A method and system for parameter calibration of an airborne lidar for a bucket wheel stacker-reclaimer.

Abstract

This invention belongs to the field of lidar parameter calibration technology, specifically providing a method and system for calibrating the parameters of an airborne lidar for a bucket wheel stacker-reclaimer. The method includes: calculating the conversion relationship between lidar scanning data and 3D point cloud data based on the relative positional relationship of the coordinate system; then scanning the field data through the movement of the bucket wheel stacker-reclaimer, and converting the lidar-returned data into 3D point cloud data based on the initial measured values; then fitting the ground data from the 3D point cloud data using a random sampling consistent plane fitting method, designing an objective function, and using a genetic algorithm to calculate the lidar's installation parameters. The installation parameters of the airborne lidar for the cantilever bucket wheel stacker-reclaimer obtained through this scheme have high accuracy and are easy to operate, requiring no total station or reflective strips, thus providing a foundation for the design of subsequent automatic stacking and reclaiming strategies for bucket wheel stackers.

Description

Technical Field

[0001] This invention relates to the field of lidar parameter calibration technology, and more specifically, to a parameter calibration method and system for an airborne lidar of a bucket wheel stacker-reclaimer. Background Technology

[0002] Cantilever bucket wheel stacker-reclaimers are crucial operational equipment in steel companies' raw material yards. To achieve full automation and improve operational efficiency, many companies install lidar systems on the cantilever of the reclaimer. By translating, pitching, and rotating the stacker-reclaimer, a 3D point cloud model of the material pile is acquired in real time. Analysis of this model allows for calculation of the bucket wheel's entry point and angle during reclaiming, as well as the pile position and height, ultimately achieving full automation. Accurate acquisition of the 3D model relies on accurate calibration of the lidar's installation parameters. Since the scanning area in a raw material yard is large (radius of tens of meters), even minor deviations in installation parameters can lead to significant errors in the 3D model. Therefore, calibrating the installation parameters of the cantilever bucket wheel stacker-reclaimer's onboard lidar is a prerequisite for automated material reclaiming in bulk material yards.

[0003] The installation position of a lidar sensor is not easily measured directly, as it involves three translational parameters and three rotational parameters. Currently, most domestic companies calibrate the installation parameters of lidar sensors mounted on bucket wheel stacker-reclaimers using total stations and reflectors. This method requires additional calibration equipment, increasing calibration costs, and necessitates attaching multiple reflectors over a large area of ​​the material pile. The installation position of the reflectors directly affects the accuracy of the calibration parameters. Furthermore, the calibration process requires changing the position of the total station, further introducing calibration errors.

[0004] In summary, developing a calibration method for the installation parameters of an airborne lidar for a bucket wheel stacker-reclaimer that is easy to operate and meets the accuracy requirements for fully automatic material handling is a key technology for achieving full automation of stacker-reclaim operations in the raw material yard of steel enterprises. Summary of the Invention

[0005] This invention addresses the technical problem of large calibration errors in the installation parameters of the airborne lidar of bucket wheel stacker-reclaimers in the prior art.

[0006] This invention provides a method for calibrating the parameters of an onboard lidar for a bucket wheel stacker-reclaimer, comprising the following steps:

[0007] S1, establish coordinate systems for the joints of the bucket wheel stacker-reclaimer, and establish a lidar coordinate system with the lidar optical center as the origin;

[0008] S2 uses lidar to scan and collect on-site data;

[0009] S3, obtain the initial values ​​of the installation parameters of the lidar;

[0010] S4, based on the initial values ​​and coordinate transformation relationships, converts the collected field data into three-dimensional point cloud data in the world coordinate system;

[0011] S5, extract the ground point cloud data containing the material yard ground from the 3D point cloud data;

[0012] S6. Use the Random Sample Consensus (RSC) plane fitting method to fit the above ground data. The points in the fitting plane are the points on the ground.

[0013] S7 converts points on the ground into points in the lidar coordinate system using coordinates.

[0014] S8. Given that the z-axis coordinates of all points on the ground are 0 and they are all on the same plane, design the objective function.

[0015] S9 calculates a set of installation parameters for the lidar based on the objective function design algorithm.

[0016] Preferably, S1 specifically includes:

[0017] The translation, rotation, and pitch joints of the bucket wheel stacker-reclaimer are each placed in a coordinate system. Then, the conversion relationship between the lidar scanning data and the 3D point cloud data is calculated based on the relative positional relationship of the coordinate systems.

[0018] Preferably, S2 specifically includes:

[0019] The data collected on site is scanned and acquired by the walking, rotating and pitching of the bucket wheel stacker-reclaimer. The data returned by the lidar includes two parameters (r, θ), where r is the distance returned by the lidar scan and θ is the scanning angle in the single-line laser scan.

[0020] Preferably, S3 specifically includes:

[0021] Three offset parameters were obtained by direct measurement on the drawings, and three rotation parameters were obtained by measurement on the lidar using a handheld level.

[0022] Preferably, S9 specifically includes:

[0023] Design a genetic algorithm based on the objective function, set the upper and lower bounds of the installation parameters, the initial population size and the number of iterations, and run the genetic algorithm to calculate a set of installation parameters for the lidar.

[0024] Preferably, S9 is followed by S10:

[0025] Based on the installation parameters obtained in step S9, step S4 is executed again to verify whether a good 3D point cloud model of the material yard can be obtained. If the point cloud accuracy meets the requirements of the automatic operation of the bucket wheel stacker-reclaimer, the calculation is stopped, and satisfactory installation parameters of the lidar are obtained. If the point cloud accuracy does not meet the requirements of the automatic operation of the bucket wheel stacker-reclaimer, steps S4 to S9 are executed again with the parameters obtained in step S9 as the initial values ​​until satisfactory lidar installation parameters are obtained.

[0026] Preferably, the objective function is min{abs(Ground)} z )+std(Ground z )}, where Ground z The z-coordinate matrix represents the ground point cloud, where abs represents the absolute value and std represents the standard deviation.

[0027] This invention also provides a parameter calibration system for an airborne lidar of a bucket wheel stacker-reclaimer. The system is used to implement the steps of a parameter calibration method for the airborne lidar of a bucket wheel stacker-reclaimer, specifically including:

[0028] The coordinate system establishment module is used to establish a fixed world coordinate system for the bucket wheel stacker-reclaimer and to establish a lidar coordinate system with the lidar optical center as the origin.

[0029] The point cloud data acquisition module is used to scan and collect field data using LiDAR; obtain the initial values ​​of the LiDAR installation parameters; and convert the collected field data into three-dimensional point cloud data in the world coordinate system based on the initial values ​​and coordinate transformation relationships.

[0030] The ground point cloud data module is used to extract ground point cloud data containing the material yard ground from the 3D point cloud data; the above ground data is fitted using the Random Sample Consensus plane fitting method, and the points in the fitted plane are the points on the ground;

[0031] The installation parameter calculation module is used to convert points on the ground into points in the lidar coordinate system. Based on the fact that the z-axis coordinate of all points on the ground is 0 and they are all on the same plane, an objective function is designed. Based on the objective function, an algorithm is designed to calculate a set of lidar installation parameters.

[0032] The present invention also provides an electronic device, including a memory and a processor, wherein the processor is used to execute a computer management program stored in the memory to implement the parameter calibration method of the airborne lidar of the bucket wheel stacker-reclaimer.

[0033] The present invention also provides a computer-readable storage medium storing a computer management program thereon, wherein the computer management program, when executed by a processor, implements the steps of a parameter calibration method for an onboard lidar of a bucket wheel stacker-reclaimer.

[0034] Beneficial Effects: This invention provides a parameter calibration method and system for an airborne lidar on a bucket wheel stacker-reclaimer. The method includes: establishing a coordinate system; calculating the conversion relationship between lidar scanning data and 3D point cloud data based on the relative positional relationship of the coordinate system; then scanning the field data through the movement of the bucket wheel stacker-reclaimer; and converting the data returned by the lidar into 3D point cloud data based on the initial measured values. Next, a random sampling consistent plane fitting method is used to fit the ground data in the 3D point cloud data, and an objective function is designed using the characteristics of coplanar data on the ground with zero height. A genetic algorithm is then used to calculate the installation parameters of the lidar. The installation parameters of the airborne lidar on the cantilever bucket wheel stacker-reclaimer obtained by this scheme for ground calibration at the material pile site have high accuracy and are easy to operate, requiring no total station or reflective strips, thus providing a foundation for the subsequent design of automatic stacking and reclaiming strategies for bucket wheel stackers. Attached Figure Description

[0035] Figure 1 A flowchart illustrating a parameter calibration method for an airborne lidar of a bucket wheel stacker-reclaimer provided by the present invention;

[0036] Figure 2 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention;

[0037] Figure 3 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention;

[0038] Figure 4 A schematic diagram of the various coordinate systems provided by the present invention;

[0039] Figure 5 This is a schematic diagram of a three-dimensional point cloud of the ground captured by the present invention;

[0040] Figure 6 The image shows a 3D point cloud model of a LiDAR scanner with calibrated installation parameters, provided by this invention. Detailed Implementation

[0041] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0042] Figure 1 The present invention provides a method as shown in the appendix. Figure 1The diagram shown is an implementation flowchart of a parameter calibration method for an airborne lidar of a bucket wheel stacker-reclaimer according to an embodiment of the present invention. It illustrates the specific implementation steps of the method, including:

[0043] S1. Based on the structure of the cantilever bucket wheel stacker-reclaimer, establish the coordinate systems for the bucket wheel's translation, rotation, and pitch joints, as well as the world coordinate system and the lidar coordinate system with the lidar optical center as the origin, as shown in the appendix. Figure 4 As shown; the lidar coordinate system is O5x5y5z5, and the three coordinate systems for the translation, rotation, and pitch joints are O2x2y2z2, O3x3y3z3, and O4x4y4z4, respectively. The world coordinate system is O1x1y1z1.

[0044] S2. Use lidar to scan and collect field data. The bucket wheel stacker-reclaimer scans and collects field data by moving, rotating, and pitching. The lidar-returned data contains two parameters (r, θ), where r is the distance returned by the lidar scan, and θ is the scanning angle in a single-line laser scan.

[0045] S3. Obtain the initial values ​​of the lidar installation parameters. In this example, the initial values ​​of the three offset parameters are measured on the drawing. The initial offset values ​​in the x, y, and z directions are 4.2 meters, 33 meters, and 1.5 meters, respectively. The initial values ​​of the three rotation parameters around x, y, and z are measured using a handheld level, respectively, as 1 degree, 0.4 degrees, and 4 degrees.

[0046] S4. Based on the coordinate transformation relationship in S1 and the initial values ​​of the installation parameters in S3, convert the data collected by the lidar in S2 into three-dimensional point cloud data;

[0047] S5. Extract the ground data from the 3D point cloud data in S4. By restricting the coordinates in the x, y, and z directions, extract the 3D point cloud data containing the ground of the material yard;

[0048] S6. Use the RANSAC plane fitting method to fit the above ground data. The in-plane points of the fitted plane can be considered as points on the ground, as shown in the attached figure. Figure 5 As shown;

[0049] S7. Calculate the coordinates of the points on the ground in the lidar coordinate system, i.e., the scanner coordinate system, based on the coordinate transformation relationship in S1;

[0050] S8. Design the objective function. Points on the ground have two characteristics: first, the z-axis coordinate of all points on the ground is 0; second, all points on the ground lie on the same plane. Design the objective function based on these two characteristics. In this example, the objective function is designed as min{abs(Ground z )+std(Ground z )}, where Groundz The z-coordinate matrix represents the ground point cloud, where abs represents the absolute value and std represents the standard deviation.

[0051] S9. Design a genetic algorithm based on the objective function established in S8, setting the upper and lower bounds of the calibration parameters, the initial population size, and the number of iterations. In this example, the upper and lower bounds of the offset parameter are set within ±2 meters of the initial value, the upper and lower bounds of the rotation parameter are set within ±5 degrees of the initial value, the population size is set to 4, and the number of iterations is set to 50. Run the genetic algorithm to obtain a set of installation parameter values;

[0052] S10. Based on the installation parameters obtained in S9, re-execute S4 to verify whether a good 3D point cloud model of the material yard can be obtained. If the point cloud accuracy meets the requirements of the automatic operation of the bucket wheel stacker-reclaimer, the calculation stops, and satisfactory installation parameters for the lidar are obtained. If the point cloud accuracy does not meet the requirements of the automatic operation of the bucket wheel stacker-reclaimer, the steps S4 to S9 are re-executed with the parameters obtained in S9 as the initial values ​​until satisfactory lidar installation parameters are obtained. In this example, the final offset parameters along the x, y, and z directions are 4.6 meters, 36 meters, and 1.69 meters, respectively, and the initial values ​​of the rotation parameters around x, y, and z are 1.3 degrees, 0.12 degrees, and 3.9 degrees, respectively.

[0053] S11. Using the installation parameters of the lidar calculated in S10, draw the 3D point cloud data model of the material yard according to S4, as shown in the attached figure. Figure 6 As shown.

[0054] This invention also provides a parameter calibration system for an airborne lidar of a bucket wheel stacker-reclaimer. The system is used to implement the steps of the parameter calibration method for the airborne lidar of the bucket wheel stacker-reclaimer as described above, specifically including:

[0055] The coordinate system establishment module is used to establish a fixed world coordinate system for the bucket wheel stacker-reclaimer and to establish a lidar coordinate system with the lidar optical center as the origin.

[0056] The point cloud data acquisition module is used to scan and collect field data using LiDAR; obtain the initial values ​​of the LiDAR installation parameters; and convert the collected field data into three-dimensional point cloud data in the world coordinate system based on the initial values ​​and coordinate transformation relationships.

[0057] The ground point cloud data module is used to extract ground point cloud data containing the material yard ground from the 3D point cloud data; the above ground data is fitted using the Random Sample Consensus plane fitting method, and the points in the fitted plane are the points on the ground;

[0058] The installation parameter calculation module is used to convert points on the ground into points in the lidar coordinate system. Based on the fact that the z-axis coordinate of all points on the ground is 0 and they are all on the same plane, an objective function is designed. Based on the objective function, an algorithm is designed to calculate a set of lidar installation parameters.

[0059] Please see Figure 2 This is a schematic diagram illustrating an embodiment of the electronic device provided in this invention. For example... Figure 2 As shown, an embodiment of the present invention provides an electronic device, including a memory 1310, a processor 1320, and a computer program 1311 stored in the memory 1310 and executable on the processor 1320. When the processor 1320 executes the computer program 1311, it performs the following steps: S1, establishing coordinate systems for the joints of the bucket wheel stacker-reclaimer, and establishing a laser radar coordinate system with the optical center of the laser radar as the origin.

[0060] S2 uses lidar to scan and collect on-site data;

[0061] S3, obtain the initial values ​​of the installation parameters of the lidar;

[0062] S4, based on the initial values ​​and coordinate transformation relationships, converts the collected field data into three-dimensional point cloud data in the world coordinate system;

[0063] S5, extract the ground point cloud data containing the material yard ground from the 3D point cloud data;

[0064] S6. Use the Random Sample Consensus (RSC) plane fitting method to fit the above ground data. The points in the fitting plane are the points on the ground.

[0065] S7 converts points on the ground into points in the lidar coordinate system using coordinates.

[0066] S8. Given that the z-axis coordinates of all points on the ground are 0 and they are all on the same plane, design the objective function.

[0067] S9 calculates a set of installation parameters for the lidar based on the objective function design algorithm.

[0068] Please see Figure 3 This is a schematic diagram illustrating an embodiment of a computer-readable storage medium provided by the present invention. (See diagram below.) Figure 3 As shown, this embodiment provides a computer-readable storage medium 1400, on which a computer program 1411 is stored. When the computer program 1411 is executed by a processor, it performs the following steps:

[0069] S1, establish coordinate systems for the joints of the bucket wheel stacker-reclaimer, and establish a lidar coordinate system with the lidar optical center as the origin;

[0070] S2 uses lidar to scan and collect on-site data;

[0071] S3, obtain the initial values ​​of the installation parameters of the lidar;

[0072] S4, based on the initial values ​​and coordinate transformation relationships, converts the collected field data into three-dimensional point cloud data in the world coordinate system;

[0073] S5, extract the ground point cloud data containing the material yard ground from the 3D point cloud data;

[0074] S6. Use the Random Sample Consensus (RSC) plane fitting method to fit the above ground data. The points in the fitting plane are the points on the ground.

[0075] S7 converts points on the ground into points in the lidar coordinate system using coordinates.

[0076] S8. Given that the z-axis coordinates of all points on the ground are 0 and they are all on the same plane, design the objective function.

[0077] S9 calculates a set of installation parameters for the lidar based on the objective function design algorithm.

[0078] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0079] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0080] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for calibrating the parameters of an onboard lidar for a bucket wheel stacker-reclaimer, characterized in that, Includes the following steps: S1, establish coordinate systems for the joints of the bucket wheel stacker-reclaimer, and establish a lidar coordinate system with the lidar optical center as the origin; S2 uses lidar to scan and collect on-site data; S3, obtain the initial values ​​of the installation parameters of the lidar; S4, based on the initial values ​​and coordinate transformation relationships, converts the collected field data into three-dimensional point cloud data in the world coordinate system; S5, extracts ground point cloud data containing the material yard ground from the 3D point cloud data; S6, use the random sampling consistent plane fitting method to fit the ground point cloud data, and the points in the fitting plane are the points on the ground; S7 converts points on the ground into points in the lidar coordinate system using coordinates. S8. Given that the z-axis coordinates of all points on the ground are 0 and they are all on the same plane, design the objective function. S9, calculates a set of installation parameters for the lidar based on the objective function design algorithm; S1 specifically includes: Establish coordinate systems for the translation, rotation, and pitch joints of the bucket wheel stacker-reclaimer, and then calculate the conversion relationship between the lidar scanning data and the 3D point cloud data based on the relative positional relationship of the coordinate systems. The objective function is: ,in The z-coordinate matrix represents the ground point cloud, where abs represents the absolute value and std represents the standard deviation.

2. The parameter calibration method for the airborne lidar of the bucket wheel stacker-reclaimer according to claim 1, characterized in that, S2 specifically includes: The lidar scans and collects field data by moving, rotating, and pitching the bucket wheel stacker-reclaimer. The data returned by the lidar includes two parameters ( r, θ ), r This refers to the distance returned by the lidar scan. θ This refers to the scanning angle in laser single-line scanning.

3. The parameter calibration method for the airborne lidar of the bucket wheel stacker-reclaimer according to claim 1, characterized in that, S3 specifically includes: Three offset parameters were obtained by direct measurement on the drawings, and three rotation parameters were obtained by measurement on the lidar using a handheld level.

4. The parameter calibration method for the airborne lidar of the bucket wheel stacker-reclaimer according to claim 1, characterized in that, S9 specifically includes: Design a genetic algorithm based on the objective function, set the upper and lower bounds of the installation parameters, the initial population size and the number of iterations, and run the genetic algorithm to calculate a set of installation parameters for the lidar.

5. The parameter calibration method for the airborne lidar of the bucket wheel stacker-reclaimer according to claim 1, characterized in that, S9 is followed by S10: Based on the installation parameters obtained in step S9, step S4 is executed again to verify whether a good 3D point cloud model of the material yard can be obtained. If the point cloud accuracy meets the requirements of the automatic operation of the bucket wheel stacker-reclaimer, the calculation is stopped, and satisfactory installation parameters of the lidar are obtained. If the point cloud accuracy does not meet the requirements of the automatic operation of the bucket wheel stacker-reclaimer, steps S4 to S9 are executed again with the parameters obtained in step S9 as the initial values ​​until satisfactory lidar installation parameters are obtained.

6. A parameter calibration system for an onboard lidar of a bucket wheel stacker-reclaimer, characterized in that, The system is used to implement the parameter calibration method for the airborne lidar of the bucket wheel stacker-reclaimer as described in any one of claims 1-5, specifically including: The coordinate system establishment module is used to establish coordinate systems for the joints of the bucket wheel stacker-reclaimer, and to establish a lidar coordinate system with the lidar optical center as the origin; The point cloud data acquisition module is used to scan and collect field data using LiDAR; obtain the initial values ​​of the LiDAR installation parameters; and convert the collected field data into three-dimensional point cloud data in the world coordinate system based on the initial values ​​and coordinate transformation relationships. The ground point cloud data module is used to extract ground point cloud data containing the material yard ground from the three-dimensional point cloud data; the ground point cloud data is fitted using the random sampling consistent plane fitting method, and the points in the fitting plane are the points on the ground. The installation parameter calculation module is used to convert points on the ground into points in the lidar coordinate system; based on the fact that the z-axis coordinate of all points on the ground is 0 and they are all on the same plane, an objective function is designed; based on the objective function, an algorithm is designed to calculate a set of lidar installation parameters. The coordinate system establishment module is specifically used for: Establish coordinate systems for the translation, rotation, and pitch joints of the bucket wheel stacker-reclaimer, and then calculate the conversion relationship between the lidar scanning data and the 3D point cloud data based on the relative positional relationship of the coordinate systems. The objective function is: ,in The z-coordinate matrix represents the ground point cloud, where abs represents the absolute value and std represents the standard deviation.

7. An electronic device, characterized in that, It includes a memory and a processor, wherein the processor is used to execute computer management programs stored in the memory to implement the parameter calibration method of the airborne lidar of the bucket wheel stacker-reclaimer as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, It stores a computer management program, which, when executed by a processor, implements the steps of the parameter calibration method for the airborne lidar of the bucket wheel stacker-reclaimer as described in any one of claims 1-5.

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