Photovoltaic piling pile positioning method and device and electronic equipment

Abstract

The invention provides a photovoltaic piling pile positioning method and device and electronic equipment. The method comprises the steps that point cloud data, posture data, machine body parameter data and pile column parameter data of the pile driver are obtained, the posture data are collected by a machine body of the pile driver and posture sensors arranged on all machine arms, and the point cloud data are obtained by collecting environmental point cloud in front of the pile driver through a laser radar of the pile driver; the pile top height of the pile is determined according to the attitude data, the fuselage parameter data and the pile parameter data, position attitude parameters of the pile are determined based on the point cloud data and the pile top height, and the position attitude parameters comprise pile bottom position coordinates, pile top position coordinates and pile body attitude; and the pile is positioned according to the GNSS positioning information and the position posture parameters of the pile driver, positioning data of the pile are obtained, and the positioning data are coordinate data of the pile in the world coordinate system. The problem that an existing pile positioning scheme is insufficient in positioning precision is solved.

Description

Technical Field

[0001] This application relates to the field of positioning technology for photovoltaic piling posts, and more specifically, to a positioning method, apparatus, computer-readable storage medium, and electronic device for photovoltaic piling posts. Background Technology

[0002] As the global energy structure accelerates its transition to a low-carbon model, solar photovoltaic (PV) power generation, as a crucial component of clean energy, is experiencing rapid and sustained growth in installed capacity. Against this backdrop, the scale of PV power plant construction is expanding, leading to increasingly higher demands for construction efficiency and quality. However, traditional PV pile foundation construction still faces numerous technical bottlenecks, necessitating automated and intelligent upgrades through innovative technologies.

[0003] In photovoltaic power plant construction, the precise positioning and installation of piles is a core aspect. Currently, the industry generally adopts a method combining manual measurement with mechanical pile driving, relying on construction personnel to use total station equipment to mark the pile positions before the pile driver completes the operation. Existing pile positioning solutions suffer from insufficient positioning accuracy. Summary of the Invention

[0004] The main objective of this application is to provide a method, device, computer-readable storage medium, and electronic device for positioning photovoltaic piling columns, so as to at least solve the problem of insufficient positioning accuracy in existing piling column positioning schemes.

[0005] To achieve the above objectives, according to one aspect of this application, a method for locating photovoltaic piling columns is provided, comprising: acquiring point cloud data, attitude data, body parameter data, and column parameter data of a piling machine, wherein the attitude data is collected by attitude sensors installed on the body and each arm of the piling machine, and the point cloud data is obtained by acquiring environmental point cloud data in front of the piling machine from the laser radar of the piling machine; determining the pile top height of the column based on the attitude data, the body parameter data, and the column parameter data, and determining the position and attitude parameters of the column based on the point cloud data and the pile top height, wherein the position and attitude parameters include the pile bottom coordinates, the pile top coordinates, and the pile body attitude; and performing positioning processing on the column based on the GNSS positioning information of the piling machine and the position and attitude parameters to obtain positioning data of the column, wherein the positioning data is the coordinate data of the column in the world coordinate system.

[0006] Optionally, determining the position and attitude parameters of the pile based on the point cloud data and the pile top height includes: identifying ground point clouds in the point cloud data by fitting a plane model based on Random Sample Consensus (RANSAC), and removing the ground point clouds from the point cloud data to obtain target point cloud data; clustering the target point cloud data using a clustering algorithm based on Euclidean distance to obtain clustered point cloud clusters, and performing feature filtering on the clustered point cloud clusters to determine the pile column point cloud; and determining the position and attitude parameters of the pile column based on the pile column point cloud and the pile top height.

[0007] Optionally, determining the position and attitude parameters of the pile based on the pile point cloud and the pile top height includes: determining the principal feature vector of the pile point cloud based on the PCA principal direction estimation algorithm, and performing RANSAC cylindrical model fitting on the pile point cloud based on the principal feature vector to obtain a pile model; and determining the position and attitude parameters of the pile based on the pile model and the pile top height.

[0008] Optionally, determining the position and attitude parameters of the pile column based on the pile column model and the pile top height includes: determining the axial direction vector of the pile column model and the coordinates of the lowest point projected onto the axial direction vector based on the pile column model, and determining the coordinates of the lowest point as the pile bottom position coordinates in the position and attitude parameters; when the bottom of the pile column is below the ground, determining the pile top position coordinates in the position and attitude parameters after pile driving based on the pile bottom position coordinates and the pile top height.

[0009] Optionally, acquiring the point cloud data of the piling machine includes: constructing a high-density point cloud frame of the environmental point cloud in front of the piling machine by spatial alignment and accumulation of multiple frames, thereby obtaining the point cloud data.

[0010] Optionally, determining the pile top height based on the attitude data, the fuselage parameter data, and the pile parameter data includes: determining the end height of the boom of the pile driver based on the attitude data and the fuselage parameter data; and determining the pile top height based on the end height and the pile parameter data.

[0011] Optionally, after determining the axial direction vector of the pile model based on the pile model, the method further includes: constructing a coordinate system with the body of the pile driver, and determining the verticality of the pile based on the axial direction vector.

[0012] According to another aspect of this application, a positioning device for photovoltaic piling columns is provided, comprising: an acquisition unit, configured to acquire point cloud data, attitude data, body parameter data, and pile parameter data of a piling machine, wherein the attitude data is acquired by attitude sensors installed on the body and each arm of the piling machine, and the point cloud data is acquired by the laser radar of the piling machine acquiring the environmental point cloud in front of the piling machine; a first determination unit, configured to determine the pile top height of the pile based on the attitude data, the body parameter data, and the pile parameter data, and to determine the position attitude parameters of the pile based on the point cloud data and the pile top height, wherein the position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude; and a positioning unit, configured to perform positioning processing on the pile based on the GNSS positioning information of the piling machine and the position attitude parameters to obtain positioning data of the pile, wherein the positioning data is the coordinate data of the pile in the world coordinate system.

[0013] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform any of the photovoltaic piling column positioning methods described above.

[0014] According to another aspect of this application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any of the photovoltaic piling column positioning methods described above.

[0015] The technical solution of this application acquires point cloud data, attitude data, body parameter data, and pile parameter data of the piling machine. The attitude data is collected by attitude sensors installed on the body and each arm of the piling machine, while the point cloud data is obtained by the laser radar of the piling machine collecting the environmental point cloud in front of the piling machine. The pile top height is determined based on the attitude data, body parameter data, and pile parameter data. The position and attitude parameters of the pile are then determined based on the point cloud data and pile top height, including the pile bottom coordinates, pile top coordinates, and pile body attitude. The pile is positioned using the GNSS positioning information and position and attitude parameters of the piling machine to obtain the pile positioning data, which is the coordinate data of the pile in the world coordinate system. By integrating GNSS positioning equipment, attitude sensors, and laser radar, the structural attitude information of the vehicle body and each arm segment, as well as the point cloud data in front of the piling machine, are first accurately acquired. Then, the pile top height in the vehicle body coordinate system is calculated based on the acquired information, and the pile bottom coordinates, pile top coordinates, and pile body attitude are determined by combining the laser radar scanning results. Finally, using the GNSS positioning information of the piling machine, the position and attitude parameters of the pile are converted to the world coordinate system, thereby obtaining high-precision pile coordinate data. This solution not only improves positioning accuracy but also automates the process, eliminating the need for manual intervention, significantly improving construction efficiency, reducing labor costs, and providing a stable and reliable intelligent solution for photovoltaic piling operations; thus, it solves the problem of insufficient positioning accuracy in existing pile positioning schemes. Attached Figure Description

[0016] 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:

[0017] Figure 1 A hardware structure block diagram of a mobile terminal for performing a method for locating photovoltaic piling columns according to an embodiment of this application is shown.

[0018] Figure 2 A schematic flowchart of a method for positioning photovoltaic piling columns according to an embodiment of this application is shown.

[0019] Figure 3 A schematic diagram of the sensor installation position of a pile driver provided according to an embodiment of this application is shown;

[0020] Figure 4 A flowchart illustrating a specific method for positioning photovoltaic piling columns according to an embodiment of this application is shown.

[0021] Figure 5A structural block diagram of a positioning device for photovoltaic piling columns provided according to an embodiment of this application is shown. Detailed Implementation

[0022] 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.

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] As described in the background section, existing pile positioning schemes suffer from insufficient positioning accuracy, low efficiency, and high labor costs. To address the problem of insufficient positioning accuracy in existing pile positioning schemes, embodiments of this application provide a method, apparatus, computer-readable storage medium, and electronic device for positioning photovoltaic piles.

[0026] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0027] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a photovoltaic piling column positioning method according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0028] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the photovoltaic piling column positioning method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0029] This embodiment provides a method for locating photovoltaic piling columns that runs on a mobile terminal, computer terminal, or similar computing device. 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. Also, although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than that shown here.

[0030] Figure 2 This is a flowchart of a photovoltaic piling column positioning method according to an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0031] Step S201: Obtain point cloud data, attitude data, body parameter data and pile parameter data of the pile driver. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver. The point cloud data is obtained by the laser radar of the pile driver collecting the environmental point cloud in front of the pile driver.

[0032] Specifically, the pile driver includes a body, a boom, a middle arm, and a forearm. The boom is close to the body, the forearm is far from the body, and the middle arm is located between the boom and the forearm. Attitude sensors are installed on the body, boom, middle arm, and forearm respectively.

[0033] Step S202: Determine the pile top height based on the above attitude data, the above fuselage parameter data, and the above pile parameter data, and determine the position attitude parameters of the above pile based on the above point cloud data and the above pile top height, wherein the above position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude.

[0034] Step S203: Based on the GNSS positioning information of the pile driver and the position and attitude parameters, the pile is positioned to obtain the positioning data of the pile, wherein the positioning data is the coordinate data of the pile in the world coordinate system.

[0035] Specifically, lidar directly obtains the pile bottom coordinates and pile posture by scanning the laser point cloud. The next step is to calculate the pile bottom coordinates using the pile length and the obtained pile bottom position coordinates and pile posture (at this point, the pile bottom is above the horizontal plane). After the pile driver drives the pile into the ground, the pile top height is needed. Compared to existing technologies, this embodiment does not require calculating the coordinates of the pile driver's boom end; it only needs to estimate the height information to locate the pile, resulting in a smaller error range.

[0036] In this embodiment, by applying steps S201, S202, and S203, and integrating multiple sensors including GNSS positioning equipment, attitude sensors, and lidar, the structural attitude information of the vehicle body and each boom segment, as well as point cloud data in front of the piling machine, are first accurately acquired. Then, based on the acquired information, the pile top height in the vehicle body coordinate system is calculated. Combined with the lidar scanning results, the pile bottom coordinates, pile top coordinates, and pile attitude are determined. Finally, using the GNSS positioning information of the piling machine, the pile position and attitude parameters are converted to the world coordinate system, thereby obtaining high-precision pile coordinate data. This solution not only improves positioning accuracy but also achieves automation, eliminating the need for manual intervention, significantly improving construction efficiency, reducing labor costs, and providing a stable and reliable intelligent solution for photovoltaic piling operations; thus, it solves the problem of insufficient positioning accuracy in existing pile positioning schemes.

[0037] In the specific implementation process, the position and attitude parameters of the pile are determined based on the aforementioned point cloud data and the aforementioned pile top height. This includes: identifying ground point clouds in the aforementioned point cloud data through planar model fitting based on Random Sample Consensus (RANSAC), and removing the ground point clouds from the aforementioned point cloud data to obtain target point cloud data; clustering the aforementioned target point cloud data using a clustering algorithm based on Euclidean distance to obtain clustered point cloud clusters, and performing feature filtering processing on the clustered point cloud clusters to determine the pile column point cloud; and determining the aforementioned position and attitude parameters of the pile column based on the aforementioned pile column point cloud and the aforementioned pile top height. Compared with the prior art, this solution can directly obtain the pile column point cloud region in front of the lidar and determine the position and attitude parameters of the aforementioned pile column through lidar.

[0038] In this embodiment, the position and attitude parameters of the pile are determined based on the fusion analysis of point cloud data and pile top height. First, ground point clouds are identified and removed from the point cloud data acquired by LiDAR through planar model fitting based on Random Sample Consensus (RANSAC). This process improves the purity of the target point cloud data, reduces interference factors, and ensures the accuracy of subsequent analysis. Then, a clustering algorithm based on Euclidean distance is used to cluster the target point cloud data, resulting in multiple clusters. These clusters are then filtered based on features such as volume threshold, height range, upper and lower limits of point count, and minimum bounding box shape to ultimately determine the pile point cloud representing the pile. Finally, based on the pile point cloud and the pile top height calculated by multi-attitude sensors, the pile bottom coordinates, pile top coordinates, and axial direction vector are calculated to determine the pile's position and attitude in the world coordinate system, ensuring high-precision positioning during construction. This technical solution effectively improves the accuracy and automation of pile positioning, reduces errors and workload from manual measurements, and ensures the efficiency and quality of photovoltaic piling construction.

[0039] Specifically, determining the position and attitude parameters of the pile based on the pile point cloud and the pile top height includes: determining the principal feature vector of the pile point cloud based on the PCA principal direction estimation algorithm, and performing RANSAC cylindrical model fitting on the pile point cloud based on the principal feature vector to obtain the pile model; and determining the position and attitude parameters of the pile based on the pile model and the pile top height.

[0040] In this embodiment, a high-precision self-positioning system for photovoltaic piling piles based on multi-sensor fusion technology achieves accurate determination of the pile's position and attitude by combining GNSS positioning equipment, attitude sensors (IMUs), and lidar. The system first utilizes four IMUs installed on the vehicle body, boom, mid-arm, and forearm to calculate the forearm end height through attitude transformations at each stage of the boom, using the vehicle body coordinate system. Then, combining this with the gantry height and sleeve depth information, the pile top height is calculated. Next, the lidar performs multi-frame scans of the pile, accumulating a high-density point cloud. Point cloud preprocessing includes RANSAC plane fitting and point cloud clustering to remove interference point clouds from the ground and sleeve areas. Cylinder fitting employs PCA principal direction estimation and the RANSAC algorithm under PCA direction constraints to determine the principal feature vector of the pile point cloud, the pile axis direction vector, and a point and radius on the cylinder axis. The pile bottom coordinates are obtained by projecting the lowest point in the cylinder point cloud onto the axis direction, while the pile top coordinates are calculated based on the pile bottom coordinates, the axis direction vector, and the known pile height. Finally, the pile coordinates and attitude information acquired in the lidar coordinate system are transformed to the world coordinate system. Combined with GNSS dual-antenna data, precise world coordinate system coordinates and attitude parameters of the pile are obtained, including pile bottom coordinates, pile top coordinates, roll angle, pitch angle, and depth information. This technical solution significantly improves the automation and accuracy of photovoltaic piling operations, reduces reliance on manual measurement, and ensures construction quality and efficiency.

[0041] More specifically, determining the position and attitude parameters of the pile column based on the pile column model and the pile top height includes: determining the axial direction vector of the pile column model and the coordinates of the lowest point projected onto the axial direction vector, and determining the coordinates of the lowest point as the pile bottom position coordinates in the position and attitude parameters; when the bottom of the pile column is below the ground, determining the pile top position coordinates in the position and attitude parameters after pile driving based on the pile bottom position coordinates and the pile top height.

[0042] In this embodiment, precise calculation of the pile position and attitude during photovoltaic piling is achieved through data fusion from multi-attitude sensors and LiDAR. Specifically, four attitude sensors on the vehicle body, boom, mid-arm, and forearm, combined with the gantry height and sleeve depth, accurately calculate the height of the pile top in the vehicle body coordinate system. This step ensures real-time and accurate measurement of the pile top height during piling operations. Subsequently, the pile is scanned using LiDAR to obtain a high-density point cloud. Through point cloud preprocessing and a cylinder fitting algorithm, the bottom coordinates and axial direction vector v of the pile in the LiDAR coordinate system are accurately identified. When the bottom of the pile is below ground level, the coordinates of the pile top in the LiDAR coordinate system can be calculated based on the previously calculated pile top height. Then, through coordinate transformation, the precise position of the pile top in the world coordinate system is obtained. The implementation of this series of technical solutions effectively improves the accuracy of photovoltaic piling pile positioning, ensures high-quality piling operations, reduces reliance on manual measurement, and improves construction efficiency.

[0043] Furthermore, the point cloud data of the piling machine is obtained by: constructing a high-density point cloud frame of the environmental point cloud in front of the piling machine by spatial alignment and accumulation of multiple frames, thereby obtaining the point cloud data.

[0044] In this embodiment, a high-density point cloud frame of the environment in front of the piling machine is constructed by accumulating multiple frames spatially aligned, thus obtaining point cloud data. This technical solution utilizes multi-frame point cloud information acquired by LiDAR at different time points, transforming these point clouds into the same reference coordinate system through pose transformation for accumulation, thereby enhancing the density and stability of the point cloud and improving the accuracy of subsequent cylindrical structure fitting. The point cloud accumulation process effectively reduces the impact of factors such as distance noise and insufficient reflectivity on the point cloud quality, providing a more accurate data foundation for subsequent calculation of pile bottom and pile top coordinates and evaluation of pile verticality. This design not only improves the accuracy and reliability of automated photovoltaic piling operations but also enables real-time monitoring of pile installation, ensuring construction quality.

[0045] Furthermore, determining the pile top height based on the aforementioned attitude data, fuselage parameter data, and pile parameter data includes: determining the end height of the boom of the pile driver based on the aforementioned attitude data and fuselage parameter data; and determining the aforementioned pile top height based on the aforementioned end height and pile parameter data.

[0046] The fuselage parameter data also includes information on the pylon height and sleeve depth.

[0047] In this embodiment, the pile top height calculation scheme based on multi-attitude sensors first acquires the installation coordinates of attitude sensors on the vehicle body, boom, middle boom, and forearm. Combined with the structural length of each boom segment, a step-by-step calculation method is used to determine the height of the forearm end in the vehicle body coordinate system. This process integrates data from various sensors in the vehicle body coordinate system, achieving accurate calculation of the pile top height through multi-sensor fusion, providing fundamental data for subsequent pile positioning. Furthermore, by combining the known gantry height and sleeve depth, this embodiment can accurately calculate the pile top height information, providing crucial parameter support for the automation and intelligentization of piling operations. By integrating the relevant data of the forearm end height, gantry, and sleeve, this embodiment can determine the position of the pile top in space in a more efficient and accurate manner, ensuring accurate pile positioning during the piling process, thereby effectively improving construction efficiency and project quality.

[0048] Specifically, after determining the axial direction vector of the pile model based on the pile model, the method further includes: constructing a coordinate system using the body of the pile driver, and determining the verticality of the pile based on the axial direction vector.

[0049] In this embodiment, determining the verticality of the pile is one of the key steps to ensure the quality and efficiency of photovoltaic piling projects. The axial direction vector is obtained from the lidar cylinder fitting and represents the actual direction of the pile. To determine whether the pile is vertical, it is necessary to compare the angular difference between this axial direction vector and the ideal vertical direction.

[0050] In three-dimensional space, the ideal vertical direction usually refers to the direction of gravity, i.e., the direction of the Earth's normal. Using the frame of the pile driver as a coordinate system, this can be simplified to a unit vector along the positive z-axis. Next, the angle between the axis direction vector and the vertical direction vector is calculated using the dot product of the two vectors. This angle is then used to determine the verticality of the pile.

[0051] In addition, the vertical situation can also be represented by the roll angle and pitch angle, which describe the degree of inclination of the pile relative to the vertical direction in the horizontal plane. The roll angle is the angle of rotation in the (xz) plane, while the pitch angle is the angle of rotation in the (yz) plane.

[0052] This embodiment can not only accurately determine the verticality of the piles, but also monitor and adjust them in real time as needed, ensuring the stability and reliability of the high-precision self-positioning system for photovoltaic piling columns. This verticality detection method based on the axis direction vector avoids the errors and uncertainties of traditional manual measurement methods, greatly improving construction efficiency and quality.

[0053] To enable those skilled in the art to better understand the technical solution of this application, the implementation process of the photovoltaic piling column positioning method of this application will be described in detail below with reference to specific embodiments.

[0054] This embodiment relates to a pile driver, whose sensors include two GNSS antennas, four attitude sensors, and one lidar. The specific installation locations are as follows: Figure 3 As shown, attitude sensors are installed on the body, boom, middle boom, and forearm respectively;

[0055] 1. Calculation of pile top height based on multi-attitude sensors:

[0056] Establish the vehicle coordinate system O at the midpoint of the dual antenna installation location. b -xyz, obtains the coordinates ri of the attitude sensor's installation position in the vehicle coordinate system by measurement: ri=[xi,yi,zi] T , i=0,1,2,3, i=0 body, 1 upper arm, 2 middle arm, 3 forearm.

[0057] Based on the structural parameters of the piling machine, define the length vector l of each boom segment. i :l i =[Li,0,0] T Li is the length;

[0058] From the vehicle reference point O b Starting from the beginning, the height of the forearm end can be calculated step by step according to the posture changes of each stage of the arm. Then, the pile top height is calculated using the known gantry height and sleeve depth.

[0059] 2. Calculation of pile bottom and top coordinates and verticality based on lidar:

[0060] Establish the lidar coordinate system O with the midpoint of the lidar. l -xyz.

[0061] Since single-frame lidar point clouds may have unstable factors such as distance noise and insufficient reflectivity, this embodiment constructs high-density point cloud frames by aligning and accumulating multiple frames in space to enhance the fitability of subsequent cylindrical structures.

[0062] ,in, For the point cloud of the i-th frame, To perform a pose transformation of the point cloud in this frame to a reference coordinate system, For the accumulated high-density point cloud, N is set to 5.

[0063] The point cloud scanned by lidar not only includes the stakes in front of the vehicle, but also other unrelated point cloud interference such as the ground and sleeves. Preprocessing will remove the point cloud from the interfering areas such as the ground and sleeves.

[0064] Preprocessing mainly includes operations such as plane fitting and point cloud clustering.

[0065] A planar model based on Random Sample Consensus (RANSAC) was used to fit and identify point sets belonging to the ground. Euclidean cluster extraction was then performed on the point cloud after ground removal to obtain a series of independent point cloud clusters. Each cluster was then filtered based on the following features: volume threshold, height range, lower and upper limits of point count, and minimum bounding box shape (whether it approximates a columnar shape). Finally, irrelevant point clouds were effectively removed through preprocessing.

[0066] Cylinder fitting: performed using a combination of RANSAC and PCA methods;

[0067] 1) Obtain the principal feature vector based on PCA principal direction estimation. (The direction corresponding to the largest eigenvalue)

[0068] 2) Fitting the RANSAC cylindrical model under PCA directional constraints:

[0069] When generating a model using RANSAC, the constraint axis direction d satisfies: ;

[0070] This is the allowable deviation angle.

[0071] RANSAC optimizes the model parameters, yielding preliminary cylinder parameters: axis direction vector. A point P on the axis of the cylinder, and radius r.

[0072] Pile bottom coordinate calculation: Find the lowest point using the fitted cylindrical point cloud, project it onto the cylinder axis, and the coordinates of this projected point are the pile bottom coordinates. ;

[0073] Calculation of pile top coordinates (when the pile bottom is above ground): using the pile bottom coordinates and the axis direction vector. Known pile height The coordinates of the top center point can be calculated as follows: ;

[0074] Calculation of pile top coordinates (when the pile bottom is below ground level): In this case, the pile bottom coordinates are actually the coordinates of the bottom of the pile exposed above ground level, and need to be combined with the obtained pile top height ht (converted to the lidar coordinate system): .

[0075] Furthermore, by combining the GNSS satellite antenna, the coordinates of the pile bottom and pile top are converted into the world coordinate system. , The axis direction vector is transformed into the vehicle coordinate system, and the verticality of the pile is represented by roll and pitch. The depth is the obtained pile top height. t .

[0076] This embodiment relates to a specific method for positioning photovoltaic piling columns, such as... Figure 4 As shown, it specifically includes the following:

[0077] This embodiment is equipped with a GNSS dual-antenna module; four attitude sensors (IMUs) are respectively installed on the vehicle body, upper arm, middle arm, and lower arm; a lidar (LiDAR) is installed at the front of the vehicle for scanning the stakes; and a computing unit (industrial computer) is used for multi-frame point cloud registration, cylinder fitting, coordinate transformation, and verticality calculation.

[0078] First, known quantities are obtained through measurement: the structural lengths of the upper arm, middle arm, and forearm; the installation positions of the four attitude sensors, lidar, and GNSS dual antennas; and the height of the pile.

[0079] The first step is to start from the vehicle body reference point O. b Starting from the beginning, the height of the forearm end can be calculated step by step according to the posture changes of each stage of the arm. Then, the pile top height is calculated using the known gantry height and sleeve depth.

[0080] The second step is based on the calculation of the pile bottom and pile top positions and pile attitude using lidar, which includes multi-frame accumulation of point cloud, point cloud preprocessing, cylinder fitting, and calculation of the verticality of the pile top and pile bottom coordinates.

[0081] This embodiment constructs high-density point cloud frames by spatially aligning and accumulating multiple frames to enhance the fitability of subsequent cylindrical structures.

[0082] Where Pi is the point cloud of the i-th frame, Ti→ref is the pose transformation of the point cloud of that frame to the reference coordinate system, Pacc is the accumulated high-density point cloud, and N is set to 5.

[0083] This embodiment preprocesses the point cloud by using RANSAC plane fitting and point cloud clustering to remove point clouds in interfering areas such as the ground and sleeve.

[0084] Furthermore, a cylindrical fitting method is performed on the remaining point cloud using a combination of RANSAC and PCA. This method obtains the principal feature vector based on the principal orientation estimation of PCA. (Direction corresponding to the largest eigenvalue), RANSAC cylindrical model fitting under PCA direction constraints:

[0085] When generating a model using RANSAC, the constraint axis direction d satisfies: , This is the allowable deviation angle.

[0086] R yields preliminary cylinder parameters: axis direction vector. A point P on the axis of the cylinder, and radius r.

[0087] Further calculations were performed on the coordinates and direction vectors of the pile bottom and pile top in the lidar coordinate system.

[0088] Pile bottom coordinate calculation: Find the lowest point using the fitted cylindrical point cloud, project it onto the cylinder axis, and the coordinates of this projected point are the pile bottom coordinates. ;

[0089] Calculation of pile top coordinates (when the pile bottom is above ground): using the pile bottom coordinates and the axis direction vector. Known pile height The coordinates of the top center point can be calculated as follows: ;

[0090] Pile top coordinate calculation (when the pile bottom is below ground level): In this case, the pile bottom coordinates are actually the coordinates of the bottom of the pile column exposed above ground level, and need to be combined with the obtained pile top height. t (Transform to the lidar coordinate system): ;

[0091] Finally, by combining the GNSS dual-antenna data, the coordinates of the pile bottom and pile top were converted into the world coordinate system. , The axis direction vector is transformed into the vehicle coordinate system, and the verticality of the pile is represented by roll and pitch. The depth is the pile top height calculated by multi-attitude sensors. t .

[0092] This embodiment calculates the height of the pile apex using attitude sensors (IMUs) on multiple articulated arms, acquires the coordinates of the pile bottom and top, and the pile's tilt in real time during operation using LiDAR, and combines this with GNSS positioning information to calculate the precise coordinates and verticality of the pile in the world coordinate system (further explanation: pile top coordinates, pile bottom coordinates, roll angle, and pitch angle). This embodiment can automatically and accurately provide the pile position, ensuring real-time performance and stability, without requiring external surveying personnel, effectively reducing the labor costs for construction units.

[0093] This application also provides a positioning device for photovoltaic piling columns. It should be noted that the positioning device for photovoltaic piling columns in this application can be used to execute the positioning method for photovoltaic piling columns provided in this application. This device is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0094] The following describes the positioning device for photovoltaic piling columns provided in the embodiments of this application.

[0095] Figure 5 This is a schematic diagram of a positioning device for photovoltaic piling columns according to an embodiment of this application. Figure 5 As shown, the device includes:

[0096] The acquisition unit 51 is used to acquire point cloud data, attitude data, body parameter data and pile parameter data of the pile driver. The attitude data is acquired by attitude sensors installed on the body and each arm of the pile driver, and the point cloud data is acquired by the laser radar of the pile driver to acquire the environmental point cloud in front of the pile driver.

[0097] The first determining unit 52 is used to determine the pile top height of the pile based on the above attitude data, the above fuselage parameter data, and the above pile parameter data, and to determine the position attitude parameters of the pile based on the above point cloud data and the above pile top height, wherein the above position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude.

[0098] The positioning unit 53 is used to perform positioning processing on the pile column based on the GNSS positioning information of the pile driver and the position and attitude parameters to obtain the positioning data of the pile column, wherein the positioning data is the coordinate data of the pile column in the world coordinate system.

[0099] In this embodiment, the acquisition unit is used to acquire point cloud data, attitude data, body parameter data, and pile parameter data of the pile driver. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver, and the point cloud data is obtained by the LiDAR of the pile driver collecting the environmental point cloud in front of the pile driver. The first determination unit is used to determine the pile top height based on the attitude data, body parameter data, and pile parameter data, and to determine the pile position and attitude parameters based on the point cloud data and pile top height. The position and attitude parameters include the pile bottom coordinates, pile top coordinates, and pile body attitude. The positioning unit is used to perform positioning processing on the pile based on the GNSS positioning information and position and attitude parameters of the pile driver to obtain the pile positioning data, which is the coordinate data of the pile in the world coordinate system. By integrating multiple sensors, including GNSS positioning equipment, attitude sensors, and LiDAR, the structural attitude information of the vehicle body and each arm segment, as well as the point cloud data in front of the pile driver, are first accurately acquired. Then, based on the collected information, the pile top height in the vehicle coordinate system is calculated. Combined with the LiDAR scanning results, the pile bottom coordinates, pile top coordinates, and pile attitude are determined. Finally, using the GNSS positioning information of the pile driver, the pile's position and attitude parameters are converted to the world coordinate system, thus obtaining high-precision pile coordinate data. This solution not only improves positioning accuracy but also automates the process, eliminating the need for manual intervention, significantly improving construction efficiency, reducing labor costs, and providing a stable and reliable intelligent solution for photovoltaic piling operations. Therefore, it solves the problem of insufficient positioning accuracy in existing pile positioning schemes.

[0100] As an optional scheme, the first determining unit includes an identification module, a clustering processing module, and a first determining module; the identification module is used to identify the ground point cloud in the point cloud data by fitting a plane model based on Random Sample Consensus (RANSAC), and remove the ground point cloud from the point cloud data to obtain the target point cloud data; the clustering processing module is used to cluster the target point cloud data by using a clustering algorithm based on Euclidean distance to obtain clustered point cloud clusters, and to perform feature filtering processing on the clustered point cloud clusters to determine the pile point cloud of the pile; the first determining module is used to determine the position and attitude parameters of the pile based on the pile point cloud and the pile top height.

[0101] In one optional scheme, the first determining module includes a first determining submodule and a second determining submodule; the first determining submodule is used to determine the principal feature vector of the pile point cloud based on the principal direction estimation algorithm of PCA, and to perform RANSAC cylindrical model fitting on the pile point cloud according to the principal feature vector to obtain the pile model; the second determining submodule is used to determine the position and attitude parameters of the pile according to the pile model and the pile top height.

[0102] In one optional scheme, the second determining submodule includes a third determining submodule and a fourth determining submodule; the third determining submodule is used to determine the axial direction vector of the pile model and the coordinates of the lowest point projected onto the axial direction vector based on the pile model, and to determine the coordinates of the lowest point as the pile bottom position coordinates in the position attitude parameters; the fourth determining submodule is used to determine the pile top position coordinates in the position attitude parameters after pile driving based on the pile bottom position coordinates and the pile top height when the bottom of the pile is below the ground.

[0103] In one alternative approach, the acquisition unit includes a construction module, which is used to construct a high-density point cloud frame of the environmental point cloud in front of the pile driver by means of multi-frame spatial alignment and accumulation, thereby obtaining the point cloud data.

[0104] In one optional scheme, the first determining unit includes a second determining module and a third determining module; the second determining module is used to determine the end height of the boom of the pile driver based on the above-mentioned attitude data and the above-mentioned fuselage parameter data; the third determining module is used to determine the top height of the pile based on the above-mentioned end height and the above-mentioned pile parameter data.

[0105] In an alternative embodiment, the device further includes a second determining unit, which, after determining the axial direction vector of the pile model based on the pile model, constructs a coordinate system with the body of the pile driver and determines the verticality of the pile based on the axial direction vector.

[0106] The aforementioned positioning device for photovoltaic piling columns includes a processor and a memory. The acquisition unit, the first determining unit, the positioning unit, etc., are all stored as program units in the memory, and the processor executes the program units stored in the memory to achieve the corresponding functions. All of the above modules are located in the same processor; alternatively, the above modules may be located in different processors in any combination.

[0107] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured; adjusting kernel parameters can address the insufficient positioning accuracy issues in existing stake positioning methods.

[0108] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0109] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the photovoltaic piling column positioning method.

[0110] Specifically, the positioning methods for photovoltaic piling columns include:

[0111] Step S201: Obtain point cloud data, attitude data, body parameter data and pile parameter data of the pile driver. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver. The point cloud data is obtained by the laser radar of the pile driver collecting the environmental point cloud in front of the pile driver.

[0112] Step S202: Determine the pile top height based on the above attitude data, the above fuselage parameter data, and the above pile parameter data, and determine the position attitude parameters of the above pile based on the above point cloud data and the above pile top height, wherein the above position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude.

[0113] Step S203: Based on the GNSS positioning information of the pile driver and the position and attitude parameters, the pile is positioned to obtain the positioning data of the pile, wherein the positioning data is the coordinate data of the pile in the world coordinate system.

[0114] This invention provides a processor for running a program, wherein the program executes the photovoltaic piling column positioning method.

[0115] Specifically, the positioning methods for photovoltaic piling columns include:

[0116] Step S201: Obtain point cloud data, attitude data, body parameter data and pile parameter data of the pile driver. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver. The point cloud data is obtained by the laser radar of the pile driver collecting the environmental point cloud in front of the pile driver.

[0117] Step S202: Determine the pile top height based on the above attitude data, the above fuselage parameter data, and the above pile parameter data, and determine the position attitude parameters of the above pile based on the above point cloud data and the above pile top height, wherein the above position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude.

[0118] Step S203: Based on the GNSS positioning information of the pile driver and the position and attitude parameters, the pile is positioned to obtain the positioning data of the pile, wherein the positioning data is the coordinate data of the pile in the world coordinate system.

[0119] This invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps:

[0120] Step S201: Obtain point cloud data, attitude data, body parameter data and pile parameter data of the pile driver. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver. The point cloud data is obtained by the laser radar of the pile driver collecting the environmental point cloud in front of the pile driver.

[0121] Step S202: Determine the pile top height based on the above attitude data, the above fuselage parameter data, and the above pile parameter data, and determine the position attitude parameters of the above pile based on the above point cloud data and the above pile top height, wherein the above position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude.

[0122] Step S203: Based on the GNSS positioning information of the pile driver and the position and attitude parameters, the pile is positioned to obtain the positioning data of the pile, wherein the positioning data is the coordinate data of the pile in the world coordinate system.

[0123] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0124] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps:

[0125] Step S201: Obtain point cloud data, attitude data, body parameter data and pile parameter data of the pile driver. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver. The point cloud data is obtained by the laser radar of the pile driver collecting the environmental point cloud in front of the pile driver.

[0126] Step S202: Determine the pile top height based on the above attitude data, the above fuselage parameter data, and the above pile parameter data, and determine the position attitude parameters of the above pile based on the above point cloud data and the above pile top height, wherein the above position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude.

[0127] Step S203: Based on the GNSS positioning information of the pile driver and the position and attitude parameters, the pile is positioned to obtain the positioning data of the pile, wherein the positioning data is the coordinate data of the pile in the world coordinate system.

[0128] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0129] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0130] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0131] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0132] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0133] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0134] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0135] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0136] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0137] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0138] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for positioning photovoltaic piling columns, characterized in that, include: The point cloud data, attitude data, body parameter data and pile parameter data of the pile driver are acquired. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver. The point cloud data is obtained by the lidar of the pile driver collecting the environmental point cloud in front of the pile driver. The pile top height is determined based on the attitude data, the fuselage parameter data, and the pile parameter data. The position and attitude parameters of the pile are determined based on the point cloud data and the pile top height. The position and attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude. The pile is positioned using the GNSS positioning information of the pile driver and the position and attitude parameters to obtain the positioning data of the pile, wherein the positioning data is the coordinate data of the pile in the world coordinate system.

2. The method according to claim 1, characterized in that, Determining the position and attitude parameters of the pile based on the point cloud data and the pile top height includes: By fitting a plane model based on Random Sample Consensus (RANSAC), ground point clouds in the point cloud data are identified, and the ground point clouds in the point cloud data are removed to obtain the target point cloud data. The target point cloud data is clustered using a clustering algorithm based on Euclidean distance to obtain clustered point cloud clusters. Feature filtering is then performed on the clustered point cloud clusters to determine the point cloud of the pile. The position and attitude parameters of the pile are determined based on the pile point cloud and the pile top height.

3. The method according to claim 2, characterized in that, The position and attitude parameters of the pile are determined based on the pile point cloud and the pile top height, including: The principal orientation estimation algorithm based on PCA is used to determine the principal feature vector of the pile point cloud, and the pile point cloud is fitted with a cylindrical model of RANSAC based on the principal feature vector to obtain the pile model. The position and attitude parameters of the pile are determined based on the pile model and the pile top height.

4. The method according to claim 3, characterized in that, Determining the position and attitude parameters of the pile column based on the pile column model and the pile top height includes: Based on the pile model, determine the axial direction vector of the pile model and the coordinates of the lowest point projected onto the axial direction vector, and determine the coordinates of the lowest point as the pile bottom position coordinates in the position attitude parameters; When the bottom of the pile is below the ground, the pile top position coordinates in the position and attitude parameters after the pile is driven are determined based on the pile bottom position coordinates and the pile top height.

5. The method according to claim 1, characterized in that, Obtain point cloud data of the piling machine, including: The point cloud data is obtained by constructing a high-density point cloud frame of the environmental point cloud in front of the pile driver through multi-frame spatial alignment and accumulation.

6. The method according to claim 1, characterized in that, The pile top height is determined based on the attitude data, the fuselage parameter data, and the pile parameter data, including: The height of the boom end of the pile driver is determined based on the attitude data and the fuselage parameter data. The pile top height is determined based on the end height and the pile parameter data.

7. The method according to claim 1, characterized in that, After determining the axial direction vector of the pile column model based on the pile column model, the method further includes: A coordinate system is constructed using the body of the pile driver, and the verticality of the pile is determined based on the axial direction vector.

8. A positioning device for photovoltaic piling columns, characterized in that, include: The acquisition unit is used to acquire point cloud data, attitude data, body parameter data and pile parameter data of the pile driver. The attitude data is collected by attitude sensors installed on the body and each arm of the pile driver, and the point cloud data is obtained by the lidar of the pile driver collecting the environmental point cloud in front of the pile driver. The first determining unit is used to determine the pile top height of the pile based on the attitude data, the fuselage parameter data, and the pile parameter data, and to determine the position attitude parameters of the pile based on the point cloud data and the pile top height, wherein the position attitude parameters include the pile bottom position coordinates, the pile top position coordinates, and the pile body attitude. The positioning unit is used to perform positioning processing on the pile column based on the GNSS positioning information of the pile driver and the position and attitude parameters to obtain the positioning data of the pile column, wherein the positioning data is the coordinate data of the pile column in the world coordinate system.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the photovoltaic piling column positioning method according to any one of claims 1 to 7.

10. An electronic device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including a method for performing the positioning method for photovoltaic piling columns according to any one of claims 1 to 7.

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