures to obtain the current pose of the lidar sensor in the global coordinate system;

[0075] S5. Based on the current pose of the lidar sensor in the global coordinate system, the reference point of the front leg, and the preset geometric installation relationship of the lidar legs, obtain the dynamic pose of the front, middle, and rear legs in the global coordinate system.

[0076] S6. Based on the dynamic poses of the front, middle, and rear outriggers in the global coordinate system, the three-point configuration relationship and the path displacement of the bridge erecting machine are used to obtain the overall spatial pose of the bridge erecting machine.

[0077] In steps S1 to S6, this invention introduces structured reflective stickers into the positioning system of the front outrigger of the bridge erecting machine. Combined with two-dimensional lidar echo intensity analysis and geometric feature fitting techniques (such as high reflectivity point screening, line fitting, corner point reverse calculation, and center point reconstruction), millimeter-level spatial positioning accuracy can be achieved in typical bridge pier environments without the need for complex model construction. This method exhibits strong positioning stability, is less affected by environmental interference, meets the rigid positioning requirements of high-precision construction equipment, and is significantly superior to traditional visual positioning or single-point ranging methods. Compared to the complex architectures of traditional methods relying on image recognition, 3D point cloud modeling, or GNSS, the positioning method proposed in this invention is entirely based on two-dimensional lidar and standard reflective structures, without involving deep learning model training and inference. It has low computational resource requirements, rapid deployment, and controllable costs.

[0078] like Figure 2 As shown, preferably, step S1 includes the following steps:

[0079] A1. Analyze the bridge design drawings using the AutoCAD platform to obtain the theoretical bridge location lines of multiple piers;

[0080] A2. Define the midpoint of the line connecting any two adjacent theoretical center points of the bridge piers as the origin of the coordinate system, define the line connecting the theoretical center points as the X-axis, and the direction perpendicular to the line connecting the theoretical center points as the Y-axis to establish a global coordinate system;

[0081] A3. Convert all pier positions to theoretical coordinates in the global coordinate system, and obtain the theoretical center point of all piers accordingly;

[0082] A4. Preset the reference point for the front outrigger in the global coordinate system.

[0083] Steps A1 to A4 are implemented based on the AutoCAD platform. Secondary development of AutoCAD is performed using C# language under the .NET framework, calling the AutoCAD .NET API to parse and extract attributes of geometric elements in the drawings. The bridge location line (main bridge centerline) is automatically identified, and a unified global coordinate system is constructed after obtaining its start and end points; the midpoint of the line connecting any two adjacent pier center points is used as the coordinate origin. The direction of this connection is defined in the global coordinate system. X The axis, perpendicular to the direction is Y The positions of all bridge piers are transformed to this coordinate system, using two-dimensional plane coordinates. To achieve a unified spatial representation, and to ensure precise alignment between the outriggers and the pier structure, reference points for the front outriggers will be output in the global coordinate system. This serves as the input basis for deployment and positioning modeling.

[0084] In this embodiment, to further improve the consistency of spatial representation and the efficiency of subsequent data management, a unique number is assigned to each bridge pier (e.g., ...). PD-01, PD-02 (etc.). Numbering information can be automatically extracted from text annotations in CAD drawings, and manual verification and supplementation are also supported. Each number is bound to its corresponding pier coordinates, forming a "number-coordinate" mapping table.

[0085] Preferably, step S2 specifically includes:

[0086] Flexible, highly reflective materials are used to achieve curved surface fitting of cylindrical bridge piers through arc-shaped slots or modular sheaths;

[0087] Highly reflective material was affixed to the front of the rectangular bridge pier and its two sides.

[0088] In practical applications, a 360° circumferential flexible covering strategy is adopted for cylindrical bridge piers or temporary support columns that need to be compatible with cylindrical fitting algorithms. This solution uses flexible, highly reflective materials (such as engineering-grade films or reflective spray coatings) evenly distributed along the circumference of the bridge pier. Curved surfaces are fitted using arc-shaped slots or modular sleeves to form a complete and continuous reflective cylindrical surface. The reflective structure is uniformly positioned at a height of more than 2 meters above the ground, creating a strong echo area that can be identified by LiDAR from all directions. This design significantly enhances the target symmetry and integrity in point cloud data, facilitating subsequent center extraction and numbering, and improving anti-occlusion performance in complex scenes.

[0089] For bridge piers with rectangular or near-rectangular cross-sections, a three-sided film-coating design is adopted: highly reflective material is adhered to the front of the pier and its two left and right sides, forming a near-"∩"-shaped reflective area. The film size is customized according to the pier's cross-sectional dimensions, with the edges aligned as closely as possible to the pier's corners, and uniformly positioned at a height of at least 2 meters above the ground. This arrangement significantly enhances the spatial reflectivity of the pier in the point cloud, especially in actual working conditions where the outriggers sway laterally or scan at an angle, effectively suppressing recognition drift caused by angle changes and ensuring the stability and continuity of center point extraction. Furthermore, it offers advantages such as convenient installation and low material costs, making it suitable for various types of rectangular bridge pier structures.

[0090] like Figure 3 As shown, preferably, step S3 involves collecting two-dimensional point cloud data of bridge piers with different structures within the construction area, and then filtering and clustering the two-dimensional point cloud data, including the following steps:

[0091] B1. Collect two-dimensional point cloud data of rectangular bridge piers within the construction area, and filter out points with light reflection intensity values ​​higher than the preset reflection intensity threshold based on the light reflection intensity value of each point to construct an initial high-reflectivity area point set;

[0092] B2. Using the DBSCAN algorithm, unsupervised clustering is performed based on the spatial density distribution characteristics of the point cloud in the initial high reflectivity area point set to extract multiple high reflectivity area point cloud clusters.

[0093] In step B1, the construction area ahead is continuously scanned using a lidar system, and two-dimensional point cloud data is received in real time. To extract reflective targets with structural features, points with a reflection intensity value higher than a set threshold (e.g., 80% of the maximum intensity) are first selected based on the reflection intensity value of each point, forming a candidate set of highly reflective areas. Specifically, each point in the point cloud has spatial coordinates. and reflection intensity Extract the elements that satisfy The points form a set of highly reflective candidate points. .

[0094] In step B2, the DBSCAN algorithm is used to perform unsupervised clustering based on the spatial density distribution characteristics of the point cloud, extracting multiple discrete high-reflectivity point cloud clusters. This method is particularly suitable for processing point sets with irregular shapes and noise, and can effectively separate multiple bridge pier edge areas with reflective stickers.

[0095] Before implementing DBSCAN clustering, the high reflectivity point set was first analyzed. , where each point A two-dimensional Euclidean space is constructed. The algorithm introduces two core parameters: radius threshold. And the minimum number of neighbors, MinPts.

[0096] DBSCAN's clustering rules are as follows: If a point of The neighborhood contains at least MinPts points (including itself), that is... The point is then considered a "core point"; all points that can be reached by density from a series of core points are grouped into the same category, forming a complete point cloud cluster; points that do not belong to any cluster will be judged as noise points and automatically removed.

[0097] After DBSCAN clustering, multiple highly reflective point clouds are divided into independent clusters, with each cluster typically corresponding to a reflective surface on one side of a bridge pier. Due to the high repetition of bridge pier structures and the local high reflectivity of reflective surfaces, this clustering method demonstrates high robustness and accuracy in practical engineering.

[0098] like Figure 3 As shown, preferably, step S3 involves obtaining the actual center points of different structural piers based on the processed two-dimensional point cloud data, including the following steps:

[0099] B3. Collect the horizontal and vertical coordinates of all points in each point cloud cluster of a highly reflective region, calculate the extreme points of each point cloud cluster of a highly reflective region, form each rectangle aligned with the coordinate axes of the global coordinate system, and take the midpoint of the diagonal of each rectangle as the geometric center point of each point cloud cluster of a highly reflective region.

[0100] B4. Based on the two-dimensional straight line fitting of all points in each high reflectivity point cloud cluster, obtain the main direction vector of each high reflectivity point cluster. Using the geometric center point of each high reflectivity point cloud cluster as the reference point, construct the vector pointing from all points in each high reflectivity point cloud cluster to the center point. Based on the angle between the main direction vector of each high reflectivity point cluster and the vector pointing from all points in each high reflectivity point cloud cluster to the center point and the preset conditions, determine the spatial assignment of the high reflectivity points.

[0101] B5. Traverse the angle between the main direction vectors of any two high reflective point clusters belonging to the same space, determine the adjacent sides of the rectangular pier, enhance the stability of the adjacent sides of the rectangular pier according to the preset double-column joint constraint strategy, and obtain the intersection of the adjacent sides of the rectangular pier after the stability enhancement.

[0102] B6. Based on the intersection of adjacent sides of the rectangular pier after stability enhancement and the preset standard pier size parameters, obtain the theoretical center point of the rectangular pier. According to the external parameter calibration of the lidar and bridge erecting machine coordinate system, perform coordinate transformation on the theoretical center point of the rectangular pier to obtain the actual center point of the rectangular pier.

[0103] In step B3, the extreme points are calculated by scanning the horizontal and vertical coordinates of all points in each cluster of point clouds. This forms a minimum rectangular bounding box aligned with the coordinate axes. Then, the midpoint of the bounding box's diagonal is taken as the geometric center of the point cloud cluster, calculated using the following formula:

[0104] ;

[0105] In step B4, for each pier area, two adjacent highly reflective surface regions can typically be identified, corresponding to two adjacent sides of the rectangular pier. To extract the structural boundary orientation of these surface regions, the orientation of each cluster of highly reflective point clouds is determined. Perform two-dimensional line fitting to obtain the directional characteristics of the boundary.

[0106] The goal of fitting a two-dimensional straight line using the least squares method is to find a line of the form: Find a straight line that minimizes the sum of the squared perpendicular distances from all points to that line. Equivalently, the fitting process can be transformed into minimizing the error term:

[0107] ;

[0108] This optimization problem can be solved by... , By taking the partial derivatives and setting them to zero, we can obtain the optimal fitting parameters. Specifically, we have:

[0109] ;

[0110] After fitting, the principal direction vector of each highly reflective point cluster can be obtained. Its angle This represents the directional characteristics of the cladding cluster in a two-dimensional plane. This fitted direction will serve as an important input parameter for subsequent structure identification, reflective surface grouping, and attitude estimation. The fitted straight line accurately depicts the orientation of the cladding area, reflecting the geometric characteristics of the pier boundary;

[0111] With geometric center point For reference, the angle relationship between each cluster of reflective points and the fitted boundary direction is analyzed to assist in boundary classification.

[0112] For each highly reflective point Construct a vector pointing to the center point:

[0113] ;

[0114] Meanwhile, assuming the direction vector of the locally fitted line of the point cluster is This vector can be obtained through PCA or the least squares linear fitting method mentioned above.

[0115] Calculate the angle between the two. Using the dot product formula, we get:

[0116] ;

[0117] Based on the cosine of the included angle, make the following judgment: If If the included angle is obtuse, then the highly reflective point cluster is considered to be oriented away from the geometric center and may belong to one of the outermost edges of the pier; if If the included angle is acute, then the direction of the highly reflective dot cluster is considered to be towards the geometric center, possibly belonging to the inner side or the side facing the work area.

[0118] In step B5, the angle between the directions of any two fitted lines belonging to the same spatial domain is calculated to determine whether they are adjacent boundaries of a rectangular bridge pier. Let two fitted lines... , The unit direction vectors are respectively , The angle between the two is calculated as follows: When the included angle When this is the case, it can be determined that these two straight lines constitute adjacent sides of a rectangular bridge pier;

[0119] To further enhance fitting accuracy, a dual-column joint constraint strategy is introduced, taking into account the structural consistency of the piers during the layout process. In most actual working conditions, adjacent piers are standardized components with parallel structural arrangements and consistent reflective surface directions. Therefore, after identifying the same reflective surface direction of two piers, the following steps are used to improve the stability of boundary identification:

[0120] Compare the directions of the fitted straight lines from the two bridge piers. If the included angle satisfies... We assume that both lines lie in the same geometric direction set. By combining two approximately parallel lines and performing least-squares joint fitting, we obtain a unified global line equation: The corresponding direction vector is Projecting this global direction back onto the local straight lines of each bridge pier, adjusting the position or intercept of each line to match a unified direction, and compensating for local fitting errors caused by shading, uneven distribution of highly reflective points, etc. By comparing the deviation of each original fitted line from the global direction, abnormal boundaries with large errors are identified and eliminated, thereby improving the robustness of structure identification;

[0121] In step B6, when two adjacent straight lines are identified and their included angle is determined to be reasonable, the intersection point is solved using analytical geometry methods. The coordinates of one intersection point (also known as the corner point) of the rectangular pier are obtained, which is the core reference point for pier positioning and attitude estimation.

[0122] The standard dimensional parameters of the bridge piers (such as transverse width w and longitudinal thickness h) are read from the CAD model, and the offset direction is determined based on the identified corner point type (such as lower left corner, upper right corner, etc.). Then, based on the corner point coordinates, a vector translation operation is performed along the diagonal of the rectangle to calculate the spatial position of the center point. If the currently identified corner point is the lower right corner of the bridge pier, its corresponding center point coordinates can be calculated as follows:

[0123] ;

[0124] To ensure the consistency and traceability of the center point positioning, the coordinate transformation of the derived center point is also performed by combining the external parameter calibration results between the lidar and the coordinate system of the bridge erecting machine, so as to obtain the actual center point of the rectangular pier and make its output coordinates in the global reference coordinate system of the construction environment (aligned with CAD).

[0125] like Figure 4 As shown, preferably, step S3 further includes the following steps:

[0126] C1. Collect two-dimensional point cloud data of cylindrical bridge piers within the construction area, and filter out points with light reflection intensity values ​​higher than the preset reflection intensity threshold based on the light reflection intensity value of each point to construct an initial high-reflectivity area point set;

[0127] C2. Using a linear continuity clustering strategy, multiple high-reflectivity area point cloud clusters are extracted based on the continuity of the scan line numbers in the initial high-reflectivity area point set;

[0128] C3. Acquire the azimuth angles of all points in each point cloud cluster of the high reflectivity area, calculate the average azimuth angle of each point in the point cloud cluster of the high reflectivity area, obtain the reference azimuth angle of each point in the point cloud cluster of the high reflectivity area according to the RANSAC algorithm, project the measured distance onto the direction of the line connecting the centers of the cylinder based on the average azimuth angle and the reference azimuth angle of each point, and obtain the straight-line distance between each point and the center of the circle. According to the preset standard pier size parameters, the average azimuth angle of each point, the measured distance and the preset formula, perform distance compensation on the straight-line distance between each point and the center of the circle to obtain the center distance of each point;

[0129] C4. Take a weighted average or simple average of the center distances of all points to obtain an estimated value of the center distance of the cylindrical pier. Convert the estimated center distance and the reference azimuth to Cartesian coordinates to obtain the actual center point of the cylindrical pier.

[0130] In step C1, two-dimensional point cloud data of the construction area is continuously acquired using LiDAR, and the reflection intensity information of each point is recorded in real time. To effectively identify circular reflective pillars, the reflection intensity of all points in the current frame of data is recorded. The analysis extracts the point cloud of the highlighted areas. Specifically, the maximum reflection intensity in the current frame is set as follows: Then set a dynamic threshold. Filter out those that meet the requirements These points constitute a set of candidate highly reflective points. These points are usually concentrated on the surface of the reflective column, exhibiting obvious brightness characteristics and spatial clustering.

[0131] In step C2, a clustering strategy based on scan line continuity is adopted by further combining the scanning characteristics of the 2D LiDAR. The LiDAR emits scan beams sequentially at fixed angular intervals, thus highly reflective points from the same cylindrical surface exhibit good continuity in the angular sequence (or index). By checking the continuity of highly reflective points in the scan line numbering, consecutively occurring point segments (e.g., more than 5 consecutive index units) are identified as candidate regions for the same reflective cylinder. This method effectively improves the real-time performance and robustness of circular cylinder recognition, while also avoiding the problems of heavy computational burden and high misclassification rate of traditional density clustering algorithms in long-distance or low-density point cloud scenarios.

[0132] In step C3, since the two-dimensional lidar acquires data in polar coordinate form (distance)... r Azimuth By combining the spatial orientation and distance measurement information of each point, a strategy incorporating orientation modeling and distance compensation is adopted to improve the accuracy of center coordinate calculation. The azimuth angles of all points in the current reflective point cluster are extracted. And calculate their average value. This serves as a preliminary estimate of the center direction of the reflective bridge pier: Due to occasional outliers caused by reflective interference or occlusion, [the following is introduced]. RANSAC The algorithm performs robust processing: iteratively sampling a subset of all points, fitting a directional model, and removing outliers that deviate from the direction by more than a certain threshold (e.g., 5°), ultimately outputting a more stable and reliable reference azimuth angle. Based on the azimuth of each point relative to the reference direction The included angle , will measure distance Projecting onto the direction of the center line, we obtain the direction component: This step is equivalent to setting the point... Projecting the radar's viewpoint onto the center line allows for estimation of the straight-line distance between the radar scan point and the center of the circle. Since the radar scan point is located at the edge of the pier, the actual center distance should be slightly larger than the projected distance. Therefore, a fixed radius compensation term is added.

[0133] ;

[0134] Where R is the standard radius of the reflector (31.5 mm). This compensation amount is actually the projection component of the line connecting the laser beam illumination point to the center of the column in the reference direction. Adding the projection distance and the compensation amount, we obtain the estimated center distance corresponding to that point: .

[0135] In step C4, for all directional components Weighting Alternatively, a simple average can be used to obtain the final estimated center distance of the cylindrical reflective bridge pier. This distance value represents the straight-line distance from the radar coordinate origin along the reference direction towards the center of the circle.

[0136] To obtain the spatial location of the center of the circle, this point in polar coordinates ( , Converting to Cartesian coordinates, the calculation formula is as follows:

[0137] ;

[0138] in( , The coordinates of the center point of the reflective cylinder in the radar's two-dimensional coordinate system are given by the coordinates of the center point.

[0139] like Figure 5 As shown, preferably, step S4 includes the following steps:

[0140] D1. Perform a preliminary matching between the actual center point and the theoretical center point of the bridge piers of different structures according to the preset order;

[0141] D2. An improved ICP algorithm is used to perform a secondary matching between the actual center points of the unmatched bridge piers and the theoretical center points of the bridge piers. Specifically, based on the preset distribution pattern of the bridge piers and the spatial rigid structure, the SVD algorithm is used to obtain the optimal rotation matrix and displacement vector so that the actual center points of the bridge piers with different structures are aligned with the theoretical center points of the bridge piers after the steel body transformation.

[0142] D3. Define the optimal rotation matrix and translation vector as the pose of the current lidar sensor in the global coordinate system.

[0143] In steps D1 to D3, a global bridge pier map database is pre-constructed, containing a set of globally known theoretical center points of bridge piers: Each point corresponds to the standard center coordinates of a bridge pier, and each point carries a number, arrangement order, and construction positioning structural information. The set of actual center points of the local bridge piers extracted by the lidar in the current frame is denoted as: These local points have initially established a one-to-one correspondence with some points in the map based on echo intensity, geometry, and numbering order. During the ICP initialization phase, instead of using "nearest neighbor search," strong constraint pairing is performed directly based on numbering or arrangement order to reduce matching ambiguity.

[0144] Considering the regularity of the bridge pier distribution and the rigidity of the spatial structure, the following approach is adopted. SVD The singular value decomposition (SVD) method is used to solve for optimal rigid body transformations. The goal is to find an optimal rotation matrix in a two-dimensional plane. and displacement vector This makes the local point set Q After rigid body transformation, with the global point set P Align as closely as possible to satisfy:

[0145] ;

[0146] in For local points, For the corresponding global point, k For the number of matching point pairs.

[0147] Due to local point sets Q It is expressed in the current frame of the lidar coordinate system, therefore the rigid body transformation parameters obtained by the final solution are... (R, t) What is actually described is the current radar coordinates in the global coordinate system:

[0148] ;

[0149] The optimal rotation matrix and displacement vector are defined as the pose of the current lidar sensor in the global coordinate system.

[0150] like Figure 6 As shown, preferably, step S5 includes the following steps:

[0151] E1. Perform steel body transformation according to the preset radar leg geometric installation relationship to obtain the pose of the front leg in the radar coordinate system. Based on the pose of the current lidar sensor in the global coordinate system and the pose of the front leg in the radar coordinate system, obtain the static pose of the front leg in the global coordinate system.

[0152] E2. Based on the static geometric relationship between the front outrigger, the middle outrigger, and the rear outrigger, and using the static pose of the front outrigger in the global coordinate system as the reference point, obtain the static pose of the middle outrigger and the rear outrigger in the global coordinate system.

[0153] E3. Collect the path displacement of the bridge erecting machine, dynamically update the static pose of the front outrigger in the global coordinate system, and then perform error compensation to obtain the dynamic pose of the front outrigger, middle outrigger and rear outrigger in the global coordinate system.

[0154] In step E1, the coordinate positions of the front outriggers are solved using the known geometric installation relationship between the radar and the outriggers. Each front outrigger is fixedly equipped with a two-dimensional lidar, whose position has a fixed offset relative to the geometric center of the outrigger, which can be expressed as a rigid body transformation from the outrigger coordinate system to the radar coordinate system:

[0155] ;

[0156] in, （ ， ） This indicates the installation offset of the radar relative to the center of the outriggers. This refers to the installation angle of the radar relative to the orientation of the outriggers.

[0157] The pose of the lidar in the global coordinate system is known. Then the static pose of the front leg in the global coordinate system It can be obtained by reverse deduction from the following relationship: .

[0158] In step E2, the outriggers along the bridge direction are, in sequence, the front outrigger (with lidar), the middle outrigger, and the rear outrigger (without lidar). The static geometric relationship between the three can be given by design drawings or measured data. Let the front outrigger be the reference point. Located in the global coordinate system; the theoretical bridge distance between the middle outrigger and the front outrigger is Horizontal offset is The theoretical bridge distance between the rear outrigger and the front outrigger is: Horizontal offset is Under the ideal static attitude:

[0159] ;

[0160] in Indicates the orientation angle of the bridge erecting machine The corresponding two-dimensional rotation matrix.

[0161] In step E3, during the movement, the path displacement is collected in real time by the walking encoder under the front outrigger, and the position of the front outrigger is updated by odometer integration:

[0162] ;

[0163] in This represents the unit step distance detected by the encoder. Based on the known structural relationship between the front, middle, and rear outriggers, this can be calculated synchronously. and The relative position.

[0164] To correct encoder cumulative errors and wheel slippage, automatic correction points are set near typical workstations of the middle and rear outriggers. These points are highly reflective targets with stable echo characteristics (such as reflective pillars or reflective stickers). Once the front outrigger lidar scans these preset points and identifies their current point cloud position... Compare it with the known position of that point in the global coordinate system. Perform a comparison and calculate the error vector:

[0165] ;

[0166] Use the error vector to determine the position of the front outrigger. Perform translation correction:

[0167] ;

[0168] This leads to the synchronous correction of the positions of the middle and rear outriggers, thus obtaining the dynamic poses of the front, middle, and rear outriggers in the global coordinate system.

[0169] like Figure 7 As shown, preferably, step S6 includes the following steps:

[0170] F1. Using the front outrigger as a reference point, the forward direction of the bridge erecting machine is the X-axis, and the direction perpendicular to the forward direction of the bridge erecting machine is the Y-axis. Establish the overall coordinate system of the bridge erecting machine and convert the overall coordinate system of the bridge erecting machine into a global coordinate system.

[0171] F2. Based on the dynamic pose of the front outrigger, middle outrigger, and rear outrigger in the global coordinate system, obtain the coordinates of any component point of the whole machine in the global coordinate system, and obtain the orientation angle of the whole machine based on the path displacement of the bridge erecting machine;

[0172] F3. Define the coordinates of any component point of the whole machine in the global coordinate system and the orientation angle of the whole machine as the overall spatial pose of the bridge erecting machine.

[0173] In step F1, the front outrigger is used as a reference point for overall machine attitude modeling. A local coordinate system is established with the forward direction of the bridge erecting machine (along the bridge location line) as the X-axis of the overall machine coordinate system and the direction perpendicular to it as the Y-axis. Transform the body coordinate system to the global coordinate system (X, Y) through rotation and translation.

[0174] In step F2, let the position of the front outrigger in the global coordinate system be... The overall orientation angle is The positions of the middle and rear outriggers in the body coordinate system are respectively , Then any component point of the whole machine Its position in the global coordinate system is:

[0175] ;

[0176] in, For a two-dimensional rotation matrix:

[0177] ;

[0178] As the position of the front outriggers is updated in real time via encoder, the overall orientation of the machine... It can be estimated using the continuous position vectors of the front outriggers:

[0179] ;

[0180] To control the cumulative error, the automatic correction point information scanned by the lidar is integrated, the global error vector is calculated and the position of the front outrigger is corrected, thereby pulling the entire rigid body model to adjust synchronously, ensuring the consistency of the three-point space and the attitude accuracy of the whole machine.

[0181] The coordinates of any component point in the global coordinate system and the orientation angle of the entire machine are defined as the overall spatial pose of the bridge erecting machine.

[0182] like Figure 8 As shown, a bridge erecting machine overall spatial pose acquisition system includes:

[0183] The global coordinate system module is used to obtain the theoretical center point of any two adjacent piers based on the bridge design drawings, establish a global coordinate system with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, obtain the theoretical center point of all piers accordingly, and set the front support leg reference point in the global coordinate system.

[0184] Reflective material installation module, used to install reflective materials on bridge piers of different structures respectively;

[0185] The actual center point module is used to collect two-dimensional point cloud data of bridge piers with different structures within the construction area, filter and cluster the two-dimensional point cloud data, and obtain the actual center point of bridge piers with different structures based on the processed two-dimensional point cloud data.

[0186] The lidar pose acquisition module is used to match the actual center point of the bridge pier with the theoretical center point of the bridge pier according to different structural piers in order to obtain the pose of the current lidar sensor in the global coordinate system.

[0187] The outrigger dynamic pose acquisition module is used to acquire the dynamic poses of the front, middle, and rear outriggers in the global coordinate system based on the current pose of the lidar sensor, the front outrigger reference point, and the preset geometric installation relationship of the lidar outriggers.

[0188] The overall spatial pose acquisition module of the bridge erecting machine is used to obtain the overall spatial pose of the bridge erecting machine by adopting the three-point configuration relationship and the path displacement of the bridge erecting machine based on the dynamic pose of the front, middle and rear outriggers in the global coordinate system.

[0189] In practical applications, the overall spatial pose acquisition system for a bridge erecting machine provided by this invention includes: a global coordinate system module, a reflective material installation module, an actual center point module, a lidar pose acquisition module, a leg dynamic pose acquisition module, and an overall spatial pose acquisition module for the bridge erecting machine.

[0190] This system incorporates structured reflective stickers into the positioning system of the front outriggers of a bridge erecting machine. Combined with two-dimensional lidar echo intensity analysis and geometric feature fitting techniques (such as high reflectivity point screening, line fitting, corner point inversion, and center point reconstruction), it achieves millimeter-level spatial positioning accuracy in typical bridge pier environments without the need for complex models. The system exhibits strong positioning stability, is minimally affected by environmental interference, and meets the rigid positioning requirements of high-precision construction equipment, significantly outperforming traditional visual positioning or single-point ranging methods. Compared to the complex architectures of traditional systems relying on image recognition, 3D point cloud modeling, or GNSS, the proposed positioning system is entirely based on two-dimensional lidar and standard reflective structures, without involving deep learning model training and inference. This results in low computational resource requirements, rapid deployment, and controllable costs.

[0191] In the embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. The system embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, and can be electrical, mechanical, or other forms.

[0192] Furthermore, in the various embodiments of the present invention, each functional module can be fully integrated into a processor, or each module can be a separate device, or two or more modules can be integrated into a device; each functional module in the various embodiments of the present invention can be implemented in hardware or in the form of hardware plus software functional units.

[0193] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by program instructions and related hardware. The aforementioned program instructions can be stored in a computer-readable storage medium. When the program instructions are executed, they perform the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0194] It should be understood that the use of terms such as "system," "device," "unit," and / or "module" in this application is merely one method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0195] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "a," and / or "the" are not specifically singular and may include the plural. Generally, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements. An element defined by the phrase "comprising an..." does not exclude the presence of other identical elements in the process, method, product, or apparatus that includes the element.

[0196] If a flowchart is used in this application, it is used to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0197] The foregoing has provided a detailed description of a method and system for acquiring the overall spatial pose of a bridge erecting machine, as provided by the present invention. The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for acquiring the overall spatial pose of a bridge machine, characterized in that, The method comprises the following steps: According to the bridge design drawings, the theoretical center points of any two adjacent piers are obtained, a global coordinate system is established with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, the theoretical center points of all piers are obtained, and a front leg reference point is set in the global coordinate system; The reflective material is installed on different structure piers respectively; Two-dimensional point cloud data of different structure piers in the construction area is collected, the two-dimensional point cloud data is filtered and clustered, and the actual center points of different structure piers are obtained according to the processed two-dimensional point cloud data; According to the matching of the actual center points of the different structure piers and the theoretical center points of the piers, the pose of the current laser radar sensor in the global coordinate system is obtained; According to the pose of the current laser radar sensor in the global coordinate system, the front leg reference point and the preset radar leg geometric installation relationship, the dynamic poses of the front, middle and rear legs in the global coordinate system are obtained; According to the dynamic poses of the front, middle and rear legs in the global coordinate system, the three-point configuration relationship and the bridge erecting machine path displacement are obtained to obtain the overall space pose of the bridge erecting machine.

2. The method of claim 1, wherein, According to the bridge design drawings, the theoretical center points of any two adjacent piers are obtained, a global coordinate system is established with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, and a front leg reference point is set in the global coordinate system, comprising the following steps: According to the AutoCAD platform, the bridge design drawings are analyzed to obtain a plurality of pier theoretical bridge position lines; The midpoint of the line connecting the theoretical center points of any two adjacent piers is defined as the coordinate origin, the line connecting the theoretical center points is defined as the X-axis, and the direction perpendicular to the line connecting the theoretical center points is defined as the Y-axis to establish the global coordinate system; All pier positions are converted into theoretical coordinates in the global coordinate system to obtain the theoretical center points of all piers; The front leg reference point is preset in the global coordinate system.

3. The method of claim 1, wherein, The reflective material is installed on different structure piers respectively, specifically: The bendable high-reflective material is fitted on the cylindrical pier through an arc-shaped slot or a modular sheath to realize curved surface fitting; The high-reflective material is pasted on the front face and the left and right two side faces of the rectangular pier.

4. The method of claim 3, wherein, The two-dimensional point cloud data of different structure piers in the construction area is collected, the two-dimensional point cloud data is filtered and clustered, comprising the following steps: The two-dimensional point cloud data of the rectangular pier in the construction area is collected, points with a light reflection intensity value higher than a preset reflection intensity threshold value are selected according to the light reflection intensity value of each point, and an initial high-reflective area point set is constructed; The DBSCAN algorithm is used to perform unsupervised clustering according to the point cloud spatial density distribution characteristics in the initial high-reflective area point set, and a plurality of high-reflective area point cloud clusters are extracted.

5. The method of claim 4, wherein, The actual center points of different structure piers are obtained according to the processed two-dimensional point cloud data, comprising the following steps: The horizontal and vertical coordinates of all points in each high-reflective area point cloud cluster are collected, the extreme points of each high-reflective area point cloud cluster are calculated, each rectangular frame aligned with the coordinate axes of the global coordinate system is formed, and the diagonal midpoint of each rectangular frame is taken as the geometric center point of each high-reflective area point cloud cluster; According to the two-dimensional straight line fitting of all points in each high-reflective region point cloud cluster, the main direction vector of each high-reflective point cluster is obtained, taking the geometric center point of each high-reflective region point cloud cluster as a reference point, the vector of all points in each high-reflective region point cloud cluster pointing to the center point is constructed, and according to the included angle between the main direction vector of each high-reflective point cluster and the vector of all points in each high-reflective region point cloud cluster pointing to the center point and a preset condition, the spatial attribution of the high-reflective point is determined; Iterating the included angle between the main direction vectors of any two high-reflective point clusters with the same spatial attribution, the adjacent edges of the rectangular bridge pier are determined, the stability of the adjacent edges of the rectangular bridge pier is enhanced according to a preset double-column joint constraint strategy, and the intersection point of the adjacent edges of the rectangular bridge pier after stability enhancement is obtained; According to the intersection point of the adjacent edges of the rectangular bridge pier after stability enhancement and a preset bridge pier standard size parameter, the theoretical center point of the rectangular bridge pier is obtained, and the coordinate transformation of the theoretical center point of the rectangular bridge pier is performed according to the external parameter calibration of the laser radar and the bridge erecting machine coordinate system, so that the actual center point of the rectangular bridge pier is obtained.

6. The method of claim 3, wherein, The two-dimensional point cloud data of different structure bridge piers in the construction area is collected, the two-dimensional point cloud data is screened and clustered, and the actual center points of different structure bridge piers are obtained according to the processed two-dimensional point cloud data, and the method further includes the following steps: The two-dimensional point cloud data of the cylindrical bridge pier in the construction area is collected, points with a light reflection intensity value higher than a preset reflection intensity threshold value are screened out according to the light reflection intensity value of each point, and an initial high-reflective region point set is constructed; A linear continuity clustering strategy is used, and a plurality of high-reflective region point cloud clusters are extracted according to the continuity of the scan line numbers in the initial high-reflective region point set. extracting the azimuth angle of each point in the current cluster and the reference azimuth angle ; according to the azimuth angle of each point and the reference azimuth angle , the angle between them , the measured distance is projected onto the reference direction to obtain the projected distance: , which is equivalent to projecting the point along the radar view angle onto the reference direction to estimate the straight-line distance from the center; since the radar scanning point is located at the edge of the pier, the true center distance should be slightly larger than the projected distance, so a fixed radius compensation term is added: ； R is the standard radius of the reflective bridge pier; the fixed radius compensation term is actually the projection component of the connecting line from the laser beam irradiation point to the center of the cylinder in the reference direction; the projection distance and the fixed radius compensation term are added to obtain the center distance estimate corresponding to each point: ； The center distance estimates of all points are weighted or simply averaged to obtain the center distance estimate value of the cylindrical bridge pier, and the center distance estimate value and the reference azimuth angle are converted into Cartesian coordinates to obtain the actual center point of the cylindrical bridge pier.

7. The method of claim 2, wherein, The actual center points of different structure bridge piers are matched with the theoretical center points of the bridge piers to obtain the pose of the current laser radar sensor in the global coordinate system, and the method includes the following steps: The actual center points of different structure bridge piers are preliminarily matched with the theoretical center points of the bridge piers in a preset order; An improved ICP algorithm is used to perform secondary matching on the actual center points of different structure bridge piers and the theoretical center points of the bridge piers that are not matched, specifically: according to a preset bridge pier distribution regularity and a spatial rigid structure, an SVD algorithm is used to obtain an optimal rotation matrix and a displacement vector, so that the actual center points of different structure bridge piers are aligned with the theoretical center points of the bridge piers after rigid body transformation; The optimal rotation matrix and the displacement vector are defined as the pose of the current laser radar sensor in the global coordinate system.

8. The method of claim 7, wherein, The front, middle and rear support leg dynamic poses in the global coordinate system are obtained according to the current laser radar sensor pose, the front support leg reference point and a preset radar support leg geometric installation relationship, and the method comprises the following steps: According to the preset radar support leg geometric installation relationship, the steel body transformation is carried out to obtain the pose of the front support leg in the radar coordinate system, and the static pose of the front support leg in the global coordinate system is obtained according to the pose of the current laser radar sensor in the global coordinate system and the pose of the front support leg in the radar coordinate system; According to the static geometric relationship of the front support leg, the middle support leg and the rear support leg, the static poses of the middle support leg and the rear support leg in the global coordinate system are obtained with the static pose of the front support leg in the global coordinate system as the reference point; The static pose of the front support leg in the global coordinate system is dynamically updated after the error compensation of the collected bridge erecting machine path displacement, and the dynamic poses of the front support leg, the middle support leg and the rear support leg in the global coordinate system are obtained.

9. The method of claim 8, wherein, The global coordinate system is established with the front support leg as the reference point, the forward direction of the bridge erecting machine as the X axis and the direction perpendicular to the forward direction of the bridge erecting machine as the Y axis, the bridge erecting machine coordinate system is converted into the global coordinate system, the dynamic poses of the front support leg, the middle support leg and the rear support leg in the global coordinate system are obtained, the coordinates of any component point of the whole machine in the global coordinate system are obtained according to the dynamic poses of the front support leg, the middle support leg and the rear support leg in the global coordinate system, and the heading angle of the whole machine is obtained according to the bridge erecting machine path displacement; The coordinates of any component point of the whole machine in the global coordinate system and the heading angle of the whole machine are defined as the global spatial pose of the bridge erecting machine. The global coordinate system module is used to obtain the theoretical center points of any two adjacent piers according to the bridge design drawings, establish the global coordinate system with the midpoint of the line connecting the theoretical center points of any two adjacent piers as the origin, and obtain the theoretical center points of all piers, and set the front support leg reference point in the global coordinate system; The reflective material installation module is used to install reflective materials on different structure piers respectively; 10. A bridge girder machine overall spatial pose acquisition system, characterized in that, The actual center point module is used to collect two-dimensional point cloud data of different structure piers in the construction area, filter and cluster process the two-dimensional point cloud data, and obtain the actual center points of different structure piers according to the processed two-dimensional point cloud data; The laser radar pose acquisition module is used to match the actual center points of different structure piers with the theoretical center points of the piers to obtain the pose of the current laser radar sensor in the global coordinate system; The support leg dynamic pose acquisition module is used to obtain the dynamic poses of the front, middle and rear support legs in the global coordinate system according to the pose of the current laser radar sensor in the global coordinate system, the front support leg reference point and the preset radar support leg geometric installation relationship; The global spatial pose acquisition module of the bridge erecting machine is used to obtain the global spatial pose of the bridge erecting machine according to the dynamic poses of the front, middle and rear support legs in the global coordinate system and the bridge erecting machine path displacement. ​ ​ ​

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