A canvas-based map calibration method, device and terminal equipment

Abstract

The application is suitable for the field of image calibration technology, and provides a map calibration method and device based on canvas and terminal equipment, the method comprising: when receiving a partition calibration instruction, obtaining outer boundary information and a partition calibration type of a preset area, determining a pre-calibration visual image and a pre-calibration instant positioning image corresponding to the preset area, segmenting the pre-calibration visual image and the pre-calibration instant positioning image according to collected segmentation parameters, obtaining at least two pre-calibration visual partition images and pre-calibration instant positioning partition images, collecting calibration point parameters according to the partition calibration type and calibrating target partition image pairs to obtain calibrated visual partition images and instant positioning partition images. The application improves the precision of instant positioning images by performing partition calibration on visual images and instant positioning images on the basis of pre-calibration, thereby improving the control precision of controlling robots based on visual images.

Description

Technical Field

[0001] This application belongs to the field of image calibration technology, and in particular relates to a canvas-based map calibration method, apparatus and terminal equipment. Background Technology

[0002] In the process of controlling a robot, it is usually necessary to issue commands to the robot based on a visual map so that the robot can perform corresponding operations on the corresponding real-time positioning map.

[0003] However, the real-time localization maps constructed by relevant robot localization technologies have certain errors. This causes distortion of the visual map, resulting in errors in the robot's localization and navigation results after control commands are issued based on the visual map. This affects the normal performance of the robot's tasks and leads to a reduction in the control accuracy of the robot. Summary of the Invention

[0004] This application provides a canvas-based map calibration method, apparatus, and terminal device, which can solve the problem that the low accuracy of map construction methods makes it impossible to accurately control robots based on the constructed maps.

[0005] In a first aspect, embodiments of this application provide a canvas-based map calibration method, including:

[0006] Upon receiving a partition calibration command, the partition calibration parameters carried by the command are parsed and obtained; wherein, the partition calibration parameters include the outer boundary information of the preset area and the partition calibration type;

[0007] Based on the outer boundary information, a pre-calibrated visualization image and a pre-calibrated real-time positioning image corresponding to the preset region are determined; the pre-calibrated visualization image is a visualization image that has undergone pre-calibration processing; the pre-calibrated real-time positioning image is a real-time positioning image that has undergone pre-calibration processing.

[0008] Collect segmentation parameters, and segment the pre-calibrated visualization image and the pre-calibrated instantaneous localization image according to the segmentation parameters to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images;

[0009] According to the partition calibration type, the corresponding calibration point parameters are collected, and the target partition image pair is calibrated based on the calibration point parameters to obtain the calibrated visual partition image and the calibrated real-time positioning partition image; the target partition image pair includes the target pre-calibrated visual partition image and the corresponding target pre-calibrated real-time positioning partition image.

[0010] This embodiment, upon receiving a partition calibration command, parses the partition calibration parameters, determines a pre-calibrated visual image and a pre-calibrated real-time positioning image corresponding to a preset region based on outer boundary information, collects segmentation parameters, and segments the pre-calibrated visual image and the pre-calibrated real-time positioning image to obtain at least two pre-calibrated visual partition images and at least two pre-calibrated real-time positioning partition images. According to the partition calibration type, corresponding calibration point parameters are collected, and the target partition image pair is calibrated based on the calibration point parameters to obtain calibrated visual partition images and real-time positioning partition images. By segmenting the pre-calibrated visual image and real-time positioning image, and then further calibrating the partition image based on the calibration points, the accuracy of the real-time positioning image is improved, thereby improving the control accuracy of robot control based on the visual image.

[0011] In one embodiment, the partition calibration type includes specified area calibration or global calibration;

[0012] Correspondingly, the step involves collecting corresponding calibration point parameters based on the partition calibration type, calibrating the target partition image pair based on the calibration point parameters, and obtaining a calibrated visual partition image and a calibrated real-time positioning partition image; the target partition image pair includes a target pre-calibrated visual partition image and a corresponding target pre-calibrated real-time positioning partition image, comprising:

[0013] When the partition calibration type is detected to be specified area calibration, the target partition parameters are collected;

[0014] The target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image are determined based on the target partition parameters.

[0015] Collect at least two first calibration point parameters on the target pre-calibration visualization partition image, and determine at least two second calibration point parameters on the target pre-calibration instant positioning partition image based on the first calibration point parameters;

[0016] Based on the first calibration point parameter and the second calibration point parameter, the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image are calibrated to obtain the calibrated visualization partition image and the calibrated instant positioning partition image; the first calibration point parameter is the coordinate of the first calibration point in the target pre-calibration visualization partition image, and the second calibration point parameter is the coordinate of the second calibration point in the target pre-calibration instant positioning partition image.

[0017] In one embodiment, the step of collecting corresponding calibration point parameters according to the partition calibration type, calibrating the target partition image pair based on the calibration point parameters, and obtaining a calibrated visual partition image and a calibrated real-time positioning partition image; the target partition image pair includes a target pre-calibrated visual partition image and a corresponding target pre-calibrated real-time positioning partition image, and further includes:

[0018] When the partition calibration type is detected to be global calibration, each pre-calibration visualization partition image is traversed and used as the target pre-calibration visualization partition image; the pre-calibration instant positioning partition image corresponding to the target pre-calibration visualization partition image is used as the target pre-calibration instant positioning partition image.

[0019] At least two third calibration point parameters are acquired on each target pre-calibration visualization partition image, and at least two fourth calibration point parameters are determined on the target pre-calibration instant positioning partition image based on the third calibration point parameters; the third calibration point parameters are the coordinates of the third calibration point in the target pre-calibration visualization partition image, and the fourth calibration point parameters are the coordinates of the fourth calibration point in the target pre-calibration instant positioning partition image.

[0020] The target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image are calibrated according to the third calibration point parameters and the fourth calibration point parameters to obtain the calibrated visualization partition image and the calibrated instant positioning partition image.

[0021] In one embodiment, calibrating the target pre-calibration visualization partition image and the target pre-calibration instantaneous positioning partition image according to the third calibration point parameters and the fourth calibration point parameters to obtain the calibrated visualization partition image and the calibrated instantaneous positioning partition image includes:

[0022] Perform coordinate transformation on each of the third calibration point parameters and the corresponding fourth calibration point parameters to obtain the coordinate mapping relationship between each of the third calibration point parameters and the corresponding fourth calibration point parameters;

[0023] The calibrated visual partition image and the calibrated real-time positioning partition image are obtained based on the mapping relationship.

[0024] In one embodiment, the acquisition of segmentation parameters, and the segmentation of the pre-calibrated visualization image and the pre-calibrated instantaneous localization image according to the segmentation parameters, to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images, including:

[0025] Collect segmentation parameters; the segmentation parameters include at least one starting point coordinate and an ending point coordinate corresponding to each starting point coordinate;

[0026] When the starting point coordinates and the ending point coordinates are detected to be outside the preset area, the number N of the starting point coordinates is determined; where N is a positive integer greater than or equal to 1.

[0027] The pre-calibrated visualization image and the pre-calibrated instantaneous positioning image are segmented according to the starting point coordinates and the ending point coordinates to obtain N+1 pre-calibrated visualization partition images and N+1 pre-calibrated instantaneous positioning partition images.

[0028] In one embodiment, after acquiring the segmentation parameters, the method further includes:

[0029] When any of the starting point coordinates or the ending point coordinates are detected to be within the preset area, a partitioning failure alarm message is generated and displayed.

[0030] In one embodiment, determining the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image corresponding to the preset region based on the outer boundary information includes:

[0031] Based on the outer boundary information, obtain a visual image and a real-time positioning image corresponding to the preset area;

[0032] Collect at least two fifth calibration point parameters on the visualized image, and determine at least two sixth calibration point parameters on the instantaneous positioning image based on the fifth calibration point parameters;

[0033] The visualization image and the instantaneous positioning image are calibrated according to each of the fifth calibration point parameters and the corresponding sixth calibration point parameters to obtain the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image.

[0034] Secondly, embodiments of this application provide a canvas-based map calibration device, comprising:

[0035] The instruction parsing module is used to parse the partition calibration parameters carried by the partition calibration instruction when a partition calibration instruction is received; wherein, the partition calibration parameters include the outer boundary information of the preset area and the partition calibration type;

[0036] The image acquisition module is used to determine a pre-calibrated visualization image and a pre-calibrated real-time positioning image corresponding to the preset area based on the outer boundary information; the pre-calibrated visualization image is a visualization image that has undergone pre-calibration processing; the pre-calibrated real-time positioning image is a real-time positioning image that has undergone pre-calibration processing.

[0037] An image segmentation module is used to acquire segmentation parameters and segment the pre-calibrated visualization image and the pre-calibrated instantaneous localization image according to the segmentation parameters to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images.

[0038] The partition calibration module is used to collect corresponding calibration point parameters according to the partition calibration type, and calibrate the target partition image pair based on the calibration point parameters to obtain the calibrated visual partition image and the calibrated real-time positioning partition image; the target partition image pair includes the target pre-calibrated visual partition image and the corresponding target pre-calibrated real-time positioning partition image.

[0039] In one embodiment, the partition calibration module includes:

[0040] The partition parameter acquisition unit is used to acquire target partition parameters when the partition calibration type is detected to be specified area calibration;

[0041] The target partitioning determination unit is used to determine the target pre-calibration visualization partitioning image and the target pre-calibration instant positioning partitioning image based on the target partitioning parameters.

[0042] The calibration point parameter acquisition unit is used to acquire at least two first calibration point parameters on the target pre-calibration visualization partition image, and determine at least two second calibration point parameters on the target pre-calibration instant positioning partition image based on the first calibration point parameters.

[0043] The first calibration unit is used to calibrate the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image according to the first calibration point parameter and the second calibration point parameter, so as to obtain the calibrated visualization partition image and the calibrated instant positioning partition image; the first calibration point parameter is the coordinate of the first calibration point in the target pre-calibration visualization partition image, and the second calibration point parameter is the coordinate of the second calibration point in the target pre-calibration instant positioning partition image.

[0044] In one embodiment, the partition calibration module further includes:

[0045] The partition image traversal unit is used to, when the partition calibration type is detected to be global calibration, traverse each pre-calibration visualization partition image as a target pre-calibration visualization partition image; and use the pre-calibration instant positioning partition image corresponding to the target pre-calibration visualization partition image as the target pre-calibration instant positioning partition image.

[0046] The calibration point parameter determination unit is used to collect at least two third calibration point parameters on each target pre-calibration visualization partition image, and determine at least two fourth calibration point parameters on the target pre-calibration instant positioning partition image based on the third calibration point parameters; the third calibration point parameters are the coordinates of the third calibration point in the target pre-calibration visualization partition image, and the fourth calibration point parameters are the coordinates of the fourth calibration point in the target pre-calibration instant positioning partition image.

[0047] The second calibration unit is used to calibrate the target pre-calibrated visualization partition image and the target pre-calibrated instantaneous positioning partition image according to the third calibration point parameters and the fourth calibration point parameters, so as to obtain the calibrated visualization partition image and the calibrated instantaneous positioning partition image.

[0048] In one embodiment, the second calibration unit includes:

[0049] The coordinate transformation unit is used to perform coordinate transformation processing on each of the third calibration point parameters and the corresponding fourth calibration point parameters to obtain the coordinate mapping relationship between each of the third calibration point parameters and the corresponding fourth calibration point parameters;

[0050] The coordinate mapping unit is used to obtain the calibrated visual partition image and the calibrated real-time positioning partition image based on the mapping relationship.

[0051] In one embodiment, the image segmentation module includes:

[0052] A segmentation parameter acquisition unit is used to acquire segmentation parameters; the segmentation parameters include at least one starting point coordinate and an ending point coordinate corresponding to each starting point coordinate.

[0053] A quantity determination unit is used to determine the quantity N of the starting point coordinates when the starting point coordinates and the ending point coordinates are detected to be outside the preset area; wherein N is a positive integer greater than or equal to 1;

[0054] The image segmentation unit is used to segment the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image according to the starting point coordinates and the ending point coordinates, to obtain N+1 pre-calibrated visualization partition images and N+1 pre-calibrated instantaneous positioning partition images.

[0055] In one embodiment, the image segmentation module further includes:

[0056] The alarm unit is used to generate and display partitioning failure alarm information when it detects that any of the starting point coordinates or the ending point coordinates are within the preset area.

[0057] In one embodiment, the image acquisition module includes:

[0058] The image acquisition unit is used to acquire a visual image and a real-time positioning image corresponding to the preset area based on the outer boundary information;

[0059] A pre-calibration parameter acquisition unit is used to acquire at least two fifth calibration point parameters on the visualization image and determine at least two sixth calibration point parameters on the instantaneous positioning image based on the fifth calibration point parameters.

[0060] The pre-calibration unit is used to calibrate the visualization image and the instantaneous positioning image according to each of the fifth calibration point parameters and the corresponding sixth calibration point parameters, so as to obtain the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image.

[0061] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the canvas-based map calibration method as described in any of the first aspects above.

[0062] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the canvas-based map calibration method as described in any of the first aspects above.

[0063] Fifthly, embodiments of this application provide a computer program product that, when run on a terminal device, causes the terminal device to execute the canvas-based map calibration method described in any of the first aspects above.

[0064] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0065] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 This is a schematic flowchart of the canvas-based map calibration method provided in the embodiments of this application;

[0067] Figure 2 This is a schematic diagram of the pre-calibrated visualization image provided in an embodiment of this application;

[0068] Figure 3 This is a schematic diagram of the pre-calibrated instantaneous positioning image provided in an embodiment of this application;

[0069] Figure 4 This is a schematic diagram illustrating the application scenario of the segmentation pre-calibration visualization image and the pre-calibration instant localization image provided in the embodiments of this application;

[0070] Figure 5 This is a schematic diagram illustrating the application scenario of the target pre-calibration visualization partition image and the target pre-calibration real-time positioning partition image provided in the embodiments of this application;

[0071] Figure 6 This is a schematic diagram of the structure of the canvas-based map calibration device provided in the embodiments of this application;

[0072] Figure 7 This is a schematic diagram of the structure of the terminal device provided in the embodiments of this application. Detailed Implementation

[0073] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0074] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0075] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0076] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0077] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0078] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0079] The canvas-based map calibration method provided in this application can be applied to terminal devices such as mobile phones, tablets, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, and laptops. This application does not impose any restrictions on the specific type of terminal device.

[0080] Figure 1 A schematic flowchart of the canvas-based map calibration method provided in this application is shown. It is provided as an example and not a limitation. The method can be applied to the aforementioned laptop computer.

[0081] S101. Upon receiving a partition calibration command, the partition calibration parameters carried by the partition calibration command are parsed and obtained; wherein, the partition calibration parameters include the outer boundary information of the preset area and the partition calibration type.

[0082] Specifically, upon receiving a partition calibration command sent by the user through a user terminal, a partition calibration command generated by the user pressing a button, or a partition calibration command generated by the user touching or swiping the current terminal screen, the partition calibration command is parsed to obtain the partition calibration parameters carried by the aforementioned partition calibration command. These partition calibration parameters include, but are not limited to, the outer boundary information of a preset area and the partition calibration type. The preset area is the area to be calibrated for map calibration. The outer boundary information is generated by the user through touching or swiping, or determined based on information such as the GPS positioning information and name of the preset area input by the user through the user terminal. The partition calibration type includes, but is not limited to, specified area calibration and global calibration. Specified area calibration is a method of calibrating the visualized image and real-time positioning image corresponding to a portion of the preset area after segmenting it. Global calibration is a method of calibrating the visualized image and real-time positioning image corresponding to all the segments of the preset area after segmenting it. The segmentation parameters are standard data for determining the position and size of each segment in the preset area.

[0083] S102. Based on the outer boundary information, determine the pre-calibrated visualization image and the pre-calibrated instant positioning image corresponding to the preset area; the pre-calibrated visualization image is a visualization image that has undergone pre-calibration processing; the pre-calibrated instant positioning image is an instant positioning image that has undergone pre-calibration processing.

[0084] Specifically, two canvases are used to determine a visual image and a real-time positioning image corresponding to the preset area based on the outer boundary information of the preset area. These images are then pre-calibrated to obtain a pre-calibrated visual image and a pre-calibrated real-time positioning image corresponding to the preset area. The real-time positioning image is the image data obtained by the intelligent robot communicating with the current terminal, which locates and maps the preset area using the Simultaneous Localization and Mapping (SLAM) algorithm. The visual image is the image data constructed by an architect or designer designing the target area, or by a graphic UI designer based on CAD architectural drawings of the target area.

[0085] S103. Acquire segmentation parameters, and segment the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image according to the segmentation parameters to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous positioning partition images.

[0086] Specifically, the segmentation parameters include at least one starting point coordinate and a corresponding ending point coordinate. A segmentation line is formed by connecting a starting point and a corresponding ending point. The pre-calibration visualization image and the pre-calibration instantaneous localization image are segmented according to the segmentation line formed by the starting point coordinate and the ending point coordinate in the segmentation parameters, respectively, to obtain at least two pre-calibration visualization partition images and at least two pre-calibration instantaneous localization partition images.

[0087] Figure 2 A schematic diagram of a pre-calibrated visualization image is provided;

[0088] Figure 3 A schematic diagram of a pre-calibrated instantaneous positioning image is provided.

[0089] like Figure 2 As shown, a pre-calibrated visualization image corresponding to the preset region is obtained through the outer boundary information of the preset region, such as... Figure 3 As shown, a pre-calibrated instantaneous positioning image corresponding to the pre-calibrated visualization image is obtained through the aforementioned outer boundary information.

[0090] Figure 4 A schematic diagram illustrating an application scenario of segmenting pre-calibrated visualization images and pre-calibrated instantaneous localization images is provided.

[0091] Figure 5 A schematic diagram illustrating an application scenario for determining a target pre-calibration visualization partition image and a target pre-calibration instant positioning partition image is provided.

[0092] like Figure 4 As shown, taking a pre-calibrated visualization image as a reference, the user determines the starting point coordinates and the corresponding ending point coordinates on the pre-calibrated visualization image corresponding to the preset area (specifically, this includes determining the position of the starting point and the ending point on the pre-calibrated visualization image through a mouse-triggered click event, thus obtaining the starting point coordinates and the corresponding ending point coordinates; or, the user directly inputs the position of the starting point in the preset area and the corresponding position of the ending point in the preset area, thus obtaining the starting point coordinates and the corresponding ending point coordinates; or, the user inputs the GPS positioning information of the starting point and the ending point, and based on matching with the positioning address of the preset area, determines the position of the starting point and the ending point on the pre-calibrated visualization image, thus obtaining the starting point coordinates and the corresponding ending point coordinates). Two dividing lines are formed by connecting the starting point coordinates and the corresponding ending point coordinates; the pre-calibrated visualization image and the pre-calibrated real-time positioning image are divided by these dividing lines, resulting in three pre-calibrated visualization partition images (a1, a2, a3) and corresponding pre-calibrated real-time positioning partition images (b1, b2, b3) (e.g., ...). Figure 4As shown in the figure, it can be understood that, based on the pre-calibration operation, the segmented pre-calibration visualization image a1 has a certain correspondence with the pre-calibration instantaneous localization image b1, the pre-calibration visualization image a2 has a certain correspondence with the pre-calibration instantaneous localization image b2, and the pre-calibration visualization image a3 has a certain correspondence with the pre-calibration instantaneous localization image b3.

[0093] S104. Collect the corresponding calibration point parameters according to the partition calibration type, and calibrate the target partition image pair based on the calibration point parameters to obtain the calibrated visual partition image and the calibrated real-time positioning partition image; the target partition image pair includes the target pre-calibrated visual partition image and the corresponding target pre-calibrated real-time positioning partition image.

[0094] Specifically, based on the partition calibration type carried by the partition calibration command, the corresponding target pre-calibration visualization partition image and target pre-calibration instant positioning partition image are determined, and the first calibration point parameters in the target pre-calibration visualization partition image are collected. Based on the first calibration point parameters, the second calibration point parameters of the target pre-calibration instant positioning partition image are determined. Based on the first calibration point parameters and the second calibration point parameters, the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image corresponding to the target pre-calibration visualization partition image are calibrated to obtain the calibrated visualization partition image and the calibrated instant positioning partition image.

[0095] The calibration point parameter refers to the coordinates of the calibration point in the corresponding image.

[0096] Understandably, users can determine the coordinates of the calibration points in each target partition image (target pre-calibration visualization partition image and target pre-calibration real-time positioning partition image) by inputting the GPS positioning information of the calibration points; or, users can determine the coordinates of the calibration points in each target partition image by inputting the relative position information of the calibration points in the corresponding images; or, users can determine the coordinates of the calibration points generated by the click event in the standard target partition image (e.g., using the target pre-calibration visualization partition image as the standard target partition image to calibrate the corresponding target pre-calibration real-time positioning partition image, or using the target pre-calibration real-time positioning partition image as the standard target partition image to calibrate the corresponding target pre-calibration visualization partition image) by clicking the standard target partition image with the mouse, and thus determine the coordinates of the calibration points in another target partition image.

[0097] In one embodiment, the partition calibration type includes specified area calibration or global calibration;

[0098] Correspondingly, the step involves collecting corresponding calibration point parameters based on the partition calibration type, calibrating the target partition image pair based on the calibration point parameters, and obtaining a calibrated visual partition image and a calibrated real-time positioning partition image; the target partition image pair includes a target pre-calibrated visual partition image and a corresponding target pre-calibrated real-time positioning partition image, comprising:

[0099] S1041. When the partition calibration type is detected to be specified area calibration, the target partition parameters are collected;

[0100] S1042. Determine the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image based on the target partition parameters.

[0101] Specifically, the zonal calibration type includes, but is not limited to, specified area calibration or global calibration. Correspondingly, when the zonal calibration command is detected to carry a specified area calibration type, it is determined that only the pre-calibrated visual zonal image and the pre-calibrated real-time positioning zonal image corresponding to the user-specified target area need to be calibrated. This requires determining a target zonal image pair (including a target pre-calibrated visual zonal image and its corresponding target pre-calibrated real-time positioning zonal image). Target zonal parameters corresponding to the target area to be calibrated are collected, and the target pre-calibrated visual zonal image and the target pre-calibrated real-time positioning zonal image are determined based on these parameters. Target zonal parameters include, but are not limited to, the target zonal ID, the GPS positioning information of the calibration point, or the relative position information of the calibration point within a preset area.

[0102] In one embodiment, after segmenting the precalibrated visualization image and the precalibrated instantaneous localization image using segmentation parameters, a partition ID needs to be assigned to each precalibrated visualization partition image and the corresponding precalibrated instantaneous localization partition image.

[0103] Specifically, when the target partition parameter is detected to be the target partition ID, the corresponding target partition image pair is determined based on the target partition ID.

[0104] like Figure 4 As shown, after segmenting the pre-calibration visualization image and the pre-calibration instantaneous localization image using segmentation parameters, three pre-calibration visualization partition images and three pre-calibration instantaneous localization partition images are obtained. Correspondingly, the partition ID of the first pre-calibration visualization partition image a1 is determined as ID0001, and the partition ID of the first pre-calibration instantaneous localization partition image b1 is ID1001; the partition ID of the second pre-calibration visualization partition image a2 is ID0002, and the partition ID of the second pre-calibration instantaneous localization partition image b2 is ID1002; the partition ID of the third pre-calibration visualization partition image a3 is ID0003, and the partition ID of the third pre-calibration instantaneous localization partition image b3 is ID1003.

[0105] For example, if the target partition ID is ID0001, the corresponding target partition image pair includes the first pre-calibrated visualization partition image and the corresponding first pre-calibrated instantaneous positioning partition image.

[0106] Specifically, when GPS positioning information of the calibration point is detected as the target partition parameter, the location information of the calibration point in the preset area is determined based on the GPS positioning information of the calibration point. Based on the location information, the pre-calibration visualization image and the pre-calibration real-time positioning image of the calibration point are determined as the target pre-calibration visualization partition image and the corresponding target pre-calibration real-time positioning partition image.

[0107] like Figure 5 As shown, when the GPS positioning information of the calibration point determines the leftmost partition of the preset area, the corresponding target partition image pair is the first pre-calibration visualization partition image a1 and the corresponding first pre-calibration instant positioning partition image b1.

[0108] Specifically, when the target partition parameter is detected as the relative position information of the calibration point in the preset area, the partition image where the calibration point is located is determined based on the relative position information, and the corresponding target partition image pair is determined.

[0109] For example, such as Figure 5 As shown, when calibrating the corresponding target pre-calibration instant positioning partition image using the target pre-calibration visualization partition image as the standard target partition image, the user determines the relative position information of two calibration points in the preset area by using the mouse (specifically, by triggering two click events on the target pre-calibration visualization partition image corresponding to the preset area), and determines that the calibration point is located in the first pre-calibration visualization partition image a1. The corresponding target partition image pair is the first pre-calibration visualization partition image a1 and the corresponding first pre-calibration instant positioning partition image b1.

[0110] S1043. Collect at least two first calibration point parameters on the target pre-calibration visualization partition image, and determine at least two second calibration point parameters on the target pre-calibration instant positioning partition image based on the first calibration point parameters.

[0111] Specifically, in the process of controlling an intelligent robot, it is usually necessary to issue control tasks to the intelligent robot based on a user interface (specifically a visual interface) to control the intelligent robot to perform corresponding task operations on the acquired real-time positioning map. Therefore, the target pre-calibration visual partition image is set as the standard target partition image. At least two first calibration point coordinates are collected from at least two first calibration point coordinates sent by the user through the user terminal, at least two first calibration point coordinates input by the user through the input device, or at least two first calibration point coordinates generated by the user touching or sliding on the target pre-calibration visual partition image displayed on the current terminal's display interface, and these are used as first calibration point parameters. Second calibration point coordinates corresponding one-to-one with the above-mentioned first calibration point coordinates are determined on the target pre-calibration real-time positioning partition image to obtain at least two second calibration point parameters.

[0112] S1044. Based on the first calibration point parameter and the second calibration point parameter, calibrate the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image to obtain the calibrated visualization partition image and the calibrated instant positioning partition image; the first calibration point parameter is the coordinate of the first calibration point in the target pre-calibration visualization partition image, and the second calibration point parameter is the coordinate of the second calibration point in the target pre-calibration instant positioning partition image.

[0113] Specifically, by performing coordinate translation, rotation, scaling transformations on each first calibration point parameter and its corresponding second calibration point parameter, a mapping relationship is established between each first calibration point parameter and its corresponding second calibration point parameter. This ensures that each coordinate in the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image forms a corresponding basic mapping relationship, resulting in the calibrated visualization partition image and the calibrated instant positioning partition image.

[0114] In one embodiment, the step of collecting corresponding calibration point parameters according to the partition calibration type, calibrating the target partition image pair based on the calibration point parameters, and obtaining a calibrated visual partition image and a calibrated real-time positioning partition image; the target partition image pair includes a target pre-calibrated visual partition image and a corresponding target pre-calibrated real-time positioning partition image, and further includes:

[0115] S1045. When it is detected that the partition calibration type is global calibration, each pre-calibration visualization partition image is traversed as the target pre-calibration visualization partition image; the pre-calibration instant positioning partition image corresponding to the target pre-calibration visualization partition image is taken as the target pre-calibration instant positioning partition image.

[0116] Specifically, when it is detected that the partition calibration type carried by the partition calibration command is global calibration, it is determined that each pre-calibrated visualization partition image and its corresponding pre-calibrated instantaneous positioning partition image need to be calibrated. Each pre-calibrated visualization partition image is then used as the target pre-calibrated visualization partition image, and the pre-calibrated instantaneous positioning partition image corresponding to the aforementioned target pre-calibrated visualization partition image is used as the target pre-calibrated instantaneous positioning partition image.

[0117] For example, such as Figure 5 As shown, firstly, the pre-calibration visualization partition image a1 is used as the target pre-calibration visualization partition image, and correspondingly, the pre-calibration instantaneous positioning partition image b1 is used as the target pre-calibration instantaneous positioning partition image. Partition calibration operations are then performed on both pre-calibration visualization partition image a1 and pre-calibration instantaneous positioning partition image b1. After completing the partition calibration operations on pre-calibration visualization partition image a1 and pre-calibration instantaneous positioning partition image b1, the pre-calibration visualization partition image a2 is used as the target pre-calibration visualization partition image, and correspondingly, the pre-calibration instantaneous positioning partition image b2 is used as the target pre-calibration instantaneous positioning partition image. Then, partition calibration operations are performed on both pre-calibration visualization partition image a2 and pre-calibration instantaneous positioning image b2, and so on.

[0118] S1046. Collect at least two third calibration point parameters on each target pre-calibration visualization partition image, and determine at least two fourth calibration point parameters on the target pre-calibration instant positioning partition image based on the third calibration point parameters; the third calibration point parameters are the coordinates of the third calibration point in the target pre-calibration visualization partition image, and the fourth calibration point parameters are the coordinates of the fourth calibration point in the target pre-calibration instant positioning partition image.

[0119] Specifically, at least two calibration point coordinates sent by the user through the user terminal, at least two calibration point coordinates input by the user through the input device, or at least two calibration point coordinates generated by the user touching or sliding within the target pre-calibration visualization partition image displayed on the current terminal's display interface are collected as the corresponding third calibration point parameters; a fourth calibration point corresponding to each of the above third calibration points is determined in the target pre-calibration instant positioning partition image, and its coordinates within the target pre-calibration instant positioning partition image are used as the corresponding fourth calibration point parameters.

[0120] S1047. The target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image are calibrated according to the third calibration point parameters and the fourth calibration point parameters to obtain the calibrated visualization partition image and the calibrated instant positioning partition image.

[0121] Specifically, by performing coordinate transformations such as translation, rotation, and scaling on each third calibration point parameter and its corresponding fourth calibration point parameter, a mapping relationship is established between each third calibration point parameter and its corresponding fourth calibration point parameter. This ensures that each coordinate in the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image forms a corresponding basic mapping relationship, resulting in the calibrated visualization partition image and the calibrated instant positioning partition image. After traversing and completing the partition calibration for each target pre-calibration visualization partition image and its corresponding target pre-calibration instant positioning partition image, the calibrated visualization partition image and the calibrated instant positioning partition image are obtained.

[0122] In one embodiment, calibrating the target pre-calibration visualization partition image and the target pre-calibration instantaneous positioning partition image according to the third calibration point parameters and the fourth calibration point parameters to obtain the calibrated visualization partition image and the calibrated instantaneous positioning partition image includes:

[0123] Perform coordinate transformation on each of the third calibration point parameters and the corresponding fourth calibration point parameters to obtain the coordinate mapping relationship between each of the third calibration point parameters and the corresponding fourth calibration point parameters;

[0124] The calibrated visual partition image and the calibrated real-time positioning partition image are obtained based on the mapping relationship.

[0125] Specifically, based on each third calibration point parameter, the coordinates of the fourth calibration point corresponding to the third calibration point are determined in the target pre-calibration instant positioning partition image. After obtaining the corresponding fourth calibration point parameter, coordinate transformation processing is required for each calibration point parameter pair (each calibration point parameter pair includes a third calibration point parameter and its corresponding fourth calibration point parameter) to obtain the coordinate mapping relationship between each calibration point parameter pair. Based on the above mapping relationship, coordinate transformation processing is performed on all calibration point parameter pairs in the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image to obtain the calibrated target visualization partition image and the calibrated target instant positioning partition image. After traversing and completing the partition calibration for each target pre-calibration visualization partition image and the corresponding target pre-calibration instant positioning partition image, the calibrated visualization partition image and the calibrated instant positioning partition image are obtained.

[0126] For example, three third calibration point parameters (specifically, parameter 1, parameter 2, and parameter 3) are currently collected. Based on these third calibration point parameters, three corresponding fourth calibration point parameters (specifically, parameter 4, parameter 5, and parameter 6) are determined. Parameter 1 and parameter 4 are the coordinates of the same calibration point in the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image, respectively; therefore, parameter 1 and parameter 4 are calibration point parameter pairs. Correspondingly, parameter 2 and parameter 5 are calibration point parameter pairs, and parameter 3 and parameter 6 are calibration point parameter pairs. Therefore, it is necessary to perform a calibration transformation on parameter 1 and parameter 4 to obtain the coordinate mapping relationship between them; perform a calibration transformation on parameter 2 and parameter 5 to obtain the coordinate mapping relationship between them; and perform a calibration transformation on parameter 3 and parameter 6 to obtain the coordinate mapping relationship between them. Based on these three sets of mapping relationships, all coordinate pairs in the current target pre-calibration visualization partition image and the corresponding target pre-calibration instant positioning partition image are transformed to complete the partition calibration operation of the current target pre-calibration visualization partition image and the corresponding target pre-calibration instant positioning partition image.

[0127] In one embodiment, the acquisition of segmentation parameters, and the segmentation of the pre-calibrated visualization image and the pre-calibrated instantaneous localization image according to the segmentation parameters, to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images, including:

[0128] Collect segmentation parameters; the segmentation parameters include at least one starting point coordinate and an ending point coordinate corresponding to each starting point coordinate;

[0129] When the starting point coordinates and the ending point coordinates are detected to be outside the preset area, the number N of the starting point coordinates is determined; where N is a positive integer greater than or equal to 1.

[0130] The pre-calibrated visualization image and the pre-calibrated instantaneous positioning image are segmented based on the starting point coordinates and the ending point coordinates to obtain N+1 pre-calibrated visualization partition images and N+1 pre-calibrated instantaneous positioning partition images.

[0131] Specifically, the segmentation parameters include at least one starting point coordinate and a corresponding ending point coordinate for each starting point coordinate. Correspondingly, the segmentation parameters include at least one dividing line connecting the starting point coordinates and the corresponding ending point coordinates. The starting point coordinates or ending point coordinates are specifically coordinate information sent by the user through a user terminal, input by the user through an input device, or generated by the user touching or swiping on the current terminal's display interface.

[0132] Specifically, when collecting the start and end coordinates, it is necessary to determine whether the start and end coordinates are within the preset area by checking whether they exceed the outer boundary information of the preset area. If both the start and end coordinates are detected to be outside the outer boundary of the preset area, the number N of the currently collected start coordinates is determined. The number N of start coordinates can be understood as the number of dividing lines. N is a positive integer greater than or equal to 1.

[0133] Specifically, the pre-calibration visualization image and the pre-calibration instant positioning image are segmented according to the dividing line formed by connecting the starting point coordinates and the ending point coordinates, resulting in N+1 pre-calibration visualization partition images and N+1 pre-calibration instant positioning partition images.

[0134] like Figure 5 As shown, the segmentation parameters are two dividing lines formed by connecting two starting coordinates and two ending coordinates corresponding to each starting coordinate. After segmenting the pre-calibration visualization image and the pre-calibration instant positioning image based on the above two dividing lines, the corresponding first pre-calibration visualization partition image a1, second pre-calibration visualization partition image a2, and third pre-calibration visualization partition image a3 are obtained; first pre-calibration instant positioning partition image b1, second pre-calibration instant positioning partition image b2, and third pre-calibration instant positioning partition image b3 are obtained.

[0135] In one embodiment, after acquiring the segmentation parameters, the method further includes:

[0136] When any of the starting point coordinates or the ending point coordinates are detected to be within the preset area, a partitioning failure alarm message is generated and displayed.

[0137] Specifically, when a start-point or end-point coordinate in the partitioning parameters is detected to be within the outer boundary of the preset area, it is determined that a dividing line cannot be determined based on the start-point and end-point coordinates. Consequently, the pre-calibrated visualization image and the pre-calibrated real-time positioning image cannot be segmented based on the dividing line. A partitioning failure alarm message is generated and displayed to inform the user that the partitioning operation for the preset area has failed. The partitioning failure alarm message includes, but is not limited to, the detected start-point or end-point coordinates within the outer boundary of the preset area, and a text or voice prompt message indicating "partitioning failed".

[0138] In one embodiment, determining the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image corresponding to the preset region based on the outer boundary information includes:

[0139] S1021. Based on the outer boundary information, obtain the visualization image and real-time positioning image corresponding to the preset area.

[0140] Specifically, based on the outer boundary information of the preset area, the size and location of the preset area are determined, and based on the size, location and outer boundary information of the preset area, a visualization image and a real-time positioning image corresponding to the preset area are obtained.

[0141] For example, if the preset area requiring zoning calibration is a commercial building, the corresponding outer boundary information is the location information of the building's outer boundary, used to describe its shape. Based on this outer boundary information, a visual image and a real-time positioning image of the commercial building are obtained.

[0142] S1022. Collect at least two fifth calibration point parameters on the visualized image, and determine at least two sixth calibration point parameters on the instantaneous positioning image based on the fifth calibration point parameters.

[0143] Specifically, at least two fifth calibration point coordinates are collected from the user through the user terminal, at least two fifth calibration point coordinates are input by the user through the input device, or at least two fifth calibration point coordinates are generated by the user by touching or sliding the visual image displayed on the current terminal's display interface, and these are used as fifth calibration point parameters; correspondingly, the sixth calibration point coordinates corresponding to each of the above fifth calibration point coordinates are determined on the real-time positioning image to obtain the sixth calibration point parameter.

[0144] S1023. The visualization image and the instant positioning image are calibrated according to each of the fifth calibration point parameters and the corresponding sixth calibration point parameters to obtain the pre-calibrated visualization image and the pre-calibrated instant positioning image.

[0145] Specifically, coordinate transformation is required for each fifth calibration point parameter and its corresponding sixth calibration point parameter to obtain the coordinate mapping relationship between them. Based on this mapping relationship, all coordinate pairs in the visualization image and the real-time positioning image are transformed to obtain the pre-calibrated visualization image and the pre-calibrated real-time positioning image.

[0146] By pre-calibrating the original visualization image and the real-time positioning image, the two images based on the same preset area have a certain initial mapping relationship. Based on the initial mapping relationship, the pre-calibrated visualization image and the pre-calibrated real-time positioning image are subjected to partition calibration, thereby improving the calibration accuracy and efficiency of partition calibration of the real-time positioning image.

[0147] This embodiment, upon receiving a partition calibration command, parses the partition calibration parameters, determines a pre-calibrated visual image and a pre-calibrated real-time positioning image corresponding to a preset region based on outer boundary information, collects segmentation parameters, and segments the pre-calibrated visual image and the pre-calibrated real-time positioning image to obtain at least two pre-calibrated visual partition images and at least two pre-calibrated real-time positioning partition images. According to the partition calibration type, corresponding calibration point parameters are collected, and the target partition image pair is calibrated based on the calibration point parameters to obtain calibrated visual partition images and real-time positioning partition images. By segmenting the pre-calibrated visual image and real-time positioning image, and then further calibrating the partition image based on the calibration points, the accuracy of the real-time positioning image is improved, thereby improving the control accuracy of robot control based on the visual image.

[0148] It should be understood that the sequence number of each step in the above embodiments does not imply 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 this application.

[0149] Corresponding to the canvas-based map calibration method described in the above embodiments, Figure 5 The diagram shows a structural block diagram of a canvas-based map calibration device provided in an embodiment of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0150] Reference Figure 5 The canvas-based map calibration device 100 includes:

[0151] The instruction parsing module 101 is used to parse the partition calibration parameters carried by the partition calibration instruction when a partition calibration instruction is received; wherein, the partition calibration parameters include the outer boundary information of the preset area and the partition calibration type;

[0152] Image acquisition module 102 is used to determine a pre-calibrated visualization image and a pre-calibrated real-time positioning image corresponding to the preset area based on the outer boundary information; the pre-calibrated visualization image is a visualization image that has undergone pre-calibration processing; the pre-calibrated real-time positioning image is a real-time positioning image that has undergone pre-calibration processing.

[0153] The image segmentation module 103 is used to collect segmentation parameters and segment the pre-calibrated visualization image and the pre-calibrated instantaneous localization image according to the segmentation parameters to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images.

[0154] The partition calibration module 104 is used to collect corresponding calibration point parameters according to the partition calibration type, and calibrate the target partition image pair based on the calibration point parameters to obtain the calibrated visual partition image and the calibrated real-time positioning partition image; the target partition image pair includes the target pre-calibrated visual partition image and the corresponding target pre-calibrated real-time positioning partition image.

[0155] In one embodiment, the partition calibration module includes:

[0156] The partition parameter acquisition unit is used to acquire target partition parameters when the partition calibration type is detected to be specified area calibration;

[0157] The target partitioning determination unit is used to determine the target pre-calibration visualization partitioning image and the target pre-calibration instant positioning partitioning image based on the target partitioning parameters.

[0158] The calibration point parameter acquisition unit is used to acquire at least two first calibration point parameters on the target pre-calibration visualization partition image, and determine at least two second calibration point parameters on the target pre-calibration instant positioning partition image based on the first calibration point parameters.

[0159] The first calibration unit is used to calibrate the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image according to the first calibration point parameter and the second calibration point parameter, so as to obtain the calibrated visualization partition image and the calibrated instant positioning partition image; the first calibration point parameter is the coordinate of the first calibration point in the target pre-calibration visualization partition image, and the second calibration point parameter is the coordinate of the second calibration point in the target pre-calibration instant positioning partition image.

[0160] In one embodiment, the partition calibration module further includes:

[0161] The partition image traversal unit is used to, when the partition calibration type is detected to be global calibration, traverse each pre-calibration visualization partition image as a target pre-calibration visualization partition image; and use the pre-calibration instant positioning partition image corresponding to the target pre-calibration visualization partition image as the target pre-calibration instant positioning partition image.

[0162] The calibration point parameter determination unit is used to collect at least two third calibration point parameters on each target pre-calibration visualization partition image, and determine at least two fourth calibration point parameters on the target pre-calibration instant positioning partition image based on the third calibration point parameters; the third calibration point parameters are the coordinates of the third calibration point in the target pre-calibration visualization partition image, and the fourth calibration point parameters are the coordinates of the fourth calibration point in the target pre-calibration instant positioning partition image.

[0163] The second calibration unit is used to calibrate the target pre-calibrated visualization partition image and the target pre-calibrated instantaneous positioning partition image according to the third calibration point parameters and the fourth calibration point parameters, so as to obtain the calibrated visualization partition image and the calibrated instantaneous positioning partition image.

[0164] In one embodiment, the second calibration unit includes:

[0165] The coordinate transformation unit is used to perform coordinate transformation processing on each of the third calibration point parameters and the corresponding fourth calibration point parameters to obtain the coordinate mapping relationship between each of the third calibration point parameters and the corresponding fourth calibration point parameters;

[0166] The coordinate mapping unit is used to obtain the calibrated visual partition image and the calibrated real-time positioning partition image based on the mapping relationship.

[0167] In one embodiment, the image segmentation module includes:

[0168] A segmentation parameter acquisition unit is used to acquire segmentation parameters; the segmentation parameters include at least one starting point coordinate and an ending point coordinate corresponding to each starting point coordinate.

[0169] A quantity determination unit is used to determine the quantity N of the starting point coordinates when the starting point coordinates and the ending point coordinates are detected to be outside the preset area; wherein N is a positive integer greater than or equal to 1;

[0170] The image segmentation unit is used to segment the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image according to the starting point coordinates and the ending point coordinates, to obtain N+1 pre-calibrated visualization partition images and N+1 pre-calibrated instantaneous positioning partition images.

[0171] In one embodiment, the image segmentation module further includes:

[0172] The alarm unit is used to generate and display partitioning failure alarm information when it detects that any of the starting point coordinates or the ending point coordinates are within the preset area.

[0173] In one embodiment, the image acquisition module includes:

[0174] The image acquisition unit is used to acquire a visual image and a real-time positioning image corresponding to the preset area based on the outer boundary information;

[0175] A pre-calibration parameter acquisition unit is used to acquire at least two fifth calibration point parameters on the visualization image and determine at least two sixth calibration point parameters on the instantaneous positioning image based on the fifth calibration point parameters.

[0176] The pre-calibration unit is used to calibrate the visualization image and the instantaneous positioning image according to each of the fifth calibration point parameters and the corresponding sixth calibration point parameters, so as to obtain the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image.

[0177] This embodiment, upon receiving a partition calibration command, parses the partition calibration parameters, determines a pre-calibrated visual image and a pre-calibrated real-time positioning image corresponding to a preset region based on outer boundary information, collects segmentation parameters, and segments the pre-calibrated visual image and the pre-calibrated real-time positioning image to obtain at least two pre-calibrated visual partition images and at least two pre-calibrated real-time positioning partition images. According to the partition calibration type, corresponding calibration point parameters are collected, and the target partition image pair is calibrated based on the calibration point parameters to obtain calibrated visual partition images and real-time positioning partition images. By segmenting the pre-calibrated visual image and real-time positioning image, and then further calibrating the partition image based on the calibration points, the accuracy of the real-time positioning image is improved, thereby improving the control accuracy of robot control based on the visual image.

[0178] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0179] Figure 7 This is a schematic diagram of the structure of the terminal device provided in this embodiment. Figure 7 As shown, the terminal device 7 of this embodiment includes: at least one processor 70 ( Figure 7 (Only one is shown in the diagram), memory 71, and computer program 72 stored in said memory 71 and executable on said at least one processor 70, which, when executed by said processor 70, implements the steps in any of the above embodiments of the canvas-based map calibration method.

[0180] The terminal device 7 can be a desktop computer, laptop, handheld computer, or cloud server, etc. This terminal device may include, but is not limited to, a processor 70 and a memory 71. Those skilled in the art will understand that... Figure 7 The example of terminal device 7 is merely an illustration and does not constitute a limitation on terminal device 7. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0181] The processor 70 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0182] In some embodiments, the memory 71 may be an internal storage unit of the terminal device 7, such as a hard disk or memory of the terminal device 7. In other embodiments, the memory 71 may be an external storage device of the terminal device 7, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 7. Furthermore, the memory 71 may include both internal and external storage units of the terminal device 7. The memory 71 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 71 can also be used to temporarily store data that has been output or will be output.

[0183] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0184] This application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the steps in any of the above method embodiments.

[0185] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0186] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0187] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0188] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0189] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0190] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0191] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0192] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A canvas-based map calibration method, characterized in that, include: Upon receiving a partition calibration command, the partition calibration parameters carried by the command are parsed and obtained; wherein, the partition calibration parameters include the outer boundary information of the preset area and the partition calibration type, and the partition calibration type includes specified area calibration and global calibration; Based on the outer boundary information, a pre-calibrated visualization image and a pre-calibrated real-time positioning image corresponding to the preset region are determined; the pre-calibrated visualization image is a visualization image that has undergone pre-calibration processing; the pre-calibrated real-time positioning image is a real-time positioning image that has undergone pre-calibration processing. Collect segmentation parameters, and segment the pre-calibrated visualization image and the pre-calibrated instantaneous localization image according to the segmentation parameters to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images; According to the partition calibration type, the corresponding calibration point parameters are collected, and the target partition image pair is calibrated based on the calibration point parameters to obtain the calibrated visual partition image and the calibrated real-time positioning partition image; the target partition image pair includes the target pre-calibrated visual partition image and the corresponding target pre-calibrated real-time positioning partition image.

2. The canvas-based map calibration method as described in claim 1, characterized in that, The step of collecting corresponding calibration point parameters according to the partition calibration type, calibrating the target partition image pair based on the calibration point parameters, and obtaining the calibrated visual partition image and the calibrated real-time positioning partition image includes: When the partition calibration type is detected to be specified area calibration, the target partition parameters are collected; The target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image are determined based on the target partition parameters. Collect at least two first calibration point parameters on the target pre-calibration visualization partition image, and determine at least two second calibration point parameters on the target pre-calibration instant positioning partition image based on the first calibration point parameters; Based on the first calibration point parameter and the second calibration point parameter, the target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image are calibrated to obtain the calibrated visualization partition image and the calibrated instant positioning partition image; the first calibration point parameter is the coordinate of the first calibration point in the target pre-calibration visualization partition image, and the second calibration point parameter is the coordinate of the second calibration point in the target pre-calibration instant positioning partition image.

3. The canvas-based map calibration method as described in claim 2, characterized in that, The step of collecting corresponding calibration point parameters according to the partition calibration type, calibrating the target partition image pair based on the calibration point parameters, and obtaining the calibrated visual partition image and the calibrated real-time positioning partition image further includes: When the partition calibration type is detected to be global calibration, each pre-calibration visualization partition image is traversed and used as the target pre-calibration visualization partition image; the pre-calibration instant positioning partition image corresponding to the target pre-calibration visualization partition image is used as the target pre-calibration instant positioning partition image. At least two third calibration point parameters are acquired on each target pre-calibration visualization partition image, and at least two fourth calibration point parameters are determined on the target pre-calibration instant positioning partition image based on the third calibration point parameters; the third calibration point parameters are the coordinates of the third calibration point in the target pre-calibration visualization partition image, and the fourth calibration point parameters are the coordinates of the fourth calibration point in the target pre-calibration instant positioning partition image. The target pre-calibration visualization partition image and the target pre-calibration instant positioning partition image are calibrated according to the third calibration point parameters and the fourth calibration point parameters to obtain the calibrated visualization partition image and the calibrated instant positioning partition image.

4. The canvas-based map calibration method as described in claim 3, characterized in that, The step of calibrating the target pre-calibration visualization partition image and the target pre-calibration instantaneous positioning partition image according to the third calibration point parameters and the fourth calibration point parameters to obtain the calibrated visualization partition image and the calibrated instantaneous positioning partition image includes: Perform coordinate transformation on each of the third calibration point parameters and the corresponding fourth calibration point parameters to obtain the coordinate mapping relationship between each of the third calibration point parameters and the corresponding fourth calibration point parameters; The calibrated visual partition image and the calibrated real-time positioning partition image are obtained based on the mapping relationship.

5. The canvas-based map calibration method as described in claim 1, characterized in that, The acquisition segmentation parameters are used to segment the pre-calibrated visualization image and the pre-calibrated instantaneous localization image, resulting in at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images, including: Collect segmentation parameters; the segmentation parameters include at least one starting point coordinate and an ending point coordinate corresponding to each starting point coordinate; When the starting point coordinates and the ending point coordinates are detected to be outside the preset area, the number N of the starting point coordinates is determined; where N is a positive integer greater than or equal to 1. The pre-calibrated visualization image and the pre-calibrated instantaneous positioning image are segmented according to the starting point coordinates and the ending point coordinates to obtain N+1 pre-calibrated visualization partition images and N+1 pre-calibrated instantaneous positioning partition images.

6. The canvas-based map calibration method as described in claim 5, characterized in that, After acquiring the segmentation parameters, the following is also included: When any of the starting point coordinates or the ending point coordinates are detected to be within the preset area, a partitioning failure alarm message is generated and displayed.

7. The canvas-based map calibration method as described in any one of claims 1 to 6, characterized in that, The step of determining the pre-calibrated visualization image and pre-calibrated real-time positioning image corresponding to the preset region based on the outer boundary information includes: Based on the outer boundary information, obtain a visual image and a real-time positioning image corresponding to the preset area; Collect at least two fifth calibration point parameters on the visualized image, and determine at least two sixth calibration point parameters on the instantaneous positioning image based on the fifth calibration point parameters; The visualization image and the instantaneous positioning image are calibrated according to each of the fifth calibration point parameters and the corresponding sixth calibration point parameters to obtain the pre-calibrated visualization image and the pre-calibrated instantaneous positioning image.

8. A canvas-based map calibration device, characterized in that, include: The instruction parsing module is used to parse the partition calibration parameters carried by the partition calibration instruction when a partition calibration instruction is received; wherein, the partition calibration parameters include the outer boundary information of the preset area and the partition calibration type, and the partition calibration type includes specified area calibration and global calibration; The image acquisition module is used to determine a pre-calibrated visualization image and a pre-calibrated real-time positioning image corresponding to the preset area based on the outer boundary information; the pre-calibrated visualization image is a visualization image that has undergone pre-calibration processing; the pre-calibrated real-time positioning image is a real-time positioning image that has undergone pre-calibration processing. An image segmentation module is used to acquire segmentation parameters and segment the pre-calibrated visualization image and the pre-calibrated instantaneous localization image according to the segmentation parameters to obtain at least two pre-calibrated visualization partition images and at least two pre-calibrated instantaneous localization partition images. The partition calibration module is used to collect corresponding calibration point parameters according to the partition calibration type, and calibrate the target partition image pair based on the calibration point parameters to obtain the calibrated visual partition image and the calibrated real-time positioning partition image; the target partition image pair includes the target pre-calibrated visual partition image and the corresponding target pre-calibrated real-time positioning partition image.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 7.

Images