A wide-range high-precision multi-structured light sensor calibration method and system

Abstract

The application discloses a wide-range high-precision multi-structure light sensor calibration method and system, and the method comprises the following steps: completing the combined installation of an optical platform; controlling a guide rail to move away from the equipment from an initial distance, and after completing the movement according to a preset step length, sequentially collecting data by using a structure light sensor, and recording the grating ruler position of a calibration block until all the data are collected after moving to the farthest distance; recording the X coordinate corresponding to each circle center on the calibration block, and the coordinate of the guide rail movement is recorded as the Y coordinate; identifying all the circle centers on the 2D image at each position and obtaining the coordinates of the circle centers in the camera coordinate system, combining the world coordinates on the calibration block, calculating the world coordinates corresponding to each 3D coordinate output by the camera by interpolation, and forming a calibration record table; and completing the joint calibration of the multi-sensor.

Description

Technical Field

[0001] This invention belongs to the field of structured light sensor calibration technology, and more specifically, relates to a wide-range, high-precision multi-structured light sensor calibration method and system. Background Technology

[0002] In cross-sectional contour data acquisition scenarios in fields such as rail engineering and industrial inspection, the measurement range of a single structured light sensor is limited by physical principles, making it difficult to cover long-distance monitoring needs. When facing scenarios such as 3D modeling of large components, the insufficient measurement range of a single sensor makes multi-sensor array combinations an inevitable choice. However, the core challenge of multi-sensor collaborative work lies in the issue of cross-device coordinate systems—if the measurement data from different sensors cannot be mapped to the same world coordinate system, the contour data collected by each sensor will form discrete spatial point clouds, leading to serious errors such as discontinuity and misalignment in the final 3D modeling.

[0003] Existing technologies primarily utilize data from overlapping sensor regions for coordinate transformation calibration. Taking dual-sensor calibration as an example, coordinate transformation relationships can be established by matching feature points in the overlapping areas. However, this approach has significant drawbacks: as the number of sensors increases, traditional methods require a chain-like calibration strategy. This involves calibrating the first two sensors first, then using one as an intermediary for subsequent calibrations. This successive transformation mechanism leads to a cumulative effect of systematic errors in each calibration. In practical applications, the errors generated by multi-sensor chain calibration are significantly amplified with the increase in the number of sensors, severely exceeding the accuracy requirements of high-precision measurements.

[0004] Furthermore, existing calibration schemes heavily rely on high-precision calibration devices. Traditional calibration blocks typically employ simple geometric structures, and their manufacturing accuracy directly impacts coordinate mapping accuracy. In scenarios with stringent measurement accuracy requirements, high-precision calibration blocks and complex image recognition methods are necessary to meet high-precision calibration needs. This not only increases calibration costs but also makes deployment difficult in field operations.

[0005] More importantly, existing technologies cannot resolve the contradiction between "range expansion and accuracy maintenance." When range expansion is required, traditional solutions necessitate increasing the number of sensors and extending the chain calibration chain. The resulting cumulative error significantly reduces the accuracy of long-distance measurements. This accuracy degradation due to the increased number of sensors has become a core technological barrier restricting the application of multi-structured optical sensors in wide-range scenarios. This invention urgently aims to overcome the error accumulation bottleneck of existing chain calibration and establish a novel calibration system that is independent of the number of sensors and combines range expansion with high accuracy. Summary of the Invention

[0006] This invention aims to solve the problems in existing multi-structured optical sensor calibration, such as error accumulation due to the increase in the number of sensors, significant impact on the accuracy of the calibration device, and the contradiction between range expansion and accuracy maintenance. By designing a specific calibration block and utilizing grating ruler feedback for position, a direct mapping from multi-sensor coordinates to the world coordinate system is achieved. This establishes a method for high-precision calibration with a wide range that is independent of the number of sensors, meeting the high-precision measurement requirements for track profile contours and other applications.

[0007] To address the aforementioned deficiencies or improvement needs of existing technologies, as a first aspect of this invention, the present invention provides a wide-range, high-precision multi-structure optical sensor calibration method, comprising:

[0008] S1. Complete the combined installation of the optical platform, including multiple line structured light scanners. The laser lines emitted by the multiple line structured light scanners are adjusted to the same plane, and the laser lines are projected onto the calibration block with a distance difference of <0.3mm between them.

[0009] S2. Design a data acquisition program to control the guide rail to move away from the device from the initial distance. After each movement according to the preset step size, data is collected sequentially through the structured light sensor, and the position of the grating ruler of the calibration block is recorded until the farthest distance is reached and all data is collected.

[0010] S3. Record the corresponding center of each circle on the calibration block. The coordinates of the guide rail movement are recorded by the grating ruler. Coordinates; Identify all circle centers on the 2D image at each location and determine their coordinates in the camera image coordinate system; Obtain the world coordinates corresponding to the structured light line at each moving position through interpolation; Continue to obtain the world coordinates corresponding to each pixel between two moving positions through interpolation; Record all data to form a calibration record table, and complete the calibration;

[0011] S4. The camera coordinates of each structured light sensor are converted to the world coordinate system by looking up the corresponding calibration record table in S3, and all are in the same world coordinate system to complete the calibration.

[0012] Furthermore, the specific assembly and installation of the optical platform in S1 is as follows:

[0013] Mount the guide rail onto the optical platform, and simultaneously install an absolute grating ruler on the guide rail to measure the position of the guide rail movement; mount the circular pattern calibration block onto the lifting platform, which is then mounted on the guide rail; install multiple line structured light scanners into the device, then mount the device onto the optical platform, and adjust the emitting ends of all line structured light scanners to the center of the circular pattern on the calibration block.

[0014] Furthermore, the specific method for adjusting the laser lines emitted by the multiple line structured light scanners to the same plane is as follows:

[0015] Move the guide rail to the near-range boundary of the structured light laser, turn on the adjustment line structured light, check the position of all structured lights on the calibration block, adjust all line structured lights to the same line and parallel to the edge of the guide rail;

[0016] Move the guide rail to the far-range boundary of the structured light laser, turn on the adjustable structured light, check the position of all structured lights on the calibration block, adjust all structured lights to the same line and parallel to the edge of the guide rail; repeat the above two steps until the near-range boundary and the far-range boundary are on the same line and the same distance from the edge of the guide rail, and the laser lines are projected on the calibration block with a distance difference of <0.3mm between them;

[0017] Adjust the height of the lifting platform so that the emitting ends of all line structured lights are aligned with the center of the circular pattern on the calibration block.

[0018] Furthermore, the data acquired in S2 includes: camera 3D data and camera 2D grayscale image data; the camera 3D data is... ,in For the column coordinates of the image, These are the sub-pixel coordinates of the image rows.

[0019] Furthermore, the preset step size in S2 is between 0.2mm and 0.5mm.

[0020] Furthermore, the specific method for determining its coordinates in the camera image coordinate system in step S3 is as follows:

[0021] The coordinates of the center of the circle in the camera coordinate system are: ;

[0022] Indicates the center number, where The coordinates of the center of the circle in the 2D graph , The corresponding subpixel y-coordinate of the index point in the 3D data at a subdivision of 64.

[0023] Furthermore, the specific method for obtaining the world coordinates corresponding to the structured light line at each moving position through interpolation in S3 is as follows:

[0024] The coordinates of the corresponding calibration block are ,in For the calibration block The world coordinates of the center of a circle; ; The Y coordinate recorded by the grating ruler; Indicates the diameter of the circle on the calibration block;

[0025] ,

[0026] ,

[0027] in, Center and Any column of pixels in the camera image; For the guide rail Next move, For the first The output value of the absolute grating ruler during the next movement. For the first The coordinates of the center of the circle in the camera coordinate system For the first The x-coordinate of the center of the circle in the camera coordinate system ; The structured light line corresponding to the r-th movement position The x-coordinate of the world coordinates of each pixel. The structured light line corresponding to the r-th movement position The ordinate of the world coordinates of each pixel.

[0028] Furthermore, the specific method for obtaining the world coordinates of each pixel between two moving positions of the structured light bright line through interpolation in S3 is as follows:

[0029] In practical applications, structured light bright lines must simultaneously exist within the range between two movements. Further interpolation methods, combined with camera 3D data, are then used to... Image coordinates of each moving pixel The coordinates of each pixel in the world coordinate system are calculated using the following formula:

[0030] ,

[0031] ,

[0032] in, For the first The image of the c-th pixel after the second movement coordinate, For the first The image of the c-th pixel after the second movement coordinate;

[0033] For the first The world coordinates of the c-th pixel corresponding to the structured light line that moved next time. coordinate; For the first The world coordinates of the c-th pixel corresponding to the structured light line that moved next time. , For the first The world coordinate x of the c-th pixel corresponding to the structured light line that moves in this step. For the first The world coordinate x corresponding to the c-th pixel point after the next movement;

[0034] For the application process, the x-coordinate of the pixel in the image. The y-coordinate of the pixel in the image during application;

[0035] For the world coordinates of pixels during application. , For the world coordinates of pixels during application. ; meet regulation , .

[0036] As a second aspect of the present invention, a wide-range, high-precision multi-structure optical sensor calibration system is also provided, comprising:

[0037] The optical platform integrates a sensor coplanar calibration unit to complete the combined installation of the optical platform, including multiple line structured light scanners. The laser lines emitted by the multiple line structured light scanners are adjusted to the same plane, and the laser lines are projected onto the calibration block with a distance difference of <0.3mm between them.

[0038] An automated multi-position synchronous data acquisition unit is used to control the guide rail to move away from the device from an initial distance. After each movement is completed according to the preset step size, data is collected sequentially through a structured light sensor, and the position of the grating ruler of the calibration block is recorded, until all data is collected at the farthest distance.

[0039] The multi-coordinate system and calibration table generation unit are used to record the coordinates of each circle center on the calibration block. The coordinates of the guide rail movement are recorded by the grating ruler. Coordinates; Identify all circle centers on the 2D image at each location and determine their coordinates in the camera image coordinate system; Obtain the world coordinates corresponding to the structured light line at each moving position through interpolation; Continue to obtain the world coordinates corresponding to each pixel between two moving positions through interpolation; Record all data to form a calibration record table, and complete the calibration;

[0040] The multi-sensor joint calibration unit converts the camera coordinates of each structured light sensor into the world coordinate system by looking up the corresponding calibration record table in S3, and all of them are in the same world coordinate system to complete the calibration.

[0041] As a third aspect of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, wherein the computer program is executed by a processor in any step of the above-described wide-range, high-precision multi-structure optical sensor calibration method.

[0042] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects:

[0043] 1. The wide-range, high-precision multi-structure optical sensor calibration method of the present invention constructs a three-dimensional spatial reference system based on an optical calibration block and a guide rail. It utilizes pre-fabricated regular geometric patterns on the calibration block as feature points, combined with precise displacement control of the guide rail, to establish a high-precision reference grid in the world coordinate system. This method records the guide rail position in real time using a grating ruler, using it as the Y-coordinate reference in the world coordinate system. Simultaneously, the X-coordinates of the centers on the calibration block are arranged according to a preset rule, forming a two-dimensional coordinate array. This design enables the system to provide uniformly distributed three-dimensional reference points over a wide measurement range, providing a reliable foundation for subsequent coordinate mapping and effectively solving the problem of accuracy degradation in large-size measurement scenarios using traditional calibration methods.

[0044] 2. The wide-range, high-precision multi-structured optical sensor calibration method of this invention establishes a coordinate matching record storage and transformation mechanism to associate the 3D coordinates of each sensor with their corresponding world coordinates. Each sensor accesses its corresponding matching record table and uses nearest-neighbor interpolation or transformation matrix calculations to transform its output 3D coordinates to a unified world coordinate system. This mechanism achieves spatial alignment of multi-sensor data, enabling sensors at different locations and from different perspectives to work collaboratively within the same coordinate framework. Through distributed storage and parallel computing optimization, this method can efficiently process large amounts of calibration data, ensuring that the system maintains high-precision coordinate transformation performance over a wide measurement range, providing reliable technical support for multi-sensor fusion measurement. Attached Figure Description

[0045] Figure 1 This is a flowchart of the wide-range, high-precision multi-structure optical sensor calibration method according to an embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of the calibration block according to an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of an example of an optical platform and device according to an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram of an example model of the optical platform and device according to an embodiment of the present invention;

[0049] Figure 5This is a schematic diagram showing the relationship between two adjacent center points in an embodiment of the present invention;

[0050] Figure 6 This is a schematic diagram of the bright lines of the calibration block structure in an embodiment of the present invention;

[0051] Figure 7 This is a system unit diagram of an embodiment of the present invention. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0053] Example 1

[0054] Please refer to Figure 1 This embodiment 1 provides a calibration method for a wide-range, high-precision multi-structure optical sensor, including:

[0055] S1. Complete the combined installation of the optical platform, including multiple line structured light scanners. The laser lines emitted by the multiple line structured light scanners are adjusted to the same plane, and the laser lines are projected onto the calibration block with a distance difference of <0.3mm between them.

[0056] S2. Design a data acquisition program to control the guide rail to move away from the device from the initial distance. After each movement according to the preset step size, data is collected sequentially through the structured light sensor, and the position of the grating ruler of the calibration block is recorded until the farthest distance is reached and all data is collected.

[0057] S3. Record the corresponding center of each circle on the calibration block. The coordinates of the guide rail movement are recorded by the grating ruler. Coordinates; Identify all circle centers on the 2D image at each location and determine their coordinates in the camera image coordinate system; Obtain the world coordinates corresponding to the structured light line at each moving position through interpolation; Continue to obtain the world coordinates corresponding to each pixel between two moving positions through interpolation; Record all data to form a calibration record table, and complete the calibration;

[0058] S4. The camera coordinates of each structured light sensor are converted to the world coordinate system by looking up the corresponding calibration record table in S3, and all are in the same world coordinate system to complete the calibration.

[0059] This embodiment 1 further elaborates on the above steps.

[0060] (1) Optical platform integration and sensor coplanar calibration

[0061] Please refer to Figure 3 as well as Figure 4 Install the guide rail onto the optical platform, and simultaneously install an absolute grating ruler on the guide rail to measure the position of the guide rail movement; install the circular pattern calibration block onto the lifting platform, and the lifting platform is installed on the guide rail; install multiple line structured light scanners into the device, then install the device onto the optical platform, and adjust the emitting ends of all line structured light scanners to the center of the circular pattern on the calibration block.

[0062] Move the guide rail to the near-range boundary of the structured light laser, turn on the adjustment line structured light, check the position of all structured lights on the calibration block, adjust all line structured lights to the same line and parallel to the edge of the guide rail;

[0063] Move the guide rail to the far-range boundary of the structured light laser, turn on the adjustable structured light, check the position of all structured lights on the calibration block, adjust all structured lights to be on the same line and parallel to the edge of the guide rail; repeat the above two steps until the near-range boundary and the far-range boundary are on the same line and at the same distance from the edge of the guide rail, and the laser lines are projected onto the calibration block with a distance difference of <0.3mm between them.

[0064] Adjust the height of the lifting platform so that the emitting ends of all line structured lights are aligned with the center of the circular pattern on the calibration block.

[0065] In a specific embodiment, the device needs to scan data within a range of 250mm-500mm from the device. The closer distance is 250mm from the device casing, and the farther distance is 500mm from the device casing.

[0066] Use a torque wrench to tighten the screws at each connection point of the equipment in a diagonal sequence to avoid stress deformation; start the pre-detection program, drive the guide rail to move back and forth, and simultaneously monitor the position offset of the laser lines of each sensor to ensure the stability of the calibration status.

[0067] (2) Automated multi-location synchronous data acquisition

[0068] After starting the data acquisition program, the initial distance, step size, and target distance of the guide rail movement are set in the parameter setting interface. The initial distance corresponds to the closest position within the device's measurement range. The step size can be adjusted within a reasonable range as needed. In a preferred embodiment, the preset step size is between 0.2mm and 0.5mm. Simultaneously, the driving protocols for each structured light sensor are loaded, establishing a real-time communication link between the sensors and the guide rail motion controller, ensuring smooth command transmission and data interaction between components.

[0069] The drive rail moves from the initial distance towards the greater distance. When it first reaches the near-distance boundary, a closed-loop verification is performed using position data fed back by an absolute linear encoder. If there is a deviation between the actual displacement and the commanded value, a corresponding compensation mechanism is activated until the deviation is within the allowable range. Afterward, the rail moves sequentially in preset steps. After each movement, the position locking mechanism of the linear encoder is triggered, recording the current Y-axis coordinate to form a precise position reference.

[0070] After each guide rail positioning is completed, the structured light sensors are activated in a pre-set sequence, causing them to sequentially acquire 3D camera data and 2D grayscale image data from the calibration block surface. The 3D camera data is... ,in These are the column coordinates of the image, in units of 1 pixel. These are sub-pixel coordinates for the image row, in units of 1 / 64 pixel; they are derived from the emission of structured light. In images captured under low exposure settings, structured light bright lines are identified, and their coordinates are calculated. .

[0071] The system continuously executes a cycle of "guide rail movement - position calibration - sensor acquisition" until the guide rail reaches the preset long-distance position, thus achieving full-range data coverage from near to far. During acquisition, data integrity is monitored in real time: if a sensor experiences data loss or an anomaly, the location is automatically marked, and a re-acquisition mechanism is triggered; simultaneously, the overlap of point clouds at adjacent locations is calculated to ensure the accuracy continuity at data junctions. Furthermore, after completing a certain proportion of the acquisition task, 3D data, 2D images, and grating ruler position data are packaged and stored on a dual-hard disk array to prevent data loss due to sudden failures, providing a complete and reliable raw dataset for subsequent calibration processing.

[0072] (3) Generation of multi-coordinate system and calibration table

[0073] The multi-coordinate system and calibration table generation aims to solve the problem of inconsistent spatial positions caused by different reference benchmarks in multi-source data, and to achieve accurate description, fusion and application of data within a unified framework. In multi-sensor collaborative scenarios, each sensor has an independent local coordinate system. For example, the origin and coordinate axis directions of the coordinate systems of structured light sensors and cameras are different, making it impossible to directly correlate the acquired data.

[0074] By establishing a world coordinate system as a global reference frame and determining the transformation relationship between the local coordinate system and the world coordinate system, data from different sensors can be mapped to the same spatial scale, achieving spatial alignment of multi-source data and laying the foundation for subsequent data analysis and object reconstruction. Calibration table generation is crucial for achieving coordinate unification. It relies on calibration objects with precise geometric features, comparing the known coordinates of feature points in the world coordinate system with the measured coordinates in the local coordinate system. Using matrix transformations and other methods, transformation parameters such as rotation matrices and translation vectors are solved, forming a "transformation dictionary" that records the mapping relationship between the sensor coordinate system and the world coordinate system.

[0075] This process has significant implications for practical applications. In 3D reconstruction, it ensures accurate stitching of data collected from multiple sensors, avoiding model misalignment; in industrial inspection, it guarantees the consistency and traceability of measurement results, facilitating comparative analysis of data from different batches; in systems involving moving parts, it enables precise positioning of sensor spatial locations and accurate control of motion trajectories, providing crucial support for multi-sensor data fusion, measurement accuracy assurance, and system controllability.

[0076] Please refer to Figure 2 When generating a multi-coordinate system and calibration table, the coordinate information of the calibration block and guide rail must first be processed. The calibration block has pre-made circular tangent patterns, each circle's center corresponding to a unique X-coordinate in the world coordinate system, arranged horizontally according to a predetermined rule (e.g., increasing sequentially from left to right). The guide rail's movement coordinates on the optical platform are recorded in real-time by an absolute grating ruler mounted on it; this data serves as the Y-coordinate reference in the world coordinate system.

[0077] Let the set of centers of the circles on the calibration block be... In the world coordinate system, each circle center of Coordinates satisfy a functional relationship , Starting coordinates The horizontal distance between adjacent center points is constant.

[0078] For the motion of the guide rail, let its position vector in the world coordinate system be... The displacement data output by the absolute grating ruler is ,but In the world coordinate system The axial component can be expressed as ,in Changes in real time with the movement of the guide rail and The X and Z axis components remain at 0 during this motion;

[0079] During the data processing stage, for each 2D image acquired at each guide rail movement position, image recognition methods (such as edge detection and ellipse fitting) are used to extract the pixel positions of all circle centers, thus obtaining their coordinates in the camera coordinate system. .in Indicates the center number, where The coordinates of the center of the circle in the 2D graph , The corresponding subpixel y-coordinate of the index point in the 3D data at a subdivision of 64.

[0080] Meanwhile, the world coordinates on the calibration block It can be directly obtained through pre-designed parameters and feedback data from the grating ruler, among which... Determined by the physical position of the center on the calibration block. This represents the real-time displacement of the guide rail recorded by the grating ruler. The corresponding coordinate point on the calibration block is... ,in For the calibration block The world coordinates of the center of a circle; ; The Y coordinate recorded by the grating ruler; Indicates the diameter of the circle on the calibration block. In a preferred embodiment, .

[0081] Coordinate mapping calculation is based on the interpolation principle: for any column of pixels in the camera image Using the coordinates of two adjacent circle centers in the camera coordinate system ( and The world coordinates of the corresponding coordinates are calculated using a linear interpolation model. Quantity world coordinates Quantity Then directly take the grating ruler reading of the current guide rail movement position. This interpolation process satisfies the nonlinear mapping relationship between the camera coordinate system and the world coordinate system, and the transformation accuracy can be ensured through multi-point sampling and fitting.

[0082] Please refer to Figure 5 as well as Figure 6 In a specific preferred embodiment, the method for obtaining the world coordinates corresponding to the structured light line at each moving position through interpolation is as follows:

[0083] ,

[0084] ,

[0085] in, Center and Any column of pixels in the camera image; For the guide rail Next move, For the first The output value of the absolute grating ruler during the next movement. For the first The coordinates of the center of the circle in the camera coordinate system For the first The x-coordinate of the center of the circle in the camera coordinate system ; The structured light line corresponding to the r-th movement position The x-coordinate of the world coordinates of each pixel. The structured light line corresponding to the r-th movement position The ordinate of the world coordinates of each pixel.

[0086] This calculation formula is for data processing after one movement of the guide rail. During the entire data acquisition and calibration process, the guide rail will move hundreds or thousands of times. With each movement, the bright line on the calibration block will move in the camera image, thus establishing a mapping relationship between the camera image coordinate system and the world coordinate system. The formula here calculates the transformation relationship between the camera coordinate system and the world coordinate system after one movement. The coordinate transformation relationship between two adjacent movements is then calculated using linear interpolation.

[0087] In practical applications, structured light bright lines must simultaneously exist within the range between two movements. Further interpolation methods, combined with camera 3D data, are then used to... Image coordinates of each moving pixel The coordinates of each pixel in the world coordinate system are calculated using the following formula:

[0088] ,

[0089] ,

[0090] in, For the first The image of the c-th pixel after the second movement coordinate, For the first The image of the c-th pixel after the second movement coordinate;

[0091] For the first The world coordinates of the c-th pixel corresponding to the structured light line that moved next time. coordinate; For the first The world coordinates of the c-th pixel corresponding to the structured light line that moved next time. , For the first The world coordinate x of the c-th pixel corresponding to the structured light line that moves in this step. For the first The world coordinate x corresponding to the c-th pixel point after the next movement;

[0092] For the application process, the x-coordinate of the pixel in the image. The y-coordinate of the pixel in the image during application;

[0093] For the world coordinates of pixels during application. , For the world coordinates of pixels during application. ; meet regulation , .

[0094] To verify the accuracy of coordinate transformation, a redundant point verification mechanism was introduced during the calibration process. Several redundant circle centers, not evenly spaced, on the calibration block were selected as verification points. Their world coordinates were calculated using the aforementioned mapping relationship and compared with the actual measured values. If the error exceeded a preset threshold, the parameters of the interpolation model were readjusted, or the sensor's installation position was fine-tuned. Furthermore, to improve the accuracy of long-distance coordinate transformation, a piecewise interpolation strategy was adopted: the measurement range was divided into multiple intervals based on the distance the guide rail moved, and an independent interpolation model was established for each interval to accommodate the differences in camera perspective transformation at different distances.

[0095] Finally, the correspondence between camera coordinates and world coordinates for all sampling locations is stored in a structured manner: each 3D coordinate output by each camera group is recorded in tabular form. The mapping data also includes auxiliary information such as the number of guide rail movements and grating ruler readings. Each record contains the following fields: guide rail movement sequence number, grating ruler Y-coordinate, camera number, center number, corrected coordinates in the camera coordinate system, and corresponding world coordinates. Data collection timestamps, etc. To facilitate rapid subsequent queries, the database establishes a composite index based on camera coordinates and guide rail positions. Data storage employs a dual-backup mechanism, simultaneously writing to a local solid-state drive and a remote server to ensure data security and recoverability. After the calibration record table is generated, a repeatability accuracy test is required: by repeatedly performing the calibration process, the standard deviation of the coordinate mapping at the same location is calculated. If the standard deviation meets the equipment's accuracy requirements (e.g., better than ±0.05mm), the calibration process is complete; otherwise, the hardware installation status needs to be checked or the data acquisition process needs to be re-executed.

[0096] In practical measurement applications, after the structured light sensor acquires the 3D data of the target object, the system automatically queries the calibration record table based on the camera coordinates of that point and the current measurement distance, and calculates its world coordinates through interpolation. To improve computational efficiency, the K-nearest neighbor search method is used to quickly locate adjacent calibration data points, avoiding traversing the entire table. For measurement scenarios with complex curved surfaces, triangulation methods can be combined to construct an irregular triangular network of calibration data points, and more accurate coordinate transformation can be achieved through linear or bilinear interpolation methods. The entire coordinate transformation process is implemented in parallel by a hardware acceleration unit to ensure fast response during real-time measurement.

[0097] (4) Multi-sensor joint calibration

[0098] The process of obtaining a matching record table of 3D coordinates and world coordinates for each structured light sensor using S3 to unify the coordinates of multiple sensors into the same world coordinate system requires constructing a complete technical path from aspects such as data storage, transformation logic, and system calibration. In the S3 storage architecture, the matching record table adopts a distributed structured format, indexed by the sensor ID. Each record contains sensor metadata, the mapping pair of 3D coordinates and world coordinates, and accuracy indicators. It is stored in buckets according to sensor type and a spatial hash index is established to facilitate fast retrieval.

[0099] For coordinate transformation of a single sensor, when the sensor outputs 3D point coordinates, the nearest neighbor calibration sample points are first searched in the S3 record table. The weight of each sample is calculated based on the distance, and the corresponding world coordinates are obtained through a weighted summation. If there are enough calibration samples in the record table, the transformation matrix from the sensor coordinate system to the world coordinate system, including the rotation matrix and translation vector, can be solved using the least squares method to achieve coordinate transformation.

[0100] In a preferred embodiment, a unified cross-sensor calibration benchmark is established using multi-sensor coordinates. A high-precision 3D calibration board is used, whose world coordinates have been pre-calibrated precisely, ensuring that all sensors can simultaneously observe multiple feature points on the calibration board. For data processing, global clock synchronization ensures consistent timestamps across different sensor data, and an error compensation model is established to account for environmental factors. A distributed computing framework is employed to process multi-sensor data in parallel, combining sensor data with the matching record table in S3 to achieve parallel coordinate transformation.

[0101] In a preferred embodiment, to verify the accuracy of coordinate unification, the transformed world coordinates are back-projected onto the images of each sensor to calculate the reprojection error, and the world coordinate differences are calculated by selecting points observed jointly by multiple sensors. When the system detects that the coordinate transformation error exceeds a certain range, incremental calibration is automatically triggered, new calibration data is collected and uploaded to S3, the mapping record table is updated through an online learning method, and the old and new data are merged to ensure accuracy.

[0102] Example 2

[0103] Please refer to Figure 7 This embodiment 2 provides a wide-range, high-precision multi-structure optical sensor calibration system, including:

[0104] The optical platform integrates a sensor coplanar calibration unit to complete the combined installation of the optical platform, including multiple line structured light scanners. The laser lines emitted by the multiple line structured light scanners are adjusted to the same plane, and the laser lines are projected onto the calibration block with a distance difference of <0.3mm between them.

[0105] An automated multi-position synchronous data acquisition unit is used to control the guide rail to move away from the device from an initial distance. After each movement is completed according to the preset step size, data is collected sequentially through a structured light sensor, and the position of the grating ruler of the calibration block is recorded, until all data is collected at the farthest distance.

[0106] The multi-coordinate system and calibration table generation unit are used to record the coordinates of each circle center on the calibration block. The coordinates of the guide rail movement are recorded by the grating ruler. Coordinates; Identify all circle centers on the 2D image at each location and determine their coordinates in the camera image coordinate system; Obtain the world coordinates corresponding to the structured light line at each moving position through interpolation; Continue to obtain the world coordinates corresponding to each pixel between two moving positions through interpolation; Record all data to form a calibration record table, and complete the calibration;

[0107] The multi-sensor joint calibration unit converts the camera coordinates of each structured light sensor into the world coordinate system by looking up the corresponding calibration record table in S3, and all of them are in the same world coordinate system to complete the calibration.

[0108] Example 3

[0109] This embodiment 3 also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement any step of a wide-range, high-precision multi-structure optical sensor calibration method.

[0110] The computer-readable storage medium may include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0111] For a description of the computer-readable storage medium provided in this application, please refer to the above method embodiments; further details will not be repeated here.

[0112] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A calibration method for a wide-range, high-precision multi-structure optical sensor, characterized in that, include: S1. Complete the combined installation of the optical platform, including multiple line structured light scanners. The laser lines emitted by the multiple line structured light scanners are adjusted to the same plane, and the laser lines are projected onto the calibration block with a distance difference of <0.3mm between them. S2. Design a data acquisition program to control the guide rail to move away from the device from the initial distance. After each movement according to the preset step size, data is collected sequentially through the structured light sensor, and the position of the grating ruler of the calibration block is recorded until the farthest distance is reached and all data is collected. S3. Record the corresponding center of each circle on the calibration block. The coordinates of the guide rail movement are recorded by the grating ruler. Coordinates; Identify all circle centers on the 2D image at each location and determine their coordinates in the camera image coordinate system; Obtain the world coordinates corresponding to the structured light line at each moving position through interpolation; Continue to obtain the world coordinates corresponding to each pixel between two moving positions through interpolation; Record all data to form a calibration record table, and complete the calibration; S4. The camera coordinates of each structured light sensor are converted to the world coordinate system by looking up the corresponding calibration record table in S3, and all are in the same world coordinate system, thus completing the calibration. The specific method for obtaining the world coordinates corresponding to the structured light line at each moving position through interpolation in S3 is as follows: The coordinates of the corresponding calibration block are ,in For the calibration block The world coordinates of the center of a circle; ; The Y coordinate recorded by the grating ruler; Indicates the diameter of the circle on the calibration block; ， ， in, Center and Any column of pixels in the camera image; For the guide rail Next move, For the first The output value of the absolute grating ruler during the next movement. For the first The coordinates of the center of the circle in the camera coordinate system For the first The x-coordinate of the center of the circle in the camera coordinate system ; The structured light line corresponding to the r-th movement position is the first... The x-coordinate of the world coordinates of each pixel. The structured light line corresponding to the r-th movement position is the first... The ordinate of the world coordinates of each pixel.

2. The calibration method for a wide-range, high-precision multi-structure optical sensor according to claim 1, characterized in that, The specific assembly and installation of the optical platform in S1 is as follows: Mount the guide rail onto the optical platform, and simultaneously install an absolute grating ruler on the guide rail to measure the position of the guide rail movement; mount the circular pattern calibration block onto the lifting platform, which is then mounted on the guide rail; install multiple line structured light scanners into the device, then mount the device onto the optical platform, and adjust the emitting ends of all line structured light scanners to the center of the circular pattern on the calibration block.

3. The calibration method for a wide-range, high-precision multi-structure optical sensor according to claim 1, characterized in that, The specific method for adjusting the laser lines emitted by the multiple line structured light scanners to the same plane is as follows: Move the guide rail to the near-range boundary of the structured light laser, turn on the adjustment line structured light, check the position of all structured lights on the calibration block, adjust all line structured lights to the same line and parallel to the edge of the guide rail; Move the guide rail to the far-range boundary of the structured light laser, turn on the adjustable structured light, check the position of all structured lights on the calibration block, adjust all structured lights to the same line and parallel to the edge of the guide rail; repeat the above two steps until the near-range boundary and the far-range boundary are on the same line and the same distance from the edge of the guide rail, and the laser lines are projected on the calibration block with a distance difference of <0.3mm between them; Adjust the height of the lifting platform so that the emitting ends of all line structured lights are aligned with the center of the circular pattern on the calibration block.

4. The calibration method for a wide-range, high-precision multi-structure optical sensor according to claim 1, characterized in that, The data acquired in S2 includes: camera 3D data and camera 2D grayscale image data; the camera 3D data is... ,in For the column coordinates of the image, These are the sub-pixel coordinates of the image rows.

5. The calibration method for a wide-range, high-precision multi-structure optical sensor according to claim 1, characterized in that, The preset step size in S2 is between 0.2mm and 0.5mm.

6. The calibration method for a wide-range, high-precision multi-structure optical sensor according to claim 1, characterized in that, The specific method for determining its coordinates in the camera image coordinate system in S3 is as follows: The coordinates of the center of the circle in the camera coordinate system are: ; Indicates the center number, where The coordinates of the center of the circle in the 2D graph , The corresponding subpixel y-coordinate of the index point in the 3D data at a subdivision of 64.

7. The calibration method for a wide-range, high-precision multi-structure optical sensor according to claim 1, characterized in that, The specific method for obtaining the world coordinates of each pixel between two moving positions of the structured light bright line through interpolation in S3 is as follows: In practical applications, structured light bright lines must simultaneously exist within the range between two movements. Further interpolation methods, combined with camera 3D data, are then used to... Image coordinates of each moving pixel The coordinates of each pixel in the world coordinate system are calculated using the following formula: ， ， in, For the first The image of the c-th pixel after the second movement coordinate, For the first The image of the c-th pixel after the second movement coordinate; For the first The world coordinates of the c-th pixel corresponding to the structured light line that moved next time. coordinate; For the first The world coordinates of the c-th pixel corresponding to the structured light line that moved next time. , For the first The world coordinate x of the c-th pixel corresponding to the structured light line that moves in this step. For the first The world coordinate x corresponding to the c-th pixel point after the next movement; For the application process, the x-coordinate of the pixel in the image. The y-coordinate of the pixel in the image during application; For the world coordinates of pixels during application. , For the world coordinates of pixels during application. ; meet regulation , .

8. A wide-range, high-precision multi-structure optical sensor calibration system, characterized in that, include: The optical platform integrates a sensor coplanar calibration unit to complete the combined installation of the optical platform, including multiple line structured light scanners. The laser lines emitted by the multiple line structured light scanners are adjusted to the same plane, and the laser lines are projected onto the calibration block with a distance difference of <0.3mm between them. An automated multi-position synchronous data acquisition unit is used to control the guide rail to move away from the device from an initial distance. After each movement is completed according to the preset step size, data is collected sequentially through a structured light sensor, and the position of the grating ruler of the calibration block is recorded, until all data is collected at the farthest distance. The multi-coordinate system and calibration table generation unit are used to record the coordinates of each circle center on the calibration block. The coordinates of the guide rail movement are recorded by the grating ruler. Coordinates; Identify all circle centers on the 2D image at each location and determine their coordinates in the camera image coordinate system; Obtain the world coordinates corresponding to the structured light line at each moving position through interpolation; Continue to obtain the world coordinates corresponding to each pixel between two moving positions through interpolation; Record all data to form a calibration record table, and complete the calibration; The multi-sensor joint calibration unit is used to convert the camera coordinates of each structured light sensor into the world coordinate system by looking up the corresponding calibration record table in the multi-coordinate system and calibration table generation unit. All of them are under the same world coordinate system, thus completing the calibration. The specific method for obtaining the world coordinates corresponding to the structured light line at each moving position through interpolation in the multi-coordinate system and calibration table generation unit is as follows: The coordinates of the corresponding calibration block are ,in For the calibration block The world coordinates of the center of a circle; ; The Y coordinate recorded by the grating ruler; Indicates the diameter of the circle on the calibration block; ， ， in, Center and Any column of pixels in the camera image; For the guide rail Next move, For the first The output value of the absolute grating ruler during the next movement. For the first The coordinates of the center of the circle in the camera coordinate system For the first The x-coordinate of the center of the circle in the camera coordinate system ; The structured light line corresponding to the r-th movement position is the first... The x-coordinate of the world coordinates of each pixel. The structured light line corresponding to the r-th movement position is the first... The ordinate of the world coordinates of each pixel.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program is executed by a processor according to any one of claims 1-7, which describes a wide-range, high-precision multi-structure optical sensor calibration method.

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