Point cloud data calibration method, device, computer equipment and storage medium

Abstract

The present application relates to a point cloud data calibration method, device, computer equipment and storage medium. The method comprises: in response to a data calibration trigger operation, displaying a point cloud data pre-calibration result in a calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on a calibration algorithm; in a calibration adjustment area associated with the calibration result area, displaying a calibration adjustment operation item for adjusting the point cloud data pre-calibration result; in response to a calibration adjustment operation triggered by the calibration adjustment operation item, displaying a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation. The use of this method can improve the processing efficiency of point cloud data calibration.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a point cloud data calibration method, device, computer equipment and storage medium. Background Art

[0002] With the development of computer technology, the era of intelligent driving has arrived. Intelligent driving is an important starting point for the combination of industrial revolution and informatization. Its rapid development will change the flow of people, resource elements and products, and subversively change human life. Intelligent driving, and even unmanned driving, have very high requirements for the accuracy of the results of each sensor. It is necessary to obtain high-precision sensor data for environmental detection in order to make corresponding decisions, especially as one of the main sensors, which is used to detect the surrounding environment and output point cloud data.

[0003] The distribution of LiDAR and other sensors in the intelligent driving system is different. Point cloud data needs to be calibrated to determine the relative positions of each sensor so that various sensor data can be effectively integrated to make driving decisions. Currently, point cloud data is often calibrated through manual measurement or algorithm iteration, resulting in low efficiency in point cloud data calibration. Summary of the invention

[0004] Based on this, it is necessary to provide a point cloud data calibration method, device, computer equipment and storage medium that can improve the efficiency of point cloud data calibration processing in response to the above technical problems.

[0005] A point cloud data calibration method, the method comprising:

[0006] In response to the data calibration trigger operation, the point cloud data pre-calibration result is displayed in the calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm;

[0007] In the calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the pre-calibration results of the point cloud data are displayed;

[0008] In response to a calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed.

[0009] In one embodiment, in response to a data calibration trigger operation, a point cloud data pre-calibration result is displayed in a calibration result area, including:

[0010] In response to a point cloud data import trigger operation, displaying a point cloud data import operation item;

[0011] In response to the data import operation triggered by the point cloud data import operation item, displaying the data import result of the point cloud data to be calibrated;

[0012] In response to a data calibration trigger operation triggered by a data import result, a point cloud data pre-calibration result is displayed in a calibration result area.

[0013] In one embodiment, the point cloud data pre-calibration result is displayed in the calibration result area, including:

[0014] In the calibration result area, the data distribution information corresponding to the point cloud data to be calibrated is displayed in different display modes.

[0015] In one embodiment, the point cloud data pre-calibration result is obtained by a point cloud data calibration processing step, and the point cloud data calibration processing step includes:

[0016] Obtain the point cloud data to be calibrated;

[0017] The point cloud data to be calibrated is calibrated based on a preset calibration algorithm to obtain a pre-calibration result of the point cloud data corresponding to the point cloud data to be calibrated.

[0018] In one embodiment, the calibration adjustment operation item includes at least a rotation operation item and a translation operation item; in response to the calibration adjustment operation triggered by the calibration adjustment operation item, the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed, including:

[0019] In response to a rotation operation triggered on the rotation operation item, a rotation adjustment result obtained by performing rotation processing on the pre-calibration result of the point cloud data is displayed in the calibration result area;

[0020] In response to the translation operation triggered by the translation operation item, the calibration result of the point cloud data obtained by performing translation processing on the rotation adjustment result is displayed in the calibration result area.

[0021] In one embodiment, the point cloud data calibration method further includes:

[0022] Determine a rotation adjustment parameter corresponding to the rotation operation and a translation adjustment parameter corresponding to the translation operation;

[0023] The pre-calibration result of the point cloud data is rotated according to the rotation adjustment parameter to obtain a rotation adjustment result;

[0024] The rotation adjustment result is translated according to the translation adjustment parameter to obtain the point cloud data calibration result.

[0025] In one embodiment, the point cloud data calibration method further includes:

[0026] In the calibration adjustment operation item, the default adjustment parameters are displayed; the default adjustment parameters are obtained by adjusting and analyzing the pre-calibration results of the point cloud data;

[0027] In response to a calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained by adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed, including:

[0028] In response to an adjustment confirmation operation on the calibration adjustment operation item, a point cloud data calibration result obtained by adjusting the point cloud data pre-calibration result by using default adjustment parameters is displayed.

[0029] A point cloud data calibration device, the device comprising:

[0030] The data calibration module is used to display the point cloud data pre-calibration result in the calibration result area in response to the data calibration trigger operation; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm;

[0031] An adjustment operation item display module is used to display calibration adjustment operation items for adjusting the pre-calibration results of the point cloud data in a calibration adjustment area associated with the calibration result area;

[0032] The calibration adjustment module is used to respond to the calibration adjustment operation triggered by the calibration adjustment operation item, and display the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation.

[0033] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0034] In response to the data calibration trigger operation, the point cloud data pre-calibration result is displayed in the calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm;

[0035] In the calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the pre-calibration results of the point cloud data are displayed;

[0036] In response to a calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed.

[0037] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0038] In response to the data calibration trigger operation, the point cloud data pre-calibration result is displayed in the calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm;

[0039] In the calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the pre-calibration results of the point cloud data are displayed;

[0040] In response to a calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed.

[0041] The above-mentioned point cloud data calibration method, apparatus, computer equipment and storage medium, in response to a data calibration trigger operation, display the point cloud data pre-calibration result obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm in the calibration result area, and in response to a calibration adjustment operation triggered by a calibration adjustment operation item in a calibration adjustment area associated with the calibration result area, display the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation, thereby realizing the calibration processing of the point cloud data. In the process of point cloud data calibration, the point cloud data pre-calibration result obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm is immediately displayed in the calibration result area, and the point cloud data pre-calibration result is adjusted in response to the calibration adjustment operation, and the point cloud data calibration result is displayed, which can provide real-time feedback on the calibration result in the point cloud data calibration process, which is conducive to adjusting the calibration result and improving the processing efficiency of point cloud data calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A diagram of an application environment of a point cloud data calibration method in one embodiment;

[0043] Figure 2 is a schematic diagram of a process of a point cloud data calibration method in one embodiment;

[0044] Figure 3 A schematic diagram of an interface of point cloud data pre-calibration results in one embodiment;

[0045] Figure 4 A schematic diagram of a process for displaying a point cloud data pre-calibration result in one embodiment;

[0046] Figure 5 A schematic diagram of an interface of point cloud data pre-calibration results in another embodiment;

[0047] Figure 6 for Figure 6 A schematic diagram of the interface of the point cloud data calibration result in the embodiment shown;

[0048] Figure 7is a structural block diagram of a point cloud data calibration device in one embodiment;

[0049] Figure 8 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] The point cloud data calibration method provided in this application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. In response to the data calibration trigger operation triggered by the user in the point cloud data calibration interface of the terminal 102, the terminal 102 sends the point cloud data to be calibrated to the server 104, and the server 104 calibrates the point cloud data to be calibrated through the calibration algorithm, and returns the obtained point cloud data pre-calibration result to the terminal 102. The terminal 102 displays the point cloud data pre-calibration result in the calibration result area, and responds to the calibration adjustment operation triggered by the user on the calibration adjustment operation item in the calibration adjustment area associated with the calibration result area, and the terminal 102 displays the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation, thereby realizing the calibration processing of the point cloud data. In addition, the point cloud data calibration method can also directly calibrate the point cloud data to be calibrated by the terminal 102 through the calibration algorithm without sending the point cloud data to be calibrated to the server 104, that is, the terminal 102 directly calibrates the point cloud data to be calibrated and displays the pre-calibration results of the point cloud data.

[0052] The terminal 102 may be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0053] In one embodiment, Figure 2 As shown in FIG. 1 , a point cloud data calibration method is provided, which is applied to Figure 1 The terminal in is used as an example to illustrate, including the following steps:

[0054] Step 202, in response to the data calibration trigger operation, displaying the point cloud data pre-calibration result in the calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm.

[0055] Point cloud data refers to a set of vectors in a three-dimensional coordinate system. In addition to geometric positions, some point cloud data also have color information or intensity information. Color information is usually obtained by acquiring color images through a camera, and then the color information of the pixels at the corresponding position is assigned to the corresponding points in the point cloud; intensity information is obtained by the echo intensity collected by the laser scanner receiving device. This intensity information is related to the surface material, roughness, incident angle direction of the target, as well as the emission energy of the instrument and the laser wavelength.

[0056] Point cloud data can be collected by laser radar. Laser radar is a radar system that emits laser beams to detect the position, speed and other characteristic quantities of the target. Laser radar is a high-precision detection sensor that can be used in various high-precision detection demand scenarios, such as unmanned driving. It can detect the surrounding environment in real time and output a 3D point cloud map composed of point cloud data. The working principle of laser radar is to transmit a detection signal (laser beam) to the target, and then compare the received signal reflected from the target (target echo) with the transmitted signal. After appropriate processing, relevant information about the target is obtained, such as target distance, direction, height, speed, attitude, and even shape parameters, so as to detect, track and identify various targets. Laser radar consists of a laser transmitter, an optical receiver, a turntable and an information processing system. The laser converts electrical pulses into light pulses and transmits them. The optical receiver then restores the light pulses reflected from the target into electrical pulses and sends them to the display.

[0057] The data calibration trigger operation is an operation that triggers the calibration processing of the point cloud data to be calibrated, and the point cloud data to be calibrated is the point cloud data that needs to be calibrated. The data calibration trigger operation can be triggered by the user or when the conditions are met. For example, the user can click the calibration trigger control on the point cloud data calibration interface to trigger the data calibration trigger operation, so as to calibrate the point cloud data to be calibrated. For example, when the terminal detects that the point cloud data to be calibrated has been imported and no new data has been imported within a certain period of time, the data calibration trigger operation is triggered. The calibration result area is the area that displays the calibration results of the point cloud data. The point cloud data pre-calibration result is the calibration result obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm. The calibration algorithm is an algorithm for calibrating the point cloud data, such as the least squares method, ICP (Iterative Closest Point) point cloud matching algorithm, etc. The calibration algorithm can be flexibly selected according to actual needs.

[0058] Specifically, the user can import the point cloud data to be calibrated that needs to be calibrated in the terminal. The user triggers the data calibration trigger operation in the terminal. The terminal responds to the data calibration trigger operation and displays the point cloud data pre-calibration result in the calibration result area. In specific implementation, after the user triggers the data calibration trigger operation, the terminal can send the obtained point cloud data to be calibrated to the server, so that the server can calibrate the point cloud data to be calibrated based on the calibration algorithm, obtain the point cloud data pre-calibration result and return the point cloud data pre-calibration result to the terminal. The terminal displays the received point cloud data pre-calibration result in the calibration result area. In a specific application, such as Figure 3 As shown, after the point cloud data to be calibrated in the point cloud data pre-calibration result is calibrated by the calibration algorithm, the point cloud data to be calibrated cannot be completely overlapped, and the calibration accuracy of the point cloud data is limited.

[0059] Step 204 : In the calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the pre-calibration result of the point cloud data are displayed.

[0060] The calibration adjustment area is associated with the calibration result area, and is used to display operation information for adjusting the pre-calibration result of the point cloud data in the calibration result area, which may specifically include calibration adjustment operation items. The calibration adjustment operation items may include various types of operation items for manually adjusting the pre-calibration result of the point cloud data, such as rotation, translation, etc.

[0061] Specifically, the terminal displays calibration adjustment operation items for adjusting the pre-calibration results of the point cloud data in a calibration adjustment area associated with the calibration result area. The user can operate the calibration adjustment operation items to adjust the pre-calibration results of the point cloud data, thereby achieving further calibration processing of the point cloud data.

[0062] Step 206 , in response to the calibration adjustment operation triggered by the calibration adjustment operation item, displaying the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation.

[0063] Among them, the calibration adjustment operation acts on the calibration adjustment operation item, and the calibration adjustment operation is used to operate each operation item of the calibration adjustment operation item to realize the manual adjustment of the point cloud data pre-calibration result. The point cloud data pre-calibration result is the calibration result of the point cloud data obtained after the user adjusts the point cloud data pre-calibration result. Specifically, the user can operate the calibration adjustment operation item displayed by the terminal to trigger the calibration adjustment operation. The terminal responds to the calibration adjustment operation, adjusts the point cloud data pre-calibration result, and displays the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation in the calibration result area. In the specific implementation, the user can adjust the point cloud data pre-calibration result multiple times, and the terminal displays the point cloud data calibration result obtained after the user adjusts in real time. By real-time feedback of the user's adjustment result, it is convenient for the user to fine-tune the calibration result, which can simplify the calibration operation of the point cloud data and improve the processing efficiency of the point cloud data calibration.

[0064] In the above point cloud data calibration method, in response to a data calibration trigger operation, the point cloud data pre-calibration result obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm is displayed in the calibration result area, and in response to a calibration adjustment operation triggered by a calibration adjustment operation item in a calibration adjustment area associated with the calibration result area, the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed, thereby realizing the calibration processing of the point cloud data. In the process of point cloud data calibration, the point cloud data pre-calibration result obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm is immediately displayed in the calibration result area, and the point cloud data pre-calibration result is adjusted in response to the calibration adjustment operation. The point cloud data calibration result is displayed, and the calibration result in the point cloud data calibration process can be fed back in real time, which is conducive to adjusting the calibration result and improving the processing efficiency of point cloud data calibration.

[0065] In one embodiment, Figure 4 As shown, the process of displaying the point cloud data pre-calibration result, that is, in response to the data calibration trigger operation, displaying the point cloud data pre-calibration result in the calibration result area includes:

[0066] Step 402: In response to a point cloud data import trigger operation, a point cloud data import operation item is displayed.

[0067] Among them, the point cloud data import trigger operation is used to trigger the import of point cloud data, which can be specifically an operation triggered by the user on the import control in the point cloud data calibration interface of the terminal. The point cloud data import operation item can be an operation item for importing point cloud data. By operating the point cloud data import operation item, the terminal can determine the point cloud data selected by the user that needs to be calibrated, so as to calibrate the point cloud data to be calibrated. Specifically, the user can trigger the point cloud data import trigger operation in the point cloud data calibration interface of the terminal, and the terminal responds to the point cloud data import trigger operation and displays the point cloud data import operation item.

[0068] Step 404 , in response to the data import operation triggered by the point cloud data import operation item, displaying the data import result of the point cloud data to be calibrated.

[0069] Among them, the data import operation acts on the point cloud data import operation item, which can be triggered by the user to select the point cloud data to be calibrated that needs to be calibrated. The data import result is the import result of the point cloud data to be calibrated that needs to be calibrated, such as data import success, data import failure, etc. Only when the data import result is data import success, can the subsequent calibration process be further performed on the successfully imported point cloud data to be calibrated. Specifically, the user operates on the point cloud data import operation item to trigger the data import operation. For example, the user selects the corresponding path to import the point cloud data to be calibrated, and the terminal displays the data import result corresponding to the point cloud data to be calibrated.

[0070] Step 406 , in response to the data calibration triggering operation triggered by the data import result, the point cloud data pre-calibration result is displayed in the calibration result area.

[0071] The data calibration trigger operation is a calibration processing operation triggered by the user for the successfully imported point cloud data to be calibrated in the data import result. Specifically, after displaying the data import result of the imported point cloud data to be calibrated, the user further triggers the data calibration trigger operation to trigger the calibration processing of the successfully imported point cloud data to be calibrated, and displays the pre-calibration result of the point cloud data after the calibration algorithm is used to calibrate the point cloud data to be calibrated in the calibration result area.

[0072] In this embodiment, a point cloud data import operation item is displayed according to a point cloud data import trigger operation triggered by the user, and according to the user's data import operation on the point cloud data import operation item, the data of the point cloud data to be calibrated selected by the user is imported, and the data import result is displayed. The terminal responds to the data calibration trigger operation triggered by the user, calibrates the point cloud data to be calibrated, and displays the point cloud data pre-calibration result in the calibration result area, thereby providing real-time feedback on the results of the point cloud data calibration process, facilitating users to perform targeted processing, simplifying the calibration process of point cloud data, and helping to improve the calibration processing efficiency of point cloud data.

[0073] In one embodiment, displaying the pre-calibration result of the point cloud data in the calibration result area includes: displaying data distribution information corresponding to the point cloud data to be calibrated in different display modes in the calibration result area.

[0074] The display mode can be flexibly set according to actual needs, such as different colors, different shapes, different marking symbols, etc. The data distribution information is the position distribution information of each point cloud data in the point cloud data to be calibrated. When the position distribution of each point cloud data in the point cloud data to be calibrated can correspond one to one, accurate calibration of the point cloud data is achieved.

[0075] Specifically, when displaying the pre-calibration results of the point cloud data, the terminal displays the data distribution information corresponding to the point cloud data to be calibrated in different display modes in the calibration result area. For example, the point cloud data to be calibrated includes the first point cloud data to be calibrated and the second point cloud data to be calibrated. During calibration, the point cloud data at each position in the first point cloud data to be calibrated and the second point cloud data to be calibrated need to be matched one-to-one. When an accurate one-to-one correspondence is achieved, the accurate calibration of the point cloud data is achieved. In the calibration result area, the first point cloud data to be calibrated and the second point cloud data to be calibrated can be displayed in different colors, so that the data distribution information of each point cloud data in the first point cloud data to be calibrated and the second point cloud data to be calibrated can be displayed in different colors in the calibration result area, so that the point cloud data pre-calibration results of the point cloud data to be calibrated can be intuitively displayed, which is convenient for users to determine the accuracy of the point cloud data pre-calibration results, so as to make corresponding adjustments and improve the calibration processing efficiency of the point cloud data.

[0076] In one embodiment, the point cloud data pre-calibration result is obtained through the point cloud data calibration processing step, and the point cloud data calibration processing step includes: acquiring the point cloud data to be calibrated; calibrating the point cloud data to be calibrated based on a preset calibration algorithm to obtain the point cloud data pre-calibration result corresponding to the point cloud data to be calibrated.

[0077] Specifically, the point cloud data pre-calibration result displayed by the terminal in the calibration result area is obtained through the point cloud data calibration processing step, and the point cloud data calibration processing step can be implemented by the terminal or by the server. When the point cloud data calibration processing step is implemented by the terminal, after the terminal determines the point cloud data to be calibrated, the terminal directly calibrates the point cloud data to be calibrated and displays the obtained point cloud data pre-calibration result. When the point cloud data calibration processing step is implemented by the server, the terminal can send the point cloud data to be calibrated to the server after obtaining the point cloud data to be calibrated, so that the server can calibrate the point cloud data to be calibrated and return the obtained point cloud data pre-calibration result to the terminal, and the terminal displays the received point cloud data pre-calibration result in the calibration result area.

[0078] Specifically, when executing the step of point cloud data calibration processing, the terminal obtains the point cloud data to be calibrated, such as obtaining the point cloud data to be calibrated according to the path of the point cloud data to be calibrated, and calibrates the point cloud data to be calibrated based on a preset calibration algorithm to obtain a point cloud data pre-calibration result corresponding to the point cloud data to be calibrated. The calibration algorithm can be pre-set according to actual needs.

[0079] In this embodiment, the point cloud data to be calibrated is calibrated through the step of point cloud data calibration processing. The point cloud data to be calibrated can be pre-calibrated using a calibration algorithm to avoid manual measurement, thereby improving the processing efficiency of the point cloud data calibration.

[0080] In one embodiment, the calibration adjustment operation items include at least a rotation operation item and a translation operation item; in response to the calibration adjustment operation triggered by the calibration adjustment operation item, the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed, including: in response to the rotation operation triggered by the rotation operation item, the rotation adjustment result obtained after rotating the point cloud data pre-calibration result is displayed in the calibration result area; in response to the translation operation triggered by the translation operation item, the point cloud data calibration result obtained after translating the rotation adjustment result is displayed in the calibration result area.

[0081] The calibration adjustment operation items at least include a rotation operation item and a translation operation item. The rotation operation item is an operation item for selecting and processing the pre-calibration result of the point cloud data, and the translation operation item is an operation item for translating the pre-calibration result of the point cloud data.

[0082] Specifically, the user triggers a rotation operation on the rotation operation item in the calibration adjustment operation item, such as setting the rotation angle, rotation direction, etc. The terminal responds to the rotation operation, performs rotation processing on the pre-calibration result of the point cloud data, and displays the obtained rotation adjustment result in the calibration result area. Furthermore, the user triggers a translation operation on the translation operation item in the calibration adjustment operation item, such as setting the translation direction, translation angle, etc. The terminal responds to the translation operation, performs translation processing on the rotation adjustment result, and displays the obtained point cloud data calibration result in the calibration result area. In the specific implementation, there is no order relationship between the rotation operation and the translation operation, that is, the user can also first perform the translation operation triggered by the translation operation item, and then perform rotation processing on the translation adjustment result after the translation processing according to the rotation operation to obtain the point cloud data calibration result.

[0083] In this embodiment, the user can adjust the pre-calibration results of the point cloud data by performing a rotation operation triggered by a rotation operation item and a translation operation triggered by a translation operation item, thereby fine-tuning the pre-calibration results obtained based on the calibration algorithm according to user needs and avoiding iteration through the algorithm. This improves the calibration processing efficiency while also improving the accuracy of the calibration.

[0084] In one embodiment, the point cloud data calibration method also includes: determining rotation adjustment parameters corresponding to the rotation operation and translation adjustment parameters corresponding to the translation operation; rotating the point cloud data pre-calibration result according to the rotation adjustment parameters to obtain a rotation adjustment result; translating the rotation adjustment result according to the translation adjustment parameters to obtain a point cloud data calibration result.

[0085] Among them, the rotation adjustment parameters are parameters obtained according to the rotation operation, such as the rotation direction, rotation angle, etc.; the translation adjustment parameters are parameters obtained according to the translation operation, such as the translation direction, translation angle, etc. The specific values ​​of the rotation adjustment parameters and the translation adjustment parameters can be set directly by the user, or determined according to the trajectory of the rotation operation and the translation operation triggered by the user in the interface, such as determining the translation adjustment parameters according to the translation trajectory of the user in the interface. Specifically, after the user triggers the rotation operation and the translation operation, the terminal determines the rotation adjustment parameters corresponding to the rotation operation and the translation adjustment parameters corresponding to the translation operation, rotates the point cloud data pre-calibration results according to the rotation adjustment parameters, obtains the rotation adjustment results, and displays them on the terminal. Furthermore, the rotation adjustment results are translated according to the translation adjustment parameters to obtain the point cloud data calibration results, and displayed on the terminal.

[0086] In this embodiment, the pre-calibration results of the point cloud data are adjusted according to the rotation adjustment parameters corresponding to the rotation operation and the translation adjustment parameters corresponding to the translation operation, so that the pre-calibration results obtained based on the calibration algorithm are fine-tuned according to user needs to avoid iteration through the algorithm. While improving the calibration processing efficiency, the accuracy of the calibration is also improved.

[0087] In one embodiment, the point cloud data calibration method further includes: displaying default adjustment parameters in the calibration adjustment operation item; the default adjustment parameters are obtained by adjusting and analyzing the point cloud data pre-calibration results.

[0088] The default adjustment parameters are adjustment parameters obtained by adjusting and analyzing the point cloud data pre-calibration results, and may specifically include rotation default adjustment parameters and translation default adjustment parameters. The default adjustment parameters are obtained by adjusting and analyzing the point cloud data pre-calibration results, and specifically, the terminal or server may analyze the data distribution information of each point cloud data in the point cloud data pre-calibration results to generate the default adjustment parameters for the user to manually adjust.

[0089] Furthermore, in response to a calibration adjustment operation triggered by a calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed, including: in response to an adjustment confirmation operation of the calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through default adjustment parameters is displayed.

[0090] Among them, the adjustment confirmation operation acts on the calibration adjustment operation item, and is used to adjust and confirm the default adjustment parameters. After the user triggers the calibration adjustment operation for the calibration adjustment operation item, the terminal adjusts the point cloud data pre-calibration result according to the default adjustment parameters to obtain the point cloud data calibration result, thereby realizing the adjustment of the point cloud data pre-calibration result. Specifically, in the calibration adjustment operation item of the terminal, the default adjustment parameters obtained by adjusting and analyzing the point cloud data pre-calibration result are displayed. The user triggers the adjustment confirmation operation for the calibration adjustment operation item, and the terminal responds to the adjustment confirmation operation to display the obtained point cloud data calibration result, which is obtained by adjusting the point cloud data pre-calibration result through the default adjustment parameters.

[0091] In this embodiment, default adjustment parameters are obtained by adjusting and analyzing the point cloud data pre-calibration results. After the user triggers the adjustment confirmation operation, the point cloud data calibration results obtained by adjusting the point cloud data pre-calibration results through the default adjustment parameters are displayed, thereby further reducing the user's manual participation, simplifying the processing flow of point cloud data calibration, and improving the processing efficiency of point cloud data calibration.

[0092] In one embodiment, the point cloud data calibration method provided by the present application is applied to the point cloud data of the laser radar in the field of unmanned driving and the inertial navigation module. Laser radar is a high-precision detection sensor, commonly used in the field of unmanned driving, used to detect the surrounding environment in real time and output a 3D point cloud map. The inertial navigation module is a high-precision positioning sensor, commonly used in the field of unmanned driving, and outputs real-time position and posture information. Calibration in the field of unmanned driving or robots refers to the process of obtaining the relative positions between each sensor through a series of methods or calculations. The unmanned driving system has very high requirements on the accuracy of the results of each sensor, especially the laser radar as one of the main sensors, and the results (point cloud data) output by the laser radar are based on itself as the origin. Since the unmanned driving system is a complex multi-sensor system, it is necessary to accurately transform the results of all sensors into a unified coordinate system, usually the coordinate system of the inertial navigation module, that is, to calibrate the point cloud data of the laser radar.

[0093] At present, for the calibration of the laser radar point cloud data and the inertial navigation module, manual measurement is generally used to determine the calibration relationship between the laser radar and the inertial navigation module, but the accuracy of manual measurement is limited and the efficiency is low, which cannot meet the accuracy requirements of the unmanned driving system. In addition, the calibration results can be directly obtained by collecting data from a specific route and using relevant calibration algorithms, but the implementation cost is high and the results are unstable. It is necessary to collect data from a specific route, which takes a long time. In addition, if the inertial navigation device has signal fluctuations during the journey, it will also affect the final result, resulting in low efficiency of the calibration process. The point cloud data calibration method provided in this application is completed by manual adjustment and automatic algorithm optimization, and the final calibration results can be displayed in real time to improve the calibration efficiency.

[0094] Specifically, in the calibration process of the laser radar point cloud data and the inertial navigation module, the point cloud data to be calibrated are the point cloud data of the laser radar and the point cloud data in the coordinate system of the inertial navigation module. When the data distribution information of the point cloud data of the two completely overlaps, the calibration is completed. The terminal runs ROS (Robot Operating System), which provides a series of program libraries and tools to help software developers create robot application software. It provides many functions such as hardware abstraction, device drivers, library functions, visualization, message passing and software package management. ROS complies with the BSD (Berkeley Software Distribution) open source license agreement. Specifically, the RVIZ platform in ROS can be run. RVIZ is a three-dimensional visualization platform in ROS that can realize graphical display of external information. Furthermore, the terminal responds to the data calibration trigger operation triggered by the user in the RVIZ platform, and displays the point cloud data pre-calibration results in the calibration result area; the point cloud data pre-calibration results are obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm. Figure 5 As shown, the point cloud data pre-calibration result is displayed in the calibration result area in a specific application. It can be seen that the point cloud data at each corresponding position in the point cloud data pre-calibration result does not completely overlap, there is an error in the calibration, and further adjustment is needed.

[0095] The terminal displays a calibration adjustment operation item for adjusting the point cloud data pre-calibration result in the calibration adjustment area associated with the calibration result area; and in response to the calibration adjustment operation triggered by the calibration adjustment operation item, displays the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation. Figure 6 As shown in the figure, the lower left corner is the calibration adjustment area associated with the calibration result area. The calibration adjustment area includes various calibration adjustment operation items for adjusting the point cloud data pre-calibration results. The user can trigger the calibration adjustment operation on the calibration adjustment operation item. The terminal displays the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation in the calibration result area. It can be seen that at this time, the point cloud data of each corresponding position in the point cloud data pre-calibration result has completely overlapped, achieving high-precision calibration.

[0096] In the traditional black box calibration mode, after inputting data, you can only check whether the calibration is accurate after waiting for the calibration algorithm to output the final calibration result. If the accuracy does not meet the requirements, you can only adjust it by re-running the calibration algorithm by adjusting parameters, or re-collecting data, etc., which is inefficient. In this embodiment, the calibration of the lidar and inertial navigation module is performed based on the ROS-RVIZ visual interface, which is completed by manual adjustment and automatic algorithm optimization. Specifically, the calibration results are fed back in real time through the ROS-RVIZ visual interface, and two methods, automatic calibration and manual fine-tuning, are introduced. When the algorithm fails, the results are corrected in time through manual intervention, which gets rid of the troubles caused by the black box model and improves the calibration efficiency.

[0097] Compared with the traditional calibration method, this embodiment does not need to collect data for a specific route. It only needs to stop in place and collect two sets of data, one positive and one negative. It is highly feasible. It also combines manual intervention with algorithms. When the algorithm cannot produce the correct result or the result is biased, manual intervention can be performed to make adjustments without the need to re-calibrate the process, which greatly improves the calibration efficiency. In addition, the final calibration result of this embodiment is fed back in real time on the RVIZ visualization interface in the form of a point cloud. The user only needs to ensure that the two sets of point clouds overlap for the calibration to be successful. The complex calibration process is simplified into a simple puzzle process, which improves the calibration processing efficiency of point cloud data.

[0098] It should be understood that although Figure 2 , 4 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 , 4 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0099] In one embodiment, Figure 7 As shown, a point cloud data calibration device is provided, including: a data calibration module 702, an adjustment operation item display module 704 and a calibration adjustment module 706, wherein:

[0100] The data calibration module 702 is used to display the point cloud data pre-calibration result in the calibration result area in response to the data calibration trigger operation; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm;

[0101] An adjustment operation item display module 704 is used to display calibration adjustment operation items for adjusting the pre-calibration result of the point cloud data in a calibration adjustment area associated with the calibration result area;

[0102] The calibration adjustment module 706 is configured to, in response to a calibration adjustment operation triggered by a calibration adjustment operation item, display a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation.

[0103] In one embodiment, the data calibration module 702 includes an import trigger module, an import result module and a calibration trigger module; wherein: the import trigger module is used to display the point cloud data import operation item in response to the point cloud data import trigger operation; the import result module is used to display the data import result of the point cloud data to be calibrated in response to the data import operation triggered by the point cloud data import operation item; the calibration trigger module is used to display the point cloud data pre-calibration result in the calibration result area in response to the data calibration trigger operation triggered by the data import result.

[0104] In one embodiment, the data calibration module 702 is further configured to display data distribution information corresponding to the point cloud data to be calibrated in a calibration result area in different display modes.

[0105] In one embodiment, it also includes a calibration processing module, which is used to obtain the point cloud data to be calibrated; based on a preset calibration algorithm, the point cloud data to be calibrated is calibrated to obtain a point cloud data pre-calibration result corresponding to the point cloud data to be calibrated.

[0106] In one embodiment, the calibration adjustment operation items include at least a rotation operation item and a translation operation item; the calibration adjustment module 706 includes a rotation adjustment module and a translation adjustment module; wherein: the rotation adjustment module is used to respond to the rotation operation triggered by the rotation operation item, and display the rotation adjustment result obtained after the point cloud data pre-calibration result is rotated in the calibration result area; the translation adjustment module is used to respond to the translation operation triggered by the translation operation item, and display the point cloud data calibration result obtained after the rotation adjustment result is translated in the calibration result area.

[0107] In one embodiment, it also includes an adjustment parameter determination module, a rotation processing module and a translation processing module; wherein: the adjustment parameter determination module is used to determine the rotation adjustment parameters corresponding to the rotation operation and the translation adjustment parameters corresponding to the translation operation; the rotation processing module is used to perform rotation processing on the point cloud data pre-calibration result according to the rotation adjustment parameters to obtain the rotation adjustment result; the translation processing module is used to perform translation processing on the rotation adjustment result according to the translation adjustment parameters to obtain the point cloud data calibration result.

[0108] In one embodiment, it also includes a default parameter display module, which is used to display the default adjustment parameters in the calibration adjustment operation item; the default adjustment parameters are obtained by adjusting and analyzing the point cloud data pre-calibration results; the calibration adjustment module 706 is also used to respond to the adjustment confirmation operation of the calibration adjustment operation item, and display the point cloud data calibration results obtained after adjusting the point cloud data pre-calibration results through the default adjustment parameters.

[0109] For the specific definition of the point cloud data calibration device, please refer to the definition of the point cloud data calibration method above, which will not be repeated here. Each module in the above-mentioned point cloud data calibration device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0110] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a point cloud data calibration method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0111] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0112] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0113] In response to the data calibration trigger operation, the point cloud data pre-calibration result is displayed in the calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm;

[0114] In the calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the pre-calibration results of the point cloud data are displayed;

[0115] In response to a calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed.

[0116] In one embodiment, the processor further implements the following steps when executing the computer program: in response to a point cloud data import trigger operation, displaying a point cloud data import operation item; in response to a data import operation triggered by the point cloud data import operation item, displaying a data import result of importing the point cloud data to be calibrated; in response to a data calibration trigger operation triggered by the data import result, displaying a point cloud data pre-calibration result in the calibration result area.

[0117] In one embodiment, when the processor executes the computer program, the following steps are further implemented: in the calibration result area, data distribution information corresponding to the point cloud data to be calibrated is displayed in different display modes.

[0118] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the point cloud data to be calibrated; performing calibration processing on the point cloud data to be calibrated based on a preset calibration algorithm to obtain a point cloud data pre-calibration result corresponding to the point cloud data to be calibrated.

[0119] In one embodiment, the calibration adjustment operation items include at least a rotation operation item and a translation operation item; when the processor executes the computer program, the following steps are also implemented: in response to a rotation operation triggered by the rotation operation item, a rotation adjustment result obtained by rotating the point cloud data pre-calibration result is displayed in the calibration result area; in response to a translation operation triggered by the translation operation item, a point cloud data calibration result obtained by translating the rotation adjustment result is displayed in the calibration result area.

[0120] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the rotation adjustment parameters corresponding to the rotation operation and the translation adjustment parameters corresponding to the translation operation; rotating the point cloud data pre-calibration result according to the rotation adjustment parameters to obtain the rotation adjustment result; translating the rotation adjustment result according to the translation adjustment parameters to obtain the point cloud data calibration result.

[0121] In one embodiment, when the processor executes the computer program, the following steps are also implemented: in the calibration adjustment operation item, default adjustment parameters are displayed; the default adjustment parameters are obtained by adjusting and analyzing the point cloud data pre-calibration results; in response to the adjustment confirmation operation of the calibration adjustment operation item, the point cloud data calibration results obtained after adjusting the point cloud data pre-calibration results through the default adjustment parameters are displayed.

[0122] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0123] In response to the data calibration trigger operation, the point cloud data pre-calibration result is displayed in the calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm;

[0124] In the calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the pre-calibration results of the point cloud data are displayed;

[0125] In response to a calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed.

[0126] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: in response to a point cloud data import trigger operation, a point cloud data import operation item is displayed; in response to a data import operation triggered by the point cloud data import operation item, a data import result of the point cloud data to be calibrated is displayed; in response to a data calibration trigger operation triggered by the data import result, a point cloud data pre-calibration result is displayed in the calibration result area.

[0127] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: in the calibration result area, data distribution information corresponding to the point cloud data to be calibrated is displayed in different display modes.

[0128] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the point cloud data to be calibrated; calibrating the point cloud data to be calibrated based on a preset calibration algorithm to obtain a point cloud data pre-calibration result corresponding to the point cloud data to be calibrated.

[0129] In one embodiment, the calibration adjustment operation items include at least a rotation operation item and a translation operation item; when the computer program is executed by the processor, the following steps are also implemented: in response to a rotation operation triggered by the rotation operation item, a rotation adjustment result obtained by rotating the point cloud data pre-calibration result is displayed in the calibration result area; in response to a translation operation triggered by the translation operation item, a point cloud data calibration result obtained by translating the rotation adjustment result is displayed in the calibration result area.

[0130] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the rotation adjustment parameters corresponding to the rotation operation and the translation adjustment parameters corresponding to the translation operation; rotating the point cloud data pre-calibration result according to the rotation adjustment parameters to obtain the rotation adjustment result; translating the rotation adjustment result according to the translation adjustment parameters to obtain the point cloud data calibration result.

[0131] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: in the calibration adjustment operation item, default adjustment parameters are displayed; the default adjustment parameters are obtained by adjusting and analyzing the point cloud data pre-calibration results; in response to the adjustment confirmation operation of the calibration adjustment operation item, the point cloud data calibration results obtained after adjusting the point cloud data pre-calibration results through the default adjustment parameters are displayed.

[0132] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0133] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0134] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A point cloud data calibration method, characterized in that: The method comprises: In response to the data calibration trigger operation, a point cloud data pre-calibration result is displayed in the calibration result area; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on the calibration algorithm, and after the point cloud data to be calibrated in the point cloud data pre-calibration result is calibrated by the calibration algorithm, the point cloud data to be calibrated fails to completely overlap; In a calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the point cloud data pre-calibration result are displayed, wherein the calibration adjustment operation items include at least one type of operation items for manually adjusting the point cloud data pre-calibration result; In response to a calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation is displayed.

2. The method according to claim 1, characterized in that The method of displaying the point cloud data pre-calibration result in the calibration result area in response to the data calibration trigger operation includes: In response to a point cloud data import trigger operation, displaying a point cloud data import operation item; In response to the data import operation triggered by the point cloud data import operation item, displaying the data import result of importing the point cloud data to be calibrated; In response to a data calibration triggering operation triggered by the data import result, a point cloud data pre-calibration result is displayed in a calibration result area.

3. The method according to claim 2, characterized in that The displaying of the point cloud data pre-calibration result in the calibration result area includes: In the calibration result area, the data distribution information corresponding to the point cloud data to be calibrated is displayed in different display modes.

4. The method according to claim 1, characterized in that: The point cloud data pre-calibration result is obtained through the step of point cloud data calibration processing, and the step of point cloud data calibration processing includes: Obtain the point cloud data to be calibrated; The point cloud data to be calibrated is calibrated based on a preset calibration algorithm to obtain a point cloud data pre-calibration result corresponding to the point cloud data to be calibrated.

5. The method according to claim 1, characterized in that The calibration adjustment operation items at least include a rotation operation item and a translation operation item; the calibration adjustment operation triggered by the calibration adjustment operation item, displaying the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation, includes: In response to a rotation operation triggered by the rotation operation item, displaying a rotation adjustment result obtained by rotating the point cloud data pre-calibration result in the calibration result area; In response to a translation operation triggered by the translation operation item, a point cloud data calibration result obtained by performing translation processing on the rotation adjustment result is displayed in the calibration result area.

6. The method according to claim 5, characterized in that The method further comprises: Determining a rotation adjustment parameter corresponding to the rotation operation and a translation adjustment parameter corresponding to the translation operation; Performing rotation processing on the pre-calibrated result of the point cloud data according to the rotation adjustment parameter to obtain a rotation adjustment result; The rotation adjustment result is translated according to the translation adjustment parameter to obtain a point cloud data calibration result.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: In the calibration adjustment operation item, default adjustment parameters are displayed; the default adjustment parameters are obtained by adjusting and analyzing the pre-calibration results of the point cloud data; The step of displaying, in response to the calibration adjustment operation triggered by the calibration adjustment operation item, a point cloud data calibration result obtained by adjusting the point cloud data pre-calibration result through the calibration adjustment operation, comprises: In response to an adjustment confirmation operation on the calibration adjustment operation item, a point cloud data calibration result obtained by adjusting the point cloud data pre-calibration result by using the default adjustment parameters is displayed.

8. A point cloud data calibration device, characterized in that: The device comprises: A data calibration module, for displaying a point cloud data pre-calibration result in a calibration result area in response to a data calibration trigger operation; the point cloud data pre-calibration result is obtained by calibrating the point cloud data to be calibrated based on a calibration algorithm, and after the point cloud data to be calibrated in the point cloud data pre-calibration result is calibrated by the calibration algorithm, the point cloud data to be calibrated fails to completely overlap; an adjustment operation item display module, configured to display, in a calibration adjustment area associated with the calibration result area, calibration adjustment operation items for adjusting the point cloud data pre-calibration result, wherein the calibration adjustment operation items include at least one type of operation items for manually adjusting the point cloud data pre-calibration result; The calibration adjustment module is used to respond to the calibration adjustment operation triggered by the calibration adjustment operation item, and display the point cloud data calibration result obtained after adjusting the point cloud data pre-calibration result through the calibration adjustment operation.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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