Structural cursor calibration method, calibration system and readable storage medium

Abstract

The invention relates to the technical field of semiconductor measurement, discloses a structured light calibration method, and particularly relates to a structured light calibration method, a calibration system and a readable storage medium. The correction coefficient of the current calibration system is determined by acquiring the ratio of the standard plane phase data to the current plane phase data, the calibration model is updated according to the global distribution of the correction coefficient to obtain the target calibration model after parameter optimization, and the accuracy of subsequent calibration is realized based on the target calibration model. According to the method provided by the embodiment of the invention, the same calibration parameter optimization method can be provided, and the high-precision calibration result can be obtained only by using the plane and the calibration block under the condition of not depending on the system accuracy.

Description

Technical Field

[0001] The present application relates to the field of semiconductor measurement technology, and is a structured light calibration method, and specifically relates to a structured light calibration method, a calibration system, and a readable storage medium. Background Art

[0002] Traditional structured light calibration methods rely on high-precision calibration objects and have strict requirements on the geometric conditions of the system construction (for example, the camera and projector must be strictly parallel or perpendicular), resulting in a cumbersome and costly calibration process. In addition, direct measurement of physical parameters in the structured light system (such as the distance between the projector and the camera, the length of the light plane, etc.) is prone to introducing human errors, and it is difficult to accurately extract structured light features in complex lighting and noise environments, affecting the calibration accuracy. Moreover, in the existing technology, the calibration plate is moved many times during the calibration process and multiple sets of images are taken. The processing process is long and requires high stability of the optical platform. It also ignores the errors of the optical platform itself and the accumulated errors caused by multiple movements, resulting in inaccurate calibration results. Summary of the Invention

[0003] To address the above technical issues, the present application provides a structured light calibration method, calibration system, and readable storage medium. Initial calibration is performed using two-height planar data, and then decalibration is performed using standard phases to achieve structured light 3D reconstruction, achieving the goal of high-precision target measurement at low cost. To achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows:

[0004] In a first aspect, a structured light calibration method is provided, the method comprising: acquiring plane phase data at two different height positions, determining an observed phase distribution of a corresponding pixel position and a corresponding initial calibration model based on the plane phase data; retrieving standard plane phase data under a response height condition, and determining a standard phase distribution of the corresponding pixel position based on the plane phase data, and determining a correction coefficient of the corresponding pixel position based on the standard phase distribution and the observed phase distribution; fitting a plurality of the correction coefficients and extending them to the full field of view to obtain a target correction coefficient, and updating the initial calibration model by the target correction coefficient to obtain a target calibration model.

[0005] In some specific implementations, the initial calibration model is used to characterize the conversion relationship between the observed phase and the height value of the pixel position.

[0006] In some specific implementations, the phase distribution is a distribution result of the plane phase data corresponding to each pixel position.

[0007] In some specific implementations, the standard plane phase data is determined based on a standard height position condition.

[0008] In some specific implementations, the correction coefficient is a proportional relationship between the observed phase distribution and the standard phase distribution.

[0009] In some specific implementations, the plurality of correction coefficients are fitted based on a least squares method to obtain the fitted target correction coefficient.

[0010] In a second aspect, a structured light calibration system is provided, which is applied to a measurement system, wherein the measurement system includes a camera and a structured light projection device; the structured light calibration system includes a calibration plate and a movable stage, wherein the calibration plate is placed on the movable stage and can be moved in a vertical direction along the movable stage; and the system also includes a controller connected to the camera, the structured light projection device and the movable stage, and a processor electrically connected to the controller, wherein the controller is used to control the moving stroke of the movable stage, and the processor is used to execute any of the structured light calibration methods described above.

[0011] In some specific implementations, the processor includes a storage unit and a processing unit that communicate with each other, the storage unit is configured with standard plane phase data, and the processing unit includes the following modules: an initial calibration module, used to obtain plane phase data at two different height positions, and determine the observed phase distribution of the corresponding pixel position and the corresponding initial calibration model based on the plane phase data; a parameter acquisition module, used to call the standard plane phase data under the response height condition, and determine the standard phase distribution of the corresponding pixel position based on the plane phase data, and determine the correction coefficient of the corresponding pixel position based on the standard phase distribution and the observed phase distribution; a correction module, used to fit multiple correction coefficients and expand them to the full field of view to obtain a target correction coefficient, and update the initial calibration model by the target correction coefficient to obtain a target calibration model.

[0012] In some specific implementations, acquiring the standard plane phase data includes: placing the calibration plate on a standard gradient calibration block, acquiring a structured light image based on a camera and a structured light projection device, and obtaining the phase data by performing phase dephasing on the structured light image.

[0013] According to a third aspect, a computer-readable storage medium is provided, in which a plurality of instructions are stored. The instructions can be loaded by a processor to execute the steps of any one of the above-mentioned structural light positioning methods.

[0014] The technical solution provided in the embodiments of this application aims to construct a mapping relationship between structured light phase difference and height difference. Specifically, the correction coefficient of the current calibration system is determined by obtaining the ratio of the standard plane phase data and the current plane phase data. The calibration model is updated according to the global distribution of the correction coefficient to obtain a target calibration model with optimized parameters. The accuracy of subsequent calibration is achieved based on this target calibration model. This method can eliminate errors caused by inaccurate hardware equipment in the existing technology in a low-cost way and improve the calibration accuracy of the calibration model. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0016] The methods, systems, and / or programs in the accompanying drawings will be further described according to exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These exemplary embodiments are non-limiting exemplary embodiments, wherein example numerals represent similar structures in the various views of the drawings.

[0017] Figure 1 This is a schematic diagram of the structure of the structural cursor positioning system provided in an embodiment of the present application.

[0018] Figure 2 It is a flow chart of the structural cursor positioning method provided in an embodiment of the present application.

[0019] Figure 3 1 is a schematic diagram of the processor structure provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to better understand the above technical solution, the technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0021] In the following detailed description, numerous specific details are set forth by way of example in order to provide a thorough understanding of the relevant teachings. However, it will be apparent to one skilled in the art that the present application can be practiced without these details. In other instances, well-known methods, procedures, systems, compositions, and / or circuits have been described at a relatively high level, without detail, to avoid unnecessarily obscuring aspects of the present application.

[0022] Flowcharts are used in this application to illustrate the execution processes performed by the system according to the embodiments of the present application. It should be clearly understood that the execution processes of the flowcharts may not be executed in sequence. Instead, these execution processes may be executed in reverse order or simultaneously. In addition, at least one additional execution process may be added to the flowchart. One or more execution processes may be deleted from the flowchart.

[0023] Before further explaining the embodiments of the present invention in detail, the nouns and terms involved in the embodiments of the present invention are explained. The nouns and terms involved in the embodiments of the present invention are subject to the following interpretations.

[0024] (1) In response to, it is used to indicate the conditions or states on which the executed operations depend. When the dependent conditions or states are met, one or more operations executed may be in real time or with a set delay. Unless otherwise specified, there is no restriction on the order in which the multiple operations executed are executed.

[0025] (2) Based on, used to indicate the conditions or states on which the executed operations depend. When the dependent conditions or states are met, one or more operations executed may be in real time or with a set delay. Unless otherwise specified, there is no restriction on the order in which the multiple operations executed are executed.

[0026] Structured light gauging is a technology that achieves precise 3D measurement by determining the spatial relationships and parameters of components in a structured light system (typically consisting of a projector and a camera). Its core purpose is to provide an accurate geometric foundation for 3D reconstruction, ensuring the reliability of the measurement data.

[0027] In existing technologies, structured light calibration methods often employ a self-calibration method based on scene constraints. Phase differences at different depths are acquired by moving a calibration plane. Constraint equations are constructed using epipolar geometry and phase-depth mapping. Polynomial parameters are fitted to multiple sets of phase difference data, ultimately fitting the relationship between phase and depth. Acquiring phase differences at different depths typically involves placing a calibration plate on a movable platform. The platform's vertical movement allows the camera to capture structured light images at different heights. These images are then dephased to construct a relationship between phase and height.

[0028] This method avoids the complicated operations of traditional methods and is suitable for online measurement. However, it is worth noting that in order to obtain an accurate calibration relationship in this calibration method, the movement accuracy of the subject that needs to be moved is required to be high and the flatness of the surface of the subject is also required to be high. However, the applicant found in the actual operation process that in order to achieve the above requirements, high-precision control and high-precision mobile stages are required. Obviously, the cost of implementing this in the actual calibration scenario is high, and corresponding high-precision mobile stages need to be configured for multiple systems to be calibrated. In addition, for mobile stages that are used for a long time, errors will occur in the mobile stages due to repeated use, and the accumulation of errors will lead to inaccurate final calibration results.

[0029] In this embodiment, in order to solve the above technical problems, the embodiment of the present application provides a structured light calibration method and a structured light calibration system, and this system is applied to a measurement system or a structured light system. Among them, the measurement system or the structured light system at least includes a camera and a structured light projection device; the structured light projection device is used to project structured light, and the camera is used to capture the structured light image under the current field of view. The structured light calibration system is constructed based on the measurement system or the structured light system, and also includes a mobile stage set within the field of view of the camera and a calibration plate placed on the mobile stage; this system can obtain structured light images at different heights by projecting structured light onto the calibration plate and obtaining the structured light image within the field of view through the camera, and by moving the mobile stage along the height direction.

[0030] The above structure is no different from that in the prior art. It also collects structured light images at different heights by adjusting the height of the mobile stage, and performs phase decoding on the structured light images to determine the phase data and phase difference corresponding to the images at different heights, and establishes a mapping relationship between phase and height based on the phase data and height difference.

[0031] However, it's worth noting that these systems can cause inaccurate calibration due to errors in the movement and flatness of the mobile stage, and are highly dependent on the travel control and mechanical implementation of the mobile stage. Generally, to reduce these errors, a high-precision mobile stage or high-precision calibration block can be used. By selecting higher-precision hardware, the likelihood of errors is reduced and the accuracy of the calibration results is increased.

[0032] However, it is worth noting that this approach will increase the calibration cost. Each calibration device needs to be equipped with a corresponding high-precision mobile stage or high-precision calibration block. Obviously, this solution will incur a large cost.

[0033] Therefore, in this embodiment, in order to achieve high-precision calibration while controlling costs, a controller and a server electrically connected to the controller are configured in the above-mentioned system. The controller is used to control the movement of the mobile stage, and the server is configured with a structured light calibration method based on cross-ratio invariance and invariant posture calibration. This algorithm reduces the dependence of traditional calibration on external environments such as calibration plate accuracy and multi-angle shooting, improves robustness and efficiency, and reduces calibration costs in multi-device situations. This system can eliminate the differences caused by hardware equipment in existing calibration systems, and does not rely on high-precision control of the mobile stage based on the commonly used mobile stage in the existing technology, and has no other working requirements for the mobile stage.

[0034] In another embodiment, see Figure 1 In this embodiment, a structured cursor positioning method is also provided. The method is configured in a server and includes the following steps:

[0035] Step S11: Acquire plane phase data at two different height positions, and determine the observed phase distribution of the corresponding pixel position and the corresponding initial calibration model based on the plane phase data.

[0036] In this embodiment, a controller controls the vertical movement of a mobile stage to capture structured light images at at least two height positions during the movement. The two height positions can be the initial position and the final movement and stop positions, or can include the initial position and a height position during the movement. A first structured light image and a second structured light image are acquired for each of the two height positions, and the two structured light images are phase-decoded to obtain first phase data and second phase data, respectively.

[0037] The first phase data corresponds to the first structured light image and the first height position, and the second phase data corresponds to the second structured light image and the second height position. A height difference is determined based on the first height position and the second height position, and a phase difference can be determined based on the first phase data and the second phase data. A mapping relationship between the height difference and the phase difference after determination can be established, and this relationship serves as the initial positioning model described in this embodiment.

[0038] It is worth noting that the first phase data and the second phase data in this embodiment refer to the planar phase data obtained by obtaining the phase data corresponding to each pixel position and then smoothly distributing the entire field of view. Among them, the initial positioning model characterizes the mapping relationship between the phase and height value corresponding to each pixel position. This initial positioning model is expressed based on the following formula: z1 = a*θ + b. From the above formula, it can be seen that this function describes the linear relationship between a parameter in the plane equation of the line structured light and the rotation angle θ, where z1 represents the pixel coordinate, and a and b are the parameters to be calibrated.

[0039] In another possible implementation method, in order to ensure the accuracy of the relationship establishment, after obtaining the phase data at two heights, the phase data needs to be filtered to remove abnormal noise points. Among them, for the filtering process in this embodiment, any one of frequency domain filtering, time domain filtering and zero phase filtering can be used. For frequency domain filtering, the phase data is converted to the frequency domain through Fourier transform, and the filtering process is realized by inverse transforming the time domain through the filter in the frequency; for time domain filtering, the phase data is smoothed and the phase changes are dynamically tracked based on the Kalman filter to eliminate the abnormal phase data; for zero phase filtering, bidirectional filtering is used to eliminate phase delay. Any of the above filtering methods can be implemented, and the filtering method in the prior art can also be used, which will not be described in detail in this embodiment.

[0040] Step S12. Retrieve standard plane phase data under response height conditions, determine a standard phase distribution corresponding to a pixel position based on the plane phase data, and determine a correction coefficient corresponding to the pixel position based on the standard phase distribution and the observed phase distribution.

[0041] In this embodiment, the response height refers to the phase difference between the two height positions corresponding to step S11. The response height is configured in a memory, and the standard plane phase data corresponding to the corresponding height in the memory database is retrieved through the height difference in step S11.

[0042] In another embodiment, the height difference in step S11 and step S12 can also be controlled based on the response height stored in the database in the memory. That is, the response height stored in the database in the storage area is first determined and the controller controls the movable stage to perform height control movement, thereby obtaining the plane data at two different height positions in step S11.

[0043] Among them, it is preferred to control the travel of the mobile stage based on the response height. Based on this, the acquisition of the standard plane phase data in this embodiment can be determined based on a simulation model, where the simulation model is suitable for determining the response height and the corresponding standard plane phase data based on two different height positions; it can also be determined based on a high-precision step block, where the high-precision step block is suitable for first determining the response height and then controlling the mobile stage to perform actual height adjustment based on the response height. In this embodiment, it is preferred to use a high-precision step block to determine the standard plane phase data, and then control the plane phase data at two different height positions based on the response height.

[0044] Specifically, the phase data for the standard plane in this embodiment is acquired by using the same camera, projector, and calibration plate as used in the structured light calibration system. The calibration plate is placed on a high-precision step block. Structured light is projected onto the high-precision step block and structured light images are captured at different heights on the step block. The structured light images are then filtered and dephased using the same method as in step S11 to obtain data about the standard plane.

[0045] A mapping relationship is constructed based on the height difference between the standard plane data and the high-precision step blocks, thereby obtaining a mapping relationship between the height and phase data corresponding to each pixel position, namely, a standard phase distribution.

[0046] The initial calibration model obtained by the correction step S11 is used for this standard phase distribution, that is, the mapping relationship obtained in the calibration system is corrected by the mapping relationship determined by the high-precision position difference, which is expressed based on the following formula: z2=z1*k, where k is the correction coefficient.

[0047] Step S13: Fitting a plurality of the correction coefficients and extending them to the full field of view to obtain target correction coefficients, and updating the initial calibration model with the target correction coefficients to obtain a target calibration model.

[0048] Moreover, the planes of the high-precision step blocks and the calibration plates in the calibration system are all rigidly changing, so it can be seen that the k-value distribution is also a plane gradient distribution. In this embodiment, the correction coefficients corresponding to each of the above pixels can be fitted to obtain a more complete correction coefficient. Among them, the fitting method is implemented in this embodiment using the least squares method, and a correction coefficient distribution diagram is obtained after fitting multiple correction coefficients. The fitting is expressed based on the following formula: k = p1u + p2v + p3; wherein p1, p2 and p3 are the plane equation coefficients, and u and v are the pixel positions.

[0049] In this embodiment, the initial calibration model is corrected and updated based on the obtained correction coefficient distribution result to obtain a new calibration model for the entire image. This calibration model is the target calibration model, which is used to calibrate the structured light. This model is expressed based on the following formula: z2=z1*k=(a*θ+b)*k=(a*θ+b)*(p1u+p2v+p3).

[0050] As can be seen above, the method provided in this embodiment aims to determine the calibration model in the current calibration system, thereby eliminating inaccurate model acquisition caused by the motion control of the mobile stage and surface unevenness. Calibration is performed using the target calibration model obtained through the above process. This can be achieved using existing calibration processes and will not be further described in this embodiment.

[0051] In summary, the present invention provides a structured light calibration method for the purpose of establishing a mapping relationship between structured light phase difference and height difference. Specifically, the calibration coefficient of the current calibration system is determined by obtaining the ratio of the standard plane phase data to the current plane phase data. The calibration model is updated based on the global distribution of the correction coefficient to obtain a target calibration model with optimized parameters. The accuracy of subsequent calibration is achieved based on this target calibration model. This method can eliminate errors caused by inaccurate hardware equipment in the prior art at a low cost and improve the calibration accuracy of the calibration model.

[0052] In another embodiment, the above method is configured in a server, and the structure of the server can be found in Figure 2 As shown, the server may include components such as a processor 201 with one or more processing cores, a memory 202 with one or more computer-readable storage media, a power supply 203, an input module 204, and a communication module 205. The memory is used to obtain the captured image and the control parameters generated by the controller; the processor is used to retrieve data from the memory and process the data to obtain a processing result. Furthermore, the processor also communicates with the controller to issue control instructions to the controller for execution. The processing result in this embodiment refers to the calibration result, that is, the acquisition of the target calibration model.

[0053] Among them, those skilled in the art can understand that Figure 2 The server structure shown in the figure does not constitute a limitation on the server, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0054] Processor 201 is the server's processing center, connecting various components of the server using various interfaces and circuits. By running or executing software programs and / or modules stored in memory 202 and accessing data stored in memory 202, it executes various server functions, processes data, and issues control instructions to the controller. In some embodiments, processor 201 may include one or more processing cores. In some embodiments, processor 201 may integrate an application processor and a modem processor. The application processor primarily handles the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 201.

[0055] In one embodiment, the server further includes a power supply 203 for supplying power to various components. In some embodiments, the power supply 203 can be logically connected to the processor 201 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The power supply 203 can also include any components, such as one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, and a power status indicator.

[0056] In one embodiment, the server may further include an input module 204, which may be configured to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0057] In one embodiment, the server may further include a communication module 205. In some embodiments, the communication module 205 may include a wireless module. The server may use the wireless module of the communication module 205 to perform short-range wireless transmission, thereby providing users with wireless broadband Internet access. For example, the communication module 205 may be used to help users send and receive emails, browse web pages, and access streaming media.

[0058] In another embodiment, see Figure 3 The processor 201 in this embodiment includes the following modules:

[0059] The initial calibration module 2011 is used to obtain two plane phase data at different height positions, and determine the observed phase distribution of the corresponding pixel position and the corresponding initial calibration model based on the plane phase data;

[0060] a parameter acquisition module 2022 for retrieving standard plane phase data under response height conditions, determining a standard phase distribution corresponding to a pixel position based on the plane phase data, and determining a correction coefficient corresponding to the pixel position based on the standard phase distribution and the observed phase distribution;

[0061] The correction module 2033 is used to fit the multiple correction coefficients and expand them to the full field of view to obtain target correction coefficients, and update the initial calibration model with the target correction coefficients to obtain a target calibration model.

[0062] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0063] To this end, an embodiment of the present application provides a computer-readable storage medium storing a plurality of instructions that can be loaded by a processor to execute the steps of any of the calibration relationship determination methods and / or adjustment methods provided in the embodiments of the present application. For example, the instructions can execute the following steps:

[0064] Acquire plane phase data at two different height positions, and determine the observed phase distribution of the corresponding pixel position and the corresponding initial calibration model based on the plane phase data;

[0065] Retrieving standard plane phase data under response height conditions, determining a standard phase distribution corresponding to a pixel position based on the plane phase data, and determining a correction coefficient corresponding to the pixel position based on the standard phase distribution and the observed phase distribution;

[0066] A plurality of the correction coefficients are fitted and expanded to the full field of view to obtain a target correction coefficient, and the initial calibration model is updated by the target correction coefficient to obtain a target calibration model.

[0067] The storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0068] According to one aspect of the present application, a computer program product or computer program is provided, comprising a computer program / instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer program / instructions from the computer-readable storage medium and executes the computer program / instructions, causing the electronic device to perform the methods provided in various optional implementations of the chip detection aspects provided in the above-described embodiments.

[0069] Since the instructions stored in the storage medium can execute the steps of any calibration relationship determination method or / and the adjustment method between multiple devices provided in the embodiments of the present application, the beneficial effects that can be achieved by any calibration relationship determination method or / and the adjustment method between multiple devices provided in the embodiments of the present application can be achieved. Please see the previous embodiments for details and will not be repeated here.

[0070] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0071] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0072] The above is a detailed introduction to a structured light positioning method, storage medium and program product provided in the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for locating a structured light, characterized in that: The method comprises: Acquire plane phase data at two different height positions, and determine the observed phase distribution of the corresponding pixel position and the corresponding initial calibration model based on the plane phase data; Retrieving standard plane phase data under response height conditions, determining a standard phase distribution corresponding to a pixel position based on the standard plane phase data, and determining a correction coefficient corresponding to the pixel position based on the standard phase distribution and the observed phase distribution; A plurality of the correction coefficients are fitted and expanded to the full field of view to obtain a target correction coefficient, and the initial calibration model is updated by the target correction coefficient to obtain a target calibration model.

2. The structured light positioning method according to claim 1, characterized in that: The initial calibration model is used to characterize the conversion relationship between the observation phase and the height value of the pixel position.

3. The structured light positioning method according to claim 1, wherein: The phase distribution is the distribution result of the plane phase data corresponding to each pixel position.

4. The structured light locating method according to claim 1, wherein: The standard plane phase data is determined based on a standard height position condition.

5. The structured light positioning method according to claim 4, characterized in that: The correction coefficient is the proportional relationship between the observed phase distribution and the standard phase distribution.

6. The structured light positioning method according to claim 5, characterized in that: The plurality of correction coefficients are fitted based on the least square method to obtain the fitted target correction coefficient.

7. A structured light positioning system, applied to a measurement system, wherein the measurement system comprises a camera and a structured light projection device; characterized in that: The structured light calibration system includes a calibration plate and a movable platform, wherein the calibration plate is placed on the movable platform and can be moved in a vertical direction along the movable platform; and further includes a controller connected to the camera, the structured light projection device and the movable platform, and a server electrically connected to the controller, wherein the controller is used to control the moving stroke of the movable platform, and the server is used to execute the structured light calibration method described in any one of claims 1 to 6.

8. The structured light positioning system according to claim 7, characterized in that: The server includes a memory and a processor that communicate with each other, wherein the memory is configured with standard plane phase data, and the processor includes the following modules: An initial calibration module is used to obtain plane phase data at two different height positions, and determine the observed phase distribution of the corresponding pixel position and the corresponding initial calibration model based on the plane phase data; a parameter acquisition module, configured to retrieve standard plane phase data under response height conditions, determine a standard phase distribution at a corresponding pixel position based on the plane phase data, and determine a correction coefficient at the corresponding pixel position based on the standard phase distribution and the observed phase distribution; The correction module is used to fit the multiple correction coefficients and expand them to the full field of view to obtain target correction coefficients, and to update the initial calibration model using the target correction coefficients to obtain a target calibration model.

9. The structured light positioning system according to claim 8, characterized in that: The standard plane phase data is previously acquired data, and the acquisition method includes: placing the calibration plate on a standard gradient calibration block, acquiring a structured light image based on a camera and a structured light projection device, and obtaining the data by performing phase de-phase processing on the structured light image.

10. A computer-readable storage medium storing a plurality of instructions, wherein the instructions can be loaded by a processor to execute the steps of the structured light positioning method according to any one of claims 1 to 6.

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