Site map calibration method, system and photovoltaic robot

Abstract

The application provides a site map calibration method and system and a photovoltaic robot, comprising: dividing a target site into a plurality of sub-modules; collecting first positioning data of the photovoltaic robot at every preset distance or preset time, and collecting second positioning data of the photovoltaic robot through a positioning mobile station; obtaining a global conversion parameter matrix of the target site according to all the first positioning data and the second positioning data; obtaining a first sub-module with the first positioning data and the second positioning data in the sub-modules, and obtaining a calibration conversion parameter matrix of each first sub-module according to the first positioning data and the second positioning data within a preset range from the center of the first sub-module; and taking the global conversion parameter matrix as a calibration conversion parameter matrix of a second sub-module lacking the first positioning data or the second positioning data in the sub-modules. The scheme can realize accurate calibration of GNSS positioning data and map positioning data, thereby realizing accurate navigation of the photovoltaic robot.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of map calibration, and in particular to a site map calibration method, system and photovoltaic robot. BACKGROUND

[0002] The photovoltaic robot is an intelligent robot that automatically operates in a photovoltaic power station. The working scene of the photovoltaic robot is generally a large photovoltaic power station in a remote and desolate uninhabited area or a gobi desert. The photovoltaic robot has a local map during work, and various work tasks are performed on the map. Therefore, the positioning of the robot on the map is particularly important. GNSS positioning is an absolute positioning method for the photovoltaic robot. RTK-GNSS positioning is accurate, but in such a remote large photovoltaic power station, there is no network and base station, and it is basically infeasible. GNSS positioning that is independent of external network and base station by building a reference station becomes a usable positioning method. The data obtained by GNSS positioning is longitude and latitude, and UTM coordinates (utmx, utmy) are obtained by conversion. The positioning on the map is (x, y) coordinates. Therefore, a set of parameters are needed to convert the UTM coordinates (utmx, utmy) into (x, y) in the map.

[0003] However, in actual use, there is irregular deviation between the GNSS positioning data and the positioning data in the map. The reason is that the UTM coordinate error is enlarged in a non-linear manner as the distance from the reference station is farther and various obstructions affect. At the same time, due to the large area of the photovoltaic power station and the undulating terrain, the map also has a large non-linear error. Therefore, a more accurate calibration system is needed to accurately convert the GNSS positioning data to the map, so as to realize accurate navigation of the photovoltaic robot. SUMMARY

[0004] The purpose of the present application is to provide a site map calibration method, system and photovoltaic robot, which realizes accurate calibration of GNSS positioning data and positioning data in the map, so as to accurately convert the GNSS positioning data to the map and realize accurate navigation of the photovoltaic robot.

[0005] The technical solution provided by the present application is as follows:

[0006] In a first aspect, the present application provides a site map calibration method applied to a photovoltaic robot. The photovoltaic robot is provided with a positioning mobile station compatible with a global positioning reference station, and is provided with a positioning system based on a local map. The method comprises the following steps:

[0007] Dividing a target site into a plurality of preset size sub-modules;

[0008] In the driving process of the photovoltaic robot, the first positioning data of the photovoltaic robot is collected by the positioning system at every preset distance or preset time, and the second positioning data of the photovoltaic robot is collected by the positioning mobile station;

[0009] A global conversion parameter matrix of the target site is obtained according to all the first positioning data and the second positioning data;

[0010] A first sub-module having the first positioning data and the second positioning data in the sub-modules is obtained, and a calibration conversion parameter matrix of each first sub-module is obtained according to the first positioning data and the second positioning data within a preset range from the center of the first sub-module, the preset range being not less than the radius or side length of the sub-module;

[0011] The global conversion parameter matrix is taken as a calibration conversion parameter matrix of a second sub-module lacking the first positioning data or the second positioning data in the sub-modules.

[0012] Since GNSS positioning data can be accurately converted to a map within a certain range through a set of conversion parameters, the present scheme divides the target site into a plurality of sub-modules of a preset size, and collects a plurality of sets of first positioning data under the map and second positioning data (GNSS positioning data) under the GNSS positioning in the driving process of the photovoltaic robot. For each sub-module, the sub-module having the first positioning data and the second positioning data is taken as a first sub-module, and the calibration conversion parameter matrix of the first sub-module can be obtained through the first positioning data and the second positioning data within a preset range from the center of the first sub-module. The sub-module lacking the first positioning data or the second positioning data is taken as a second sub-module, and the global conversion parameter matrix can be taken as the calibration conversion parameter matrix of the second sub-module first, and then updated and replaced, so that each sub-module has an independent and more accurate calibration conversion parameter matrix. In the driving and positioning of the photovoltaic robot, the accurate calibration of the GNSS positioning data and the positioning data under the map can be realized, so that the GNSS positioning data can be accurately converted to the map, and the accurate navigation of the photovoltaic robot can be realized.

[0013] In some embodiments, the site map calibration method provided by the present application further comprises: when the photovoltaic robot changes from an off state to an on state, converting the currently collected second positioning data into third positioning data based on the local map according to the currently collected second positioning data and the global conversion parameter matrix;

[0014] The current sub-module in which the photovoltaic robot is located is determined according to the third positioning data, and a current calibration conversion parameter matrix corresponding to the current sub-module is obtained;

[0015] mapping the second positioning data currently collected onto the local map according to the current calibration conversion parameter matrix.

[0016] In some embodiments, the site map calibration method provided by the present application further comprises: when the photovoltaic robot is continuously in a working state, converting the second positioning data currently collected into fourth positioning data based on the local map according to the second positioning data currently collected and the calibration conversion parameter matrix determined by the previous first sub-module for the photovoltaic robot;

[0017] determining a next sub-module for the photovoltaic robot to travel according to the fourth positioning data and the working route of the photovoltaic robot, and positioning the photovoltaic robot running to the next sub-module with the calibration conversion parameter matrix corresponding to the next sub-module.

[0018] In some embodiments, the site map calibration method provided by the present application further comprises: when the positioning data of the first sub-module is updated, calibrating and updating the calibration conversion parameter matrix corresponding to the first sub-module according to the updated positioning data;

[0019] when the positioning data of the second sub-module is newly added, calculating a new calibration conversion parameter matrix corresponding to the second sub-module according to the newly added positioning data, and replacing the original calibration conversion parameter matrix.

[0020] In some embodiments, the global positioning reference station is located at a fixed position of the target site.

[0021] The global positioning reference station receives positioning data of a GNSS system, and is used to correct the second positioning data of the positioning mobile station.

[0022] In some embodiments, the calibration parameters of the calibration conversion parameter matrix include an offset in the x direction, an offset in the y direction, a direction offset angle, and a relative scaling factor.

[0023] In some embodiments, the calibration conversion parameter matrix is calculated in the following manner:

[0024] The corresponding relationship between the first positioning data and the second positioning data within a preset range from the center of the first sub-module can be expressed as:

[0025] (1)

[0026] wherein, is the first positioning data, is the second positioning data, is the offset in the x direction, is the offset in the y direction, is the direction offset angle and is the relative scaling factor, i is the i-th block, and the first submodule;

[0027] An intermediate variable is introduced and Expanding equation (1), we have:

[0028] (2)

[0029] (3)

[0030] Based on the calibration parameters of the calibration transformation parameter matrix, equation (2) and equation (3) are converted into matrix form, and we have:

[0031] (4)

[0032] When N>4, matrix (4) is simplified as:

[0033] (5)

[0034] wherein,

[0035] ,

[0036] ,

[0037] ,

[0038] Using the least square method to solve the matrix, the solution of the least square is: After a and b are obtained, we have: ,

[0039] ,

[0040] Further, the calibration parameters are obtained.

[0041] In some embodiments, the site map calibration method provided by the present application further comprises: storing the global transformation parameter matrix of the target site and the calibration transformation parameter matrix of each submodule in the form of a mapping table.

[0042] In a second aspect, the present application provides a site map calibration system, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to realize the steps of the site map calibration method of the first aspect.

[0043] In a third aspect, the present application provides a photovoltaic robot positioned by the site map calibration method of the first aspect.

[0044] The application provides a site map calibration method, system and photovoltaic robot. BRIEF DESCRIPTION OF DRAWINGS

[0045] The above features, technical characteristics, advantages and implementation manners of the application will be further described in the following preferred embodiments in a clear and understandable manner in combination with the drawings.

[0046] Figure 1 is a schematic diagram of the overall process of an embodiment of the application;

[0047] Figure 2 is a schematic diagram of the site map calibration process of an embodiment of the application. DETAILED DESCRIPTION

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, specific implementation manners of the application will be described below with reference to the drawings. Obviously, the drawings in the following description only represent some embodiments of the application, and for those skilled in the art, other drawings can be obtained from these drawings without creative effort, and other embodiments can also be obtained.

[0049] In order to make the drawings simple, only the parts related to the application are shown in the drawings, which do not represent the actual structure of the product. In addition, in order to make the drawings simple and easy to understand, in some drawings, only one of the parts with the same structure or function is shown, or only one of them is marked. In this document, "one" not only means "only one", but also means "more than one".

[0050] The photovoltaic robot is an intelligent robot that automatically operates in a photovoltaic power station. Its working scene is generally a large photovoltaic power station in a remote and desolate uninhabited area or a Gobi desert. The photovoltaic robot has a local map when it works, and various work tasks are performed on this map, so the positioning of the robot on this map is particularly important. The photovoltaic robot usually has a positioning system that can realize the positioning of the photovoltaic robot on the map during movement. The positioning data under the map can be represented as .

[0051] Global positioning reference station such as GNSS (Global Navigation Satellite System) positioning is an absolute positioning method of photovoltaic robot. GNSS positioning is a process of calculating the distance (pseudo-range) between the receiver and the satellite by receiving signals from multiple satellites, combining satellite orbit parameters (ephemeris), and using spatial resection to calculate the three-dimensional coordinates (longitude, latitude, and altitude) of the receiver on the earth and the time. Among them, RTK-GNSS (Real-Time Kinematic Global Navigation Satellite System, Real-Time Kinematic Global Navigation Satellite System based on carrier phase difference) positioning is accurate, but in such remote large photovoltaic power stations, there is no network and base station, which is basically not feasible. GNSS positioning based on self-built reference station does not depend on external network and base station, and becomes a useful positioning method. The data obtained by GNSS positioning is longitude and latitude, and UTM coordinates (utmx, utmy) are obtained by conversion. The positioning on the map is (x, y) coordinates, so a set of parameters are needed to convert UTM coordinates (utmx, utmy) into (x, y) in map coordinates.

[0052] However, in actual use, there is irregular deviation between global positioning data and positioning data on the map. The reason is that as the robot is farther away from the global positioning reference station, the UTM coordinate error is enlarged in a non-linear manner due to various shielding effects. At the same time, due to the large area of photovoltaic power station and the undulating terrain, the map also has a large non-linear error. Therefore, a more accurate calibration system is needed to accurately convert GNSS positioning data to the map, so as to realize accurate navigation of photovoltaic robots.

[0053] Considering that the global positioning reference station such as GNSS positioning data can be accurately converted to the map within a certain range (usually a radius of about 80 meters), the accuracy meets the use requirements. The photovoltaic site is divided into a plurality of sub-modules (for example, 50m*50m square), after collecting a plurality of map under the first positioning data and the global positioning reference station positioning under the second positioning data (GNSS positioning data), a global conversion parameter matrix can be solved by all the collected data, at the same time, each sub-module is calculated separately, and a more accurate calibration conversion parameter matrix can be solved for each sub-module by the sampling data within the preset range (such as GNSS positioning data, a radius of about 80 meters) from the center of each sub-module. In this way, during the movement of the photovoltaic robot, the positioning of the photovoltaic robot can be performed in real time according to the calibration conversion parameter matrix of each sub-module, so that the positioning is more accurate, and the global positioning data can be accurately converted to the map. Of course, the present application can not be limited to the positioning of the photovoltaic robot, and the positioning of other robots, mobile vehicles and the like can also adopt the technical means of the present application, which is not limited by the present application. In the following, the present application will be described in detail in combination with the drawings:

[0054] In one embodiment, referring to the description attached Figure 1 The present application provides a site map calibration method applied to a photovoltaic robot, the photovoltaic robot is provided with a positioning mobile station matched with a global positioning reference station, and the photovoltaic robot is provided with a positioning system based on a local map, comprising the steps of:

[0055] S100, dividing a target site into a plurality of sub-modules of a preset size;

[0056] S200, in the driving process of the photovoltaic robot, collecting first positioning data of the photovoltaic robot by the positioning system every preset distance or preset time, and collecting second positioning data of the photovoltaic robot by the positioning mobile station;

[0057] S300, acquiring a global conversion parameter matrix of the target site according to all the first positioning data and the second positioning data;

[0058] S400, acquiring a first sub-module having the first positioning data and the second positioning data in the sub-module, and acquiring a calibration conversion parameter matrix of each first sub-module according to the first positioning data and the second positioning data within a preset range from the center of the first sub-module, the preset range being not less than the radius or length of the sub-module;

[0059] S500, taking the global conversion parameter matrix as a calibration conversion parameter matrix of a second sub-module lacking the first positioning data or the second positioning data in the sub-module.

[0060] The photovoltaic robot has a moving platform, the positioning mobile station and the positioning system based on the local map can be installed on the robot moving platform. The global positioning reference station is located at a fixed position of the target site, and the global positioning reference station receives positioning data of a GNSS system, which is used to correct the second positioning data of the positioning mobile station and eliminate the cumulative deviation of the second positioning data of the positioning mobile station. The positioning system based on the local map can obtain the first positioning data of the photovoltaic robot.

[0061] The target site is divided into a plurality of preset size sub-modules, and the specific size and shape of the sub-modules are not limited. Since the global positioning reference station such as GNSS positioning data can be accurately converted to the map within a range of about 80 meters in radius by a set of conversion parameters, the side length or diameter of the sub-module is less than 80 meters, for example, the sub-module can be selected as a square of 50m*50m.

[0062] When collecting data, the more data, the more accurate the calibration conversion parameters calculated in the end, but too much collected data will also affect the travel of the photovoltaic robot. Therefore, in actual operation, the collected data can be adjusted according to actual needs. For example, as shown in Figure 2 The photovoltaic robot moving platform is driven to the working route, and the positioning under the map and the global positioning reference station such as GNSS positioning are started respectively; along the task path, the positioning data under the map is collected every 5m and the corresponding GNSS positioning data converted into UTM data , until the working route is run through. In addition, the second positioning data is the UTM data converted from the latitude and longitude data obtained by the positioning mobile station. UTM (Universal Transverse Mercator) coordinate system is a kind of equal angle transverse Mercator cylindrical projection coordinate system, which belongs to a plane rectangular coordinate system. The conversion between latitude and longitude data and UTM data can be realized by means of open source GeographicLib library, which is not limited by the present application.

[0063] After obtaining multiple sets of first positioning data and second positioning data, a global conversion parameter matrix of the target site can be obtained according to all the first positioning data and the second positioning data, which is also a commonly used conversion parameter matrix in the prior art. However, due to the increasing non-linear error of the UTM coordinate as the robot is farther away from the reference station and various obstructions, and due to the large area and undulating terrain of the photovoltaic site, the map also has a large non-linear error, resulting in low accuracy of using the global conversion parameter matrix as the calibration conversion parameter matrix. In the same position, the two kinds of positioning data will have obvious deviations. The present application divides the target site into a plurality of preset size sub-modules, determines the sub-modules with both first positioning data and second positioning data as first sub-modules, and calculates the calibration conversion parameter matrix of the first sub-module according to the first positioning data and the second positioning data within a preset range from the center of the first sub-module. The calibration conversion parameter matrix has higher accuracy than the global conversion parameter matrix. The sub-modules lacking first positioning data or second positioning data are used as second sub-modules, and the global conversion parameter matrix is used as the calibration conversion parameter matrix of the second sub-module, so that each sub-module has an independent calibration conversion parameter matrix, and the calibration conversion parameter matrices of the sub-modules can be updated and replaced as the amount of collected data increases. When storing the calibration conversion parameter matrices of the sub-modules, the global conversion parameter matrix of the target site and the calibration conversion parameter matrices of the sub-modules can be stored in the form of a mapping table.

[0064] Since GNSS positioning data can be accurately converted to a map within a certain range through a set of conversion parameters, the present application divides the target site into a plurality of preset size sub-modules, and collects multiple sets of first positioning data under the map and second positioning data (GNSS positioning data) under global positioning through the positioning system during the travel of the photovoltaic robot. For each sub-module, the sub-module with first positioning data and second positioning data is used as a first sub-module, and the calibration conversion parameter matrix of the first sub-module can be calculated through the first positioning data and the second positioning data within a preset range from the center of the first sub-module. The sub-module lacking first positioning data or second positioning data is used as a second sub-module, and the global conversion parameter matrix can be used as the calibration conversion parameter matrix of the second sub-module, which can be updated and replaced later, so that each sub-module has an independent and more accurate calibration conversion parameter matrix. When the photovoltaic robot travels and is positioned, the global positioning data such as GNSS positioning data and the positioning data under the map can be accurately calibrated, so that the global positioning data can be accurately converted to the map, and the photovoltaic robot can be accurately navigated.

[0065] In one embodiment, on the basis of the foregoing embodiment, the site map calibration method provided by the application further comprises: when the photovoltaic robot changes from the shutdown state to the startup state, converting the currently collected second positioning data into third positioning data based on the local map according to the currently collected second positioning data and the global conversion parameter matrix; determining the current sub-module in which the photovoltaic robot is located according to the third positioning data, and obtaining the current calibration conversion parameter matrix corresponding to the current sub-module; and accurately mapping the currently collected second positioning data onto the local map according to the current calibration conversion parameter matrix, so as to realize the alignment positioning of the photovoltaic robot at the startup time.

[0066] In one embodiment, on the basis of the foregoing embodiment, the site map calibration method provided by the application further comprises: when the photovoltaic robot continuously stays in the working state, converting the currently collected second positioning data into fourth positioning data based on the local map according to the currently collected second positioning data and the calibration conversion parameter matrix determined by the photovoltaic robot from the previous first sub-module; determining the next sub-module in which the photovoltaic robot travels according to the fourth positioning data and the working route of the photovoltaic robot, and positioning the photovoltaic robot running to the next sub-module with the calibration conversion parameter matrix corresponding to the next sub-module, so as to realize the accurate positioning of the photovoltaic robot when continuously staying in the working state.

[0067] In one embodiment, on the basis of the foregoing embodiment, the site map calibration method provided by the application further comprises: when the positioning data (the first positioning data or the second positioning data) of the first sub-module is updated, performing calibration update on the calibration conversion parameter matrix corresponding to the first sub-module according to the updated positioning data, so that the calibration conversion parameter matrices of the sub-modules can be more and more accurate; when the positioning data of the second sub-module is newly added, obtaining a new calibration conversion parameter matrix corresponding to the second sub-module according to the newly added positioning data, and replacing the original calibration conversion parameter matrix, and the original second sub-module becomes the first sub-module.

[0068] In one embodiment, on the basis of the foregoing embodiment, the calibration parameters of the calibration conversion parameter matrix include the offset in the x direction, the offset in the y direction, the direction offset angle and the relative scaling factor, which can be expressed as: Or .

[0069] The calculation method of the calibration conversion parameter matrix is: the first positioning data under the map and the corresponding UTM data under the global positioning comprise a set UM, the first positioning data and the map sub-module center coordinates comprise a set BC; a set PC composed of calibration parameters corresponding to the set BC is obtained.

[0070] Taking the calculation process of a certain block of the map as an example, in order to facilitate calculation, it is assumed that the center coordinates of the block are First, all the first positioning data and the corresponding second positioning data under the map in the set UMN that are within a preset distance (for example, 80 meters) from the center coordinates of the block are screened out from the set UMN, and a new set UMN is formed. The distance between the first positioning data under the map and the center coordinates of the block is calculated as:

[0071] ,

[0072] It is assumed that the set UMN contains N groups of first positioning data under the map and corresponding second positioning data , and the corresponding relationship of the first positioning data and the second positioning data within the preset range from the center of the first block can be represented as:

[0073] (1)

[0074] wherein, is the first positioning data, is the second positioning data, i takes a value in the range of 1 to N, is the offset in the x direction, is the offset in the y direction, is the direction offset angle, and is the relative scaling factor, and i is the first block of the first sub-module;

[0075] The intermediate variables and are introduced, and formula (1) is expanded to obtain:

[0076] (2)

[0077] (3)

[0078] This is a linear equation group about four unknown parameters Based on the calibration parameter of the conversion parameter matrix, formula (2) and formula (3) are converted into a matrix form to obtain:

[0079] (4)

[0080] When N>4, the matrix (4) is simplified as:

[0081] (5)

[0082] wherein,

[0083] ,

[0084] ,

[0085] ,

[0086] Solve the matrix using the least square method, and the solution of the least square is: After obtaining a and b, the following can be obtained:

[0087] ,

[0088] ,

[0089] Further obtain the calibration parameters . Perform the operation for each first sub-module with data on the map, and the calibration parameters of each first sub-module can be obtained. The calculation of the global conversion parameter matrix can also use the above calculation method, and only the input of all UM is required.

[0090] In the positioning of the photovoltaic robot, the UTM coordinate is known, and the coordinate under the map is obtained . First, the map coordinate calculated last time is obtained from the calibration conversion parameter in the calibration parameter matrix list:

[0091] ,

[0092] ,

[0093] If it is the first time to start without the map coordinate calculated last time, the global calibration conversion parameter is directly used. Suppose that the obtained conversion parameter is , then

[0094] ,

[0095] ,

[0096] That is, the GNSS positioning data is accurately converted to the positioning data on the map.

[0097] In an embodiment, on the basis of the foregoing embodiment, the application provides a site map calibration system, which comprises a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to realize the steps of the site map calibration method of the foregoing embodiment.

[0098] ​In one embodiment, on the basis of the foregoing embodiment, the application provides a photovoltaic robot positioned by the site map calibration method of the foregoing embodiment.

[0099] It should be noted that the above embodiments can be freely combined as needed. The above is only the preferred embodiment of the application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the application, a number of improvements and refinements can also be made, which should be considered as the protection scope of the application.

Claims

1. A method of site mapping, characterized by, The application is applied to a photovoltaic robot, which is provided with a positioning mobile station matched with a global positioning reference station and a positioning system based on a local map, and comprises the following steps: Dividing a target site into a plurality of preset-size sub-modules; During the driving of the photovoltaic robot, first positioning data of the photovoltaic robot is collected by the positioning system at a preset distance or a preset time, and second positioning data of the photovoltaic robot is collected by the positioning mobile station; Global conversion parameter matrixes of the target site are obtained according to all the first positioning data and the second positioning data; First sub-modules having the first positioning data and the second positioning data are obtained from the sub-modules, and calibration conversion parameter matrixes of each first sub-module are obtained according to the first positioning data and the second positioning data within a preset range from the center of the first sub-module, wherein the preset range is not less than the radius or the side length of the sub-module; The global conversion parameter matrixes are used as calibration conversion parameter matrixes of second sub-modules lacking the first positioning data or the second positioning data in the sub-modules.

2. The venue map localization method of claim 1, wherein, Further comprising: When the photovoltaic robot changes from an off state to an on state, the second positioning data currently collected is converted into third positioning data based on the local map according to the second positioning data currently collected and the global conversion parameter matrixes; A current sub-module where the photovoltaic robot is located is determined according to the third positioning data, and a current calibration conversion parameter matrix corresponding to the current sub-module is obtained; The second positioning data currently collected is mapped onto the local map according to the current calibration conversion parameter matrix.

3. The venue map localization method of claim 1, wherein, Further comprising: When the photovoltaic robot continuously operates, the second positioning data currently collected is converted into fourth positioning data based on the local map according to the second positioning data currently collected and the calibration conversion parameter matrix of the photovoltaic robot determined by the last first sub-module; A next sub-module where the photovoltaic robot drives is determined according to the fourth positioning data and the working route of the photovoltaic robot, and the photovoltaic robot is positioned in the next sub-module by using the calibration conversion parameter matrix corresponding to the next sub-module.

4. The venue map localization method of claim 1, wherein, Further comprising: When the positioning data of the first sub-module is updated, the calibration conversion parameter matrix corresponding to the first sub-module is calibrated and updated according to the updated positioning data; When the positioning data lacking in the second sub-module is added, a new calibration conversion parameter matrix corresponding to the second sub-module is obtained according to the added positioning data, and the original calibration conversion parameter matrix is replaced.

5. The field map calibration method of claim 1, wherein, The global positioning reference station is located at a fixed position of the target site; The global positioning reference station receives positioning data of a GNSS system, which is used to correct the second positioning data of the positioning mobile station.

6. The field map calibration method of claim 1, wherein, The calibration parameters of the calibration conversion parameter matrix include an offset in the x direction, an offset in the y direction, a direction offset angle and a relative scaling factor.

7. The field map calibration method of claim 6, wherein, The calibration conversion parameter matrix is calculated in the following manner: The corresponding relationship between the first positioning data and the second positioning data within the preset range from the center of the first sub-module can be represented as: （1） wherein, is the first positioning data, is the second positioning data, is the offset in x direction, is the offset in y direction, is the direction offset angle and is the relative scaling factor, i is the i-th block the first sub-module; Introducing an intermediate variable and Expanding equation (1), we obtain: （2） （3） The calibration parameters based on the calibration conversion parameter matrix are used to convert formula (2) and formula (3) into a matrix form, and the following can be obtained: （4） When N>4, the matrix (4) is simplified as: （5） Wherein: ， ， ， The matrix is solved using the least square method, and the solution of the least square is: After a and b are obtained, we have: , ， Further, the calibration parameters are obtained .

8. The field mapping method of claim 1, wherein, Further comprising: The global conversion parameter matrix of the target site and the calibration conversion parameter matrix of each sub-module are stored in the form of a mapping table.

9. A venue mapping system comprising a memory, a processor, and a computer program stored on the memory, wherein, The processor executes the computer program to implement the steps of the site map calibration method in any one of claims 1-8.

10. A photovoltaic robot, characterized in that, Positioning is performed by the site map calibration method in any one of claims 1-8.

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