Parameter calibration method and device, computer storage medium and terminal

Abstract

The invention discloses a parameter calibration method and device, a computer storage medium and a terminal, and the method and device achieve the judgment of the abnormality of a real-time dynamic carrier phase difference positioning technology (RTK) positioning system through at least one group of positioning data based on the characteristic that the positioning data outputted by a visual inertial odometer (VIO) positioning system does not have output jump. When it is determined that the RTK positioning system is abnormal and is in a stable offset state, parameter calibration is carried out through positioning data of the combined positioning system, and parameter calibration of the combined positioning system in a multi-path environment is achieved.

Description

Technical Field

[0001] The present invention relates to positioning technology, and in particular to a method, device, computer storage medium and terminal for parameter calibration. Background Art

[0002] In the fields of surveying and mapping, intelligent driving, and intelligent robots, real-time dynamic differential positioning (RTK) is the most widely used high-precision satellite positioning technology. However, in non-open areas where there are insufficient satellites and where the signal multipath effect is very significant, there are also inaccurate positioning. The RTK positioning system is combined with the visual-inertial odometer (VIO) positioning system to form a combined positioning system, which can solve the problem of inaccurate positioning caused by insufficient satellites and signal multipath effects in non-open areas of the RTK positioning system. However, in order to achieve the fusion of the two positioning results of the RTK positioning system and the VIO positioning system, when the combined positioning system is initialized, it is necessary to calculate the coordinate system transformation parameters of the output positions of the two systems, including rotation angle, translation distance, and scaling factor, to achieve the coordinate system of the two positioning systems, that is, to calibrate the parameters. At present, there are two problems with the results output during the operation of the monocular VIO: 1. The scale drift problem of the monocular system; 2. The angle error caused by the gyroscope drift. These two problems cause the coordinate system transformation parameters calibrated during the initialization of the combined positioning system to differ from the actual coordinate system transformation parameters during operation, resulting in inaccurate fusion positioning results; therefore, during the working process, it is necessary to continuously calibrate the parameters of the combined positioning system, but in a multipath environment, the RTK positioning results are distorted and cannot be directly used for parameter calibration.

[0003] To improve the VIO scale drift and angle error problems, the processing methods used in related technologies are: 1. Construct a three-dimensional map before use and save it in the system's memory: implement the loop detection function based on VIO (match the image captured by the current camera in the map. If the match is successful, it means that the device has appeared at this location before. The local coordinates are directly obtained from the map to correct the position calculated by VIO); when VIO is running, the loop detection function is used to match the position in the complete map saved in the memory, obtain the current position coordinates, and calibrate the scale according to the obtained current position coordinates to achieve the goal of significantly reducing scale drift. 2. Use deep learning technology: train the deep learning model, and VIO inputs the image into the deep learning model for calculation during operation. 3. Use the sliding window method to continuously collect data: Use the data collected within a fixed-length time window to continuously calibrate the external parameters, and use the newly calculated results to replace the old data for subsequent fusion algorithm calculations. Technologies based on three-dimensional map construction and loop detection require high-performance processors and large storage space to complete map construction and loop detection, which is not suitable for some cost-sensitive embedded systems; in addition, when VIO runs in an unfamiliar environment, this technology cannot be used because there is no map. Using deep learning technology to improve the scale drift problem requires high-performance processors and even GPUs to accelerate deep learning network calculations, which is expensive. When the running scene is very different from the training scene, poor results will also occur. The sliding window method requires both RTK and visual data to be valid for parameter calibration, and cannot be used in RTK failure scenarios such as multipath.

[0004] In summary, in a multipath environment, how to realize the parameter calibration of the combined positioning system composed of the RTK positioning system and the VIO positioning system has become a problem to be solved. Summary of the invention

[0005] The present application provides a method for parameter calibration, including: Determine an abnormality of a real-time dynamic carrier phase differential positioning technology RTK positioning system according to at least one set of positioning data of the combined positioning system, wherein a set of positioning data includes: at least one positioning coordinate output by the RTK positioning system and at least one positioning coordinate output by the visual inertial odometer (VIO) positioning system; When it is determined that the RTK positioning system is abnormal and in a stable offset state, parameter calibration is performed based on the positioning data of the combined positioning system.

[0006] On the other hand, an embodiment of the present application further provides a computer storage medium, wherein the computer storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned parameter calibration method is implemented.

[0007] On the other hand, an embodiment of the present application further provides a terminal, comprising: a memory and a processor, wherein the memory stores a computer program; wherein: The processor is configured to execute the computer program in the memory; When the computer program is executed by the processor, the method for parameter calibration as described above is implemented.

[0008] In another aspect, the embodiment of the present application further provides a parameter calibration device, comprising: a judgment unit and a calibration unit; wherein, The judgment unit is configured to: determine an abnormality of the RTK positioning system according to at least one set of positioning data of the combined positioning system, wherein the set of positioning data includes: at least one positioning coordinate output by the RTK positioning system and at least one positioning coordinate output by the visual inertial odometer (VIO) positioning system; The calibration unit is configured to perform parameter calibration based on the positioning data of the combined positioning system when it is determined that the RTK positioning system is abnormal and in a stable offset state.

[0009] The disclosed embodiment utilizes the characteristic that the positioning data output by the visual inertial odometer (VIO) positioning system will not have output jumps, and realizes the determination of abnormality of the real-time dynamic carrier phase differential positioning technology (RTK) positioning system through at least one set of positioning data; when it is determined that the RTK positioning system is abnormal and is in a stable offset state, parameter calibration is performed through the positioning data of the combined positioning system, thereby realizing the parameter calibration of the combined positioning system in a multi-path environment.

[0010] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by implementing the present application. Other advantages of the present application can be realized and obtained by the schemes described in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to provide an understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0012] Figure 1 A flow chart of a method for parameter calibration according to an embodiment of the present disclosure; Figure 2 A structural block diagram of a device for parameter calibration according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0013] The present application describes multiple embodiments, but the description is exemplary rather than restrictive, and it is obvious to those skilled in the art that there may be more embodiments and implementations within the scope of the embodiments described in the present application. Although many possible feature combinations are shown in the drawings and discussed in the specific embodiments, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with any other feature or element in any other embodiment, or may replace any other feature or element in any other embodiment.

[0014] The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in the present application may also be combined with any conventional features or elements to form a unique invention scheme. Any features or elements of any embodiment may also be combined with features or elements from other invention schemes to form another unique invention scheme. Therefore, it should be understood that any feature shown and / or discussed in the present application may be implemented individually or in any appropriate combination. Therefore, except for the limitations made according to the attached claims and their equivalents, the embodiments are not subject to other restrictions. In addition, various modifications and changes may be made within the scope of protection of the attached claims.

[0015] In addition, when describing representative embodiments, the specification may have presented the method and / or process as a specific sequence of steps. However, to the extent that the method or process does not rely on the specific order of the steps described herein, the method or process should not be limited to the steps of the specific order described. As will be understood by those of ordinary skill in the art, other sequences of steps are also possible. Therefore, the specific sequence of the steps set forth in the specification should not be interpreted as a limitation to the claims. In addition, the claims for the method and / or process should not be limited to the steps of performing them in the order written, and those skilled in the art can easily understand that these sequences can be changed and still remain within the spirit and scope of the embodiments of the present application.

[0016] The inventors of the present application have analyzed and found that: when the multipath effect of the global navigation satellite system (GNSS) receiver is significant, the positioning results output by the real-time kinematic differential positioning (RTK) system may show irregular divergence, or a relatively stable position offset may occur; when the actual operating trajectory of the GNSS receiver is a straight line and the calculated result is in a stable offset state with the true value, the operating trajectory output by the RTK positioning system is also a straight line; when the operating trajectory of the GNSS receiver is not a straight line, the RTK positioning system will hardly output a straight line trajectory.

[0017] Figure 1 Flow chart of the method for parameter calibration according to the embodiment of the present disclosure, as shown in Figure 1 As shown, including: Step 101: determining an abnormality of a real-time kinematic carrier phase differential positioning technology (RTK) positioning system according to at least one set of positioning data of a combined positioning system, wherein the set of positioning data includes: at least one positioning coordinate output by the RTK positioning system and at least one positioning coordinate output by a visual inertial odometer (VIO) positioning system; Step 102: When it is determined that the RTK positioning system is abnormal and in a stable offset state, parameter calibration is performed based on the positioning data of the combined positioning system.

[0018] The disclosed embodiment utilizes the characteristic that the positioning data output by the visual inertial odometer (VIO) positioning system will not have output jumps, and realizes the determination of abnormality of the real-time dynamic carrier phase differential positioning technology (RTK) positioning system through at least one set of positioning data; when it is determined that the RTK positioning system is abnormal and is in a stable offset state, parameter calibration is performed through the positioning data of the combined positioning system, thereby realizing the parameter calibration of the combined positioning system in a multi-path environment.

[0019] In order to realize the fusion of the two positioning results of the RTK positioning system and the VIO positioning system, it is necessary to calculate the transformation parameters of the coordinate systems of the output positions of the two systems to realize the unity of the coordinate systems of the two positioning systems, that is, to perform parameter calibration and complete the unification of the coordinate systems. It is possible to seamlessly switch between the two positioning systems to improve the overall positioning accuracy and reliability. The embodiment of the present disclosure calculates the coordinate system transformation parameters such as the rotation angle, translation distance and scaling factor of the VIO positioning system and the RTK positioning system respectively through the positioning data of the combined positioning system, unifies the coordinate systems of the two positioning systems through the calculated coordinate system transformation parameters, and realizes parameter calibration. Taking the RTK system using the WGS-84 coordinate system and the VIO system using the local coordinate system (such as the carrier coordinate system) as an example, the parameter calibration process includes: 1. Obtaining multiple sets of corresponding coordinate data from the two positioning systems (generally, if there are several transformation parameters that need to be calibrated, at least several sets of coordinate data are required, and the least squares method requires more sets of coordinate data to reduce the error); 2. Using the coordinate transformation algorithm in the relevant technology to calculate the transformation parameters, the method for calculating the transformation parameters may include: linear transformation: suitable for translation and scaling within a small range, using simple matrix operations; seven-parameter transformation method: including three-dimensional translation, rotation and scale adjustment, suitable for a large range of coordinate transformations; nonlinear transformation: in complex situations, more complex models may need to be used, such as polynomial or spline interpolation; 3. Using statistical methods such as the least squares method to optimize the calculated transformation parameters to minimize the position error between the two systems; 4. Unifying the coordinate systems of the two positioning systems through the optimized transformation parameters of the coordinate systems to achieve parameter calibration.

[0020] In an exemplary embodiment, the embodiment of the present disclosure determines an abnormal situation of a real-time RTK positioning system according to at least one set of positioning data of a combined positioning system, which may include: When positioning is performed through a combined positioning system, the abnormality of the positioning coordinates currently output by the RTK positioning system is judged by comparing the positioning data of a group of combined positioning systems received in real time, and the abnormality of the real-time RTK positioning system is determined.

[0021] The disclosed embodiment realizes real-time determination of abnormal conditions of the RTK positioning system based on positioning data received in real time, and provides support for ensuring the real-time performance of parameter calibration of the combined positioning system in a multi-path environment.

[0022] In an exemplary embodiment, the method of the embodiment of the present disclosure further includes: when it is determined that the positioning coordinates currently output by the RTK positioning system are abnormal, stopping parameter calibration.

[0023] In an exemplary embodiment, the method of the embodiment of the present disclosure further includes: when it is determined that the RTK positioning system is in an unstable offset state, stopping the parameter calibration of the positioning data received in real time, and continuing the parameter calibration of the next set of positioning data.

[0024] In an exemplary embodiment, the embodiment of the present disclosure determines that the RTK positioning system is in a stable offset state, which may include: After determining that the RTK positioning system is abnormal, receive N sets of positioning data; Based on N sets of positioning data, the stable offset state of the RTK positioning system is determined.

[0025] In an exemplary embodiment, the embodiment of the present disclosure determines a stable offset state of an RTK positioning system according to N sets of positioning data, including: When the number of recorded positioning data groups is greater than or equal to N, the first straightness error of the N coordinate data most recently output by the RTK positioning system and the second straightness error of the N coordinate data most recently output by the VIO positioning system are calculated respectively according to the most recently received N groups of positioning data; A stable offset state of the RTK positioning system is determined according to the calculated first straightness error and second straightness error.

[0026] To facilitate understanding of the technical method of this application, the following is a brief description of the relevant definitions: Straightness refers to the ability of a straight line element on a part to maintain an ideal straight line state, usually referred to as the degree of straightness. Its tolerance defines the maximum allowable variation between the actual straight line and the ideal straight line; the measurement and control of straightness is crucial in mechanical design and manufacturing because it directly affects the function and assembly accuracy of the part; by fitting an ideal straight line and calculating the deviation between the actual measured point and the ideal straight line, the straightness error is determined. Straightness error includes the following methods: 1. Minimum condition method: This method calculates the minimum value of the distance between two ideal straight lines that contain the actual elements being measured; the specific steps are: determine the maximum and minimum deviations of the measured straight line. Calculate the difference between the maximum and minimum values, which is the straightness error. 2. Drawing method: Draw the measured straight line and the ideal straight line on the drawing, and evaluate the error by visual comparison. This method is suitable for simple geometric shapes, but the accuracy is low; 3. Pitch method: suitable for the measurement of long parts. Divide the measured length into several small sections, use a level or autocollimator to measure the relative reading of each section, and then calculate the overall straightness error through data processing; 4. Data acquisition instrument method: Use a data acquisition instrument (such as a dial indicator) connected to the measured workpiece, and calculate the straightness error by automatically reading the maximum and minimum values. This method can reduce the error caused by manual readings and can automatically determine whether the workpiece is qualified; 5. Online measurement method: Use equipment such as photoelectric probes to measure the straightness of the workpiece in real time on the production line; this method improves measurement efficiency and accuracy and is suitable for large-scale production environments. Taking the minimum condition method as an example, the calculation steps include: determining the maximum and minimum deviations of the measured straight line; calculating the difference between the maximum and minimum values, which is the straightness error. The stable offset state in the disclosed embodiment generally refers to the situation where the system can maintain near a certain state after being disturbed, but will not completely return to the original state; this state is called critical stability in control theory.

[0027] In an exemplary embodiment, the embodiment of the present disclosure determines a stable offset state of the RTK positioning system according to the calculated first straightness error and second straightness error, including: Determine the first straight-line distance between the two points with the longest distance among the N coordinate data most recently output by the RTK positioning system, and determine the second straight-line distance between the two points with the longest distance among the N coordinate data most recently output by the VIO positioning system; The first straightness error is divided by the first straight line distance to obtain a first reference error ratio, and the second straightness error is divided by the second straight line distance to obtain a second reference error ratio; When the first reference error ratio and the second reference error ratio are both smaller than a preset error ratio threshold, it is determined that the combined positioning system is in a stable offset state.

[0028] In an exemplary embodiment, the error ratio threshold of the embodiment of the present disclosure can be set to 0.01, which can be adjusted by technicians based on experience; the above steps of the embodiment of the present disclosure are essentially to determine whether the GNSS and VIO running trajectories are straight lines to determine whether they are in a stable offset state; if they are both straight lines, it can be considered that the receiver output trajectory is a stable offset based on the true value. At this time, the positioning data output by the combined positioning system can be used for parameter calibration. The embodiment of the present disclosure achieves accurate judgment of the stable offset state based on N groups of positioning data, and provides a judgment basis for parameter calibration of the combined positioning system in a multi-path environment.

[0029] In an exemplary embodiment, the embodiment of the present disclosure performs parameter calibration based on positioning data of a combined positioning system, including: Based on the N groups of positioning data of the combined positioning system after determining that the positioning coordinates currently output by the RTK positioning system are abnormal, parameter calibration is performed using a preset first calibration method.

[0030] In an exemplary embodiment, the first calibration method in the embodiment of the present disclosure may include a hand-eye calibration method.

[0031] In an exemplary embodiment, the method of the present disclosure further includes: When it is determined that the RTK positioning system is normal, the positioning data of the combined positioning system after the RTK positioning system is determined to be normal is used to perform parameter calibration through a preset second calibration method.

[0032] In an exemplary instance, the second calibration method in the embodiments of the present disclosure may include a sliding window method.

[0033] In an exemplary embodiment, the embodiment of the present disclosure determines an abnormal situation of the positioning coordinates currently output by the RTK positioning system, including: When the deviation between the positioning coordinates output by the RTK positioning system and the positioning coordinates output by the VIO positioning system is greater than a preset deviation threshold, it is determined that the positioning coordinates currently output by the RTK positioning system are abnormal; When the deviation between the positioning coordinates output by the RTK positioning system and the positioning coordinates output by the VIO positioning system is less than or equal to a preset deviation threshold, it is determined that the positioning coordinates currently output by the RTK positioning system are normal.

[0034] In an exemplary instance, the deviation between the positioning coordinates output by the RTK positioning system in the embodiment of the present disclosure and the positioning coordinates output by the VIO positioning system may be an absolute error. The absolute error is compared with the deviation threshold to determine whether the positioning coordinates currently output by the RTK positioning system are abnormal. In the embodiment of the present disclosure, when the deviation is greater than the deviation threshold, it is determined that a significant deviation has occurred.

[0035] In an exemplary embodiment, the embodiment of the present disclosure records the positioning coordinates output by the combined positioning system at a preset time interval t.

[0036] In the embodiment of the present disclosure, the number of data sets N and the time interval t of data recording for parameter calibration are set by technicians based on experience; theoretically, the smaller N and t are, the better the real-time performance of the algorithm is, but the reliability of the subsequent straightness judgment is worse; conversely, the larger N and t are, the worse the real-time performance of the algorithm is, but the reliability of the subsequent straightness judgment is higher; taking all factors into consideration, the embodiment of the present disclosure can set N and t according to the operating speed of the GNSS receiver, assuming that the operating speed of the GNSS receiver is v, N=10, t=0.5m / v; example: when the receiver runs at a speed of 0.5m / s, N=10, t=1s.

[0037] The embodiment of the present disclosure further provides a computer storage medium, in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned parameter calibration method is implemented.

[0038] The embodiment of the present disclosure further provides a terminal, comprising: a memory and a processor, wherein a computer program is stored in the memory; The processor is configured to execute the computer program in the memory; When the computer program is executed by a processor, the above parameter calibration method is implemented.

[0039] Figure 2 The structural block diagram of the device for parameter calibration of the embodiment of the present disclosure is as follows: Figure 2 As shown, it includes: a judgment unit and a calibration unit; wherein, The judgment unit is configured to: determine an abnormality of the RTK positioning system according to at least one set of positioning data of the combined positioning system, wherein the set of positioning data includes: at least one positioning coordinate output by the RTK positioning system and at least one positioning coordinate output by the visual inertial odometer (VIO) positioning system; The calibration unit is configured to perform parameter calibration based on the positioning data of the combined positioning system when it is determined that the RTK positioning system is abnormal and in a stable offset state.

[0040] In an exemplary embodiment, the calibration unit of the embodiment of the present disclosure is further configured to stop parameter calibration when it is determined that the positioning coordinates currently output by the RTK positioning system are abnormal.

[0041] In an exemplary embodiment, the calibration unit of the embodiment of the present disclosure is further configured to: when it is determined that the RTK positioning system is in an unstable offset state, stop the parameter calibration of the positioning data received in real time, and continue the parameter calibration of the next set of positioning data.

[0042] In an exemplary embodiment, the calibration unit of the embodiment of the present disclosure is configured to perform parameter calibration based on positioning data of the combined positioning system, including: Based on the N groups of positioning data of the combined positioning system after determining that the positioning coordinates currently output by the RTK positioning system are abnormal, parameter calibration is performed using a preset first calibration method.

[0043] In an exemplary embodiment, the first calibration method in the embodiment of the present disclosure may include a hand-eye calibration method.

[0044] In an exemplary embodiment, the calibration unit of the embodiment of the present disclosure is further configured to: When it is determined that the RTK positioning system is normal, the positioning data of the combined positioning system after the RTK positioning system is determined to be normal is used to perform parameter calibration through a preset second calibration method.

[0045] In an exemplary instance, the second calibration method in the embodiments of the present disclosure may include a sliding window method.

[0046] In an exemplary embodiment, the judgment unit of the embodiment of the present disclosure is configured as follows: When the deviation between the positioning coordinates output by the RTK positioning system and the positioning coordinates output by the VIO positioning system is greater than a preset deviation threshold, it is determined that the positioning coordinates currently output by the RTK positioning system are abnormal; When the deviation between the positioning coordinates output by the RTK positioning system and the positioning coordinates output by the VIO positioning system is less than or equal to a preset deviation threshold, it is determined that the positioning coordinates currently output by the RTK positioning system are normal.

[0047] In an exemplary embodiment, the calibration unit of the embodiment of the present disclosure is further configured to: After determining that the RTK positioning system is abnormal, receive N sets of positioning data; Based on N sets of positioning data, the stable offset state of the RTK positioning system is determined.

[0048] In an exemplary embodiment, the calibration unit of the embodiment of the present disclosure is configured to determine a stable offset state of the RTK positioning system according to N sets of positioning data, including: When the number of recorded positioning data groups is greater than or equal to N, the first straightness error of the N coordinate data most recently output by the RTK positioning system and the second straightness error of the N coordinate data most recently output by the VIO positioning system are calculated respectively according to the most recently received N groups of positioning data; A stable offset state of the RTK positioning system is determined according to the calculated first straightness error and second straightness error.

[0049] In an exemplary embodiment, the calibration unit of the embodiment of the present disclosure is configured to determine a stable offset state of the RTK positioning system according to the calculated first straightness error and second straightness error, including: Determine the first straight-line distance between the two points with the longest distance among the N coordinate data most recently output by the RTK positioning system, and determine the second straight-line distance between the two points with the longest distance among the N coordinate data most recently output by the VIO positioning system; The first straightness error is divided by the first straight line distance to obtain a first reference error ratio, and the second straightness error is divided by the second straight line distance to obtain a second reference error ratio; When the first reference error ratio and the second reference error ratio are both smaller than a preset error ratio threshold, it is determined that the combined positioning system is in a stable offset state.

[0050] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As is known to those skilled in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

Claims

1. A method for parameter calibration, characterized in that: include: Determine an abnormality of a real-time dynamic carrier phase differential positioning technology RTK positioning system according to at least one set of positioning data of the combined positioning system, wherein a set of positioning data includes: at least one positioning coordinate output by the RTK positioning system and at least one positioning coordinate output by the visual inertial odometer (VIO) positioning system; When it is determined that the RTK positioning system is abnormal and in a stable offset state, parameter calibration is performed based on the positioning data of the combined positioning system.

2. The method according to claim 1, characterized in that Determining that the RTK positioning system is in a stable offset state includes: After determining that the RTK positioning system is abnormal, receiving N sets of positioning data; A stable offset state of the RTK positioning system is determined based on the N groups of positioning data.

3. The method according to claim 2, characterized in that Determining the stable offset state of the RTK positioning system according to the N groups of positioning data includes: When the number of groups of the recorded positioning data is greater than or equal to N, the first straightness error of the N coordinate data most recently output by the RTK positioning system and the second straightness error of the N coordinate data most recently output by the VIO positioning system are respectively calculated according to the N groups of positioning data most recently received; A stable offset state of the RTK positioning system is determined according to the calculated first straightness error and the second straightness error.

4. The method according to claim 3, characterized in that Determining the stable offset state of the RTK positioning system according to the calculated first straightness error and the second straightness error includes: Determine a first straight-line distance between two points that are farthest apart in the N coordinate data most recently output by the RTK positioning system, and determine a second straight-line distance between two points that are farthest apart in the N coordinate data most recently output by the VIO positioning system; Dividing the first straightness error by the first straight line distance to obtain a first reference error ratio, and dividing the second straightness error by the second straight line distance to obtain a second reference error ratio; When both the first reference error ratio and the second reference error ratio are smaller than a preset error ratio threshold, it is determined that the combined positioning system is in the stable offset state.

5. The method according to any one of claims 1 to 4, characterized in that: The parameter calibration based on the positioning data of the combined positioning system includes: Based on the N groups of positioning data of the combined positioning system after determining that the positioning coordinates currently output by the RTK positioning system are abnormal, the parameter calibration is performed using a preset first calibration method.

6. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: When it is determined that the RTK positioning system is normal, the positioning data of the combined positioning system after the RTK positioning system is determined to be normal is used to perform parameter calibration through a preset second calibration method.

7. The method according to any one of claims 1 to 4, characterized in that: The determining of the abnormal situation of the positioning coordinates currently output by the RTK positioning system includes: When the deviation between the positioning coordinates output by the RTK positioning system and the positioning coordinates output by the VIO positioning system is greater than a preset deviation threshold, determining that the positioning coordinates currently output by the RTK positioning system are abnormal; When the deviation between the positioning coordinates output by the RTK positioning system and the positioning coordinates output by the VIO positioning system is less than or equal to the deviation threshold, it is determined that the positioning coordinates currently output by the RTK positioning system are normal.

8. A computer storage medium, wherein a computer program is stored in the computer storage medium, and when the computer program is executed by a processor, the method for parameter calibration according to any one of claims 1 to 7 is implemented.

9. A terminal, comprising: A memory and a processor, wherein the memory stores a computer program; wherein, The processor is configured to execute the computer program in the memory; When the computer program is executed by the processor, the parameter calibration method according to any one of claims 1 to 7 is implemented.

10. A parameter calibration device, comprising: A judgment unit and a calibration unit; wherein, The judgment unit is configured to: determine an abnormality of the RTK positioning system according to at least one set of positioning data of the combined positioning system, wherein the set of positioning data includes: at least one positioning coordinate output by the RTK positioning system and at least one positioning coordinate output by the visual inertial odometer (VIO) positioning system; The calibration unit is configured to perform parameter calibration based on the positioning data of the combined positioning system when it is determined that the RTK positioning system is abnormal and in a stable offset state.

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