A radar point cloud acquisition method and device based on a scale rail

Abstract

The application provides a radar point cloud collection method and device based on a guide rail with scales, wherein the method comprises the following steps: connecting a radar to the guide rail with scales through a fixing device, determining the relative position relationship between the radar and the guide rail, collecting point cloud data at different scale positions in sequence, and fusing multiple groups of point cloud data into a global coordinate system to form a complete point cloud set. Through the guide rail, scale position information and external parameter calibration are output in real time, accurate alignment and efficient fusion of the point cloud data are realized, the problems of data distortion and spatial drift caused by radar movement are avoided, the completeness and collection accuracy of the point cloud data are improved, the radar sensing range and the density of the point cloud data are effectively improved, the cost is reduced, and meanwhile, for some working face scenes, the radar can be automatically controlled to collect data back and forth near the working face, so that the data accuracy and quality are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radar data collection, and in particular to a radar point cloud collection method and device based on a scale rail. BACKGROUND

[0002] Existing radar devices usually have a small scanning field of view angle. If a larger field of view angle needs to be covered, the traditional method is usually to use multiple radars for splicing.

[0003] However, this approach has many problems, such as complex external parameter calibration between multiple radars, high cost, unavoidable splicing errors, and greatly increased system complexity. In addition, due to the asynchronization of multiple radar devices in space and time, overlapping errors or holes may occur when fusing point cloud data, reducing the integrity and accuracy of the point cloud. SUMMARY

[0004] The present application aims to at least solve one of the technical problems in the related art to some extent.

[0005] To this end, a first object of the present application is to provide a radar point cloud collection method based on a scale rail.

[0006] A second object of the present application is to provide a radar point cloud collection device based on a scale rail.

[0007] A third object of the present application is to provide an electronic device.

[0008] A fourth object of the present application is to provide a computer-readable storage medium.

[0009] A fifth object of the present application is to provide a computer program product.

[0010] To achieve the above objects, an embodiment of the first aspect of the present application provides a radar point cloud collection method based on a scale rail, comprising:

[0011] S1, connecting a radar on a rail through a fixed connection device, the fixed connection device being capable of moving along the rail, and the rail being capable of outputting scale position information of the fixed connection device in real time;

[0012] S2, determining a relative position relationship between the rail and the radar through external parameter calibration, and the calibration result including an included angle between the rail and a horizontal plane of the radar;

[0013] S3, collecting point cloud data at an initial scale position on the rail by the radar, recording the collected point cloud data as a first group of point cloud data, and taking a current radar coordinate system as a global coordinate system;

[0014] S4, moving the fastening device along the guide rail by a certain scale, collecting point cloud data by the radar, and recording the collected point cloud data as a second group of point cloud data;

[0015] S5, projecting the second group of point cloud data into a global coordinate system corresponding to the first group of point cloud data, and adjusting the coordinates of each point in the second group of point cloud data;

[0016] S6, repeating steps S4 and S5 to collect and fuse point cloud data at multiple scale positions to form a complete point cloud set.

[0017] Optionally, the relative position relationship between the guide rail and the radar is determined by external parameter calibration, and the calibration result includes an included angle between the guide rail and a horizontal plane of the radar, and includes:

[0018] A vertical plane is arranged in front of the radar as a calibration target;

[0019] Adjust the radar so that the horizontal plane of the radar is perpendicular to the plane of the calibration target;

[0020] Move the radar to the minimum position and the maximum position of the guide rail scale respectively, and record the distances d0 and d1 from the radar to the calibration target and the moving distance s of the guide rail respectively;

[0021] The included angle between the guide rail and the horizontal plane of the radar is calculated according to the following formula, and the expression is:

[0022]

[0023] Wherein, α is the included angle between the guide rail and the horizontal plane of the radar.

[0024] Optionally, the radar is adjusted so that the horizontal plane of the radar is perpendicular to the plane of the calibration target, including:

[0025] For a single-line radar, the radar angle is adjusted until the straight line fitting parameters meet the vertical condition by collecting calibration target point cloud data and fitting a straight line;

[0026] For a multi-line or three-dimensional radar, the radar angle is adjusted until the plane fitting parameters meet the vertical condition by collecting calibration target point cloud data and fitting a plane.

[0027] Optionally, the second group of point cloud data is projected into the global coordinate system corresponding to the first group of point cloud data to adjust the coordinates of each point in the second group of point cloud data, including:

[0028] The y coordinate of each point in the second group of point cloud data is adjusted to y new =y-L*cosα;

[0029] adjusting a z coordinate of each point in the second set of point cloud data to z new =z+L*sinα.

[0030] To achieve the above object, the second aspect of the present application provides a radar point cloud collection device based on a scale rail, comprising:

[0031] a radar, configured to collect point cloud data;

[0032] a fixing device, configured to fix the radar on a rail and enable the radar to move along the rail;

[0033] a rail, which is a scale linear rail, supports the movement of the fixing device, and outputs scale position information of the fixing device in real time;

[0034] a processing unit, connected with the radar and the rail, configured to process point cloud data, including external parameter calibration, coordinate conversion and point cloud fusion.

[0035] Optionally, the processing unit is a consumer computer, an industrial control computer or other terminal device supporting data processing.

[0036] Optionally, the radar is a single-line radar, a multi-line radar or a radar device capable of collecting three-dimensional point cloud data.

[0037] To achieve the above object, the third aspect of the present application provides an electronic device, comprising a processor and a memory connected with the processor;

[0038] the memory stores computer execution instructions;

[0039] the processor executes the computer execution instructions stored in the memory to realize the method according to any one of the first aspect.

[0040] To achieve the above object, the fourth aspect of the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to realize the method according to any one of the first aspect.

[0041] To achieve the above object, the fifth aspect of the present application provides a computer program product, which realizes the method according to any one of the first aspect when the computer program is executed by a processor.

[0042] The technical scheme provided by the embodiments of the present application at least brings the following beneficial effects:

[0043] The method avoids the complexity and error caused by multi-radar splicing, reduces the equipment cost, provides a new idea for realizing large field angle and high precision point cloud collection, and can effectively improve the radar sensing range and the density of point cloud data, reduce the cost, and at the same time, for some working surface scenes, the radar can be automatically controlled to collect data back and forth near the working surface, improve the data precision and quality.

[0044] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0045] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the accompanying drawings, wherein:

[0046] Figure 1 A flowchart of a radar point cloud collection method based on a scale rail provided by an embodiment of the present application;

[0047] Figure 2 A structural schematic diagram of a radar point cloud collection device based on a scale rail provided by an embodiment of the present application. DETAILED DESCRIPTION

[0048] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0049] In view of the problems in the prior art, the present application provides a radar point cloud collection method and device based on a scale rail. The method collects point cloud data by moving a single radar along a scale rail, and uses an external parameter calibration and data fusion method to accurately align the data of multiple collection positions to generate a complete point cloud. This method effectively avoids the complexity and error caused by multi-radar splicing, reduces the equipment cost, and provides a new idea for realizing large field angle and high precision point cloud collection.

[0050] Figure 1 A flowchart of a radar point cloud collection method based on a scale rail provided by an embodiment of the present application, which is applied to Figure 2 A radar point cloud collection device based on a scale rail shown in an embodiment of the present application.

[0051] AsFigure 2 As shown in the device, the device includes a radar, a fixed device, a guide rail, and a processing unit. In design, the radar and the fixed device are fixed, the Y-axis of the radar and the forward axis of the fixed device are consistent, and the Z-axis of the fixed device and the movement direction of the guide rail form a plane that intersects the Y-axis of the radar.

[0052] The radar is used to collect point cloud data; the fixed device is used to fix the radar on the guide rail and can move along the guide rail; the guide rail is a linear guide rail with scales, supports the movement of the fixed device, and outputs the scale position information of the fixed device in real time; the processing unit is connected with the radar and the guide rail, and is used for processing point cloud data, including external parameter calibration, coordinate conversion, and point cloud fusion.

[0053] In addition, in the embodiments of the present application, the processing unit is a consumer-level computer, an industrial control computer, or other terminal equipment supporting data processing; the radar is a single-line radar, a multi-line radar, or a radar device capable of collecting three-dimensional point cloud data. The present application does not make specific limitations.

[0054] The following will explain in detail the radar point cloud collection method based on the guide rail with scales shown in the embodiments of the present application, as shown in the device. Figure 1 As shown in the method, the method comprises the following steps:

[0055] S1, connecting the radar on the guide rail through the fixed device, the fixed device can move along the guide rail, and the guide rail can output the scale position information of the fixed device in real time.

[0056] In the embodiments of the present application, as shown in the above device, the fixed device is a component for fixing the radar to the guide rail. Through the fixed device, the radar can be stably attached to the guide rail, ensuring the stability of its position and direction during movement.

[0057] Moreover, the fixed device is designed to slide or move along the guide rail. This movement allows the radar to collect point cloud data at different positions, providing a basis for subsequent multi-position point cloud fusion.

[0058] The guide rail has scale marks that can record and output the current position of the fixed device in real time. These scale position information is transmitted to the processing unit to determine the accurate position of the radar when collecting point cloud data, ensuring the relevance and accuracy of the data at different positions.

[0059] Through this step, the controllable movement and position tracking of the radar on the guide rail are realized, providing a basic condition for multi-position point cloud data collection, and laying a precise positioning basis for subsequent coordinate conversion and point cloud fusion.

[0060] S2, determining the relative position relationship between the guide rail and the radar through external parameter calibration, and the calibration result includes the included angle between the guide rail and the horizontal plane of the radar.

[0061] It should be noted that before the radar point cloud data collection, the relative position relationship between the guide rail and the radar needs to be determined, especially the included angle between the guide rail and the radar horizontal plane. This calibration process is to ensure that in the subsequent point cloud data collection, the point cloud data at different positions can be accurately projected into the global coordinate system.

[0062] The specific calibration process is as follows:

[0063] Step 1, a vertical plane is set in front of the radar as a calibration target.

[0064] First, a vertical plane is set in front of the radar as a calibration target, which provides a known standard plane to help determine the attitude of the radar.

[0065] It should be noted that the calibration target can be a plane substantially perpendicular to the ground, or a wall, which is not limited in the present application.

[0066] Step 2, adjust the radar so that the radar horizontal plane is perpendicular to the calibration target plane.

[0067] First, determine whether the radar horizontal plane is perpendicular to the calibration target. If not, adjust the direction of the radar, the specific operation is:

[0068] For a single-line radar, a set of one-dimensional point cloud data is obtained on the calibration target, and a straight line fitting method is used to calculate the straight line parameters ax+by+c=0. If a is very small, it means that the radar is perpendicular to the scanning straight line, and the radar is rotated by a certain angle along the radar horizontal plane, and the data is collected again to fit the plane. If the radar is perpendicular to the scanning straight line after rotation, it means that the current radar horizontal plane is perpendicular to the target plane, otherwise, adjust the position of the radar until the radar is perpendicular to the horizontal plane.

[0069] For multi-line or three-dimensional radar, after obtaining the point cloud data on the calibration target, directly perform plane fitting, and the fitting equation is ax+by+cz+d=0. If c is very small, it is considered that the current radar horizontal plane is perpendicular to the target plane, and the next step can be started, otherwise, the position of the radar can be adjusted until the two are perpendicular.

[0070] Step 3, move the radar to the minimum position and the maximum position of the guide rail scale respectively, and record the distance d0 and d1 from the radar to the calibration target and the moving distance s of the guide rail.

[0071] After ensuring that the radar horizontal plane is perpendicular to the target plane, move the radar to the minimum position and the maximum position of the guide rail scale respectively, and record the distance d0 and d1 from the radar to the calibration target and the moving distance s of the guide rail.

[0072] Step 4, according to the above measurement data, the included angle between the guide rail and the radar horizontal plane is calculated by using the triangular relationship, and the expression is:

[0073]

[0074] Wherein, a is the angle between the guide rail and the radar horizontal plane.

[0075] Step 5, after calculating the angle, complete the calibration.

[0076] It should be noted that through the external parameter calibration, the relative position relationship between the radar and the guide rail can be accurately measured and corrected, so that when the guide rail moves, the point cloud data will not be wrong due to the deviation of the radar angle. This step provides an accurate geometric basis for subsequent point cloud coordinate conversion and fusion.

[0077] S3, collect point cloud data by radar at the initial scale position on the guide rail, record the collected point cloud data as the first group of point cloud data, and take the current radar coordinate system as the global coordinate system.

[0078] Before collecting radar point cloud data, a scale position on the guide rail needs to be selected as the starting point, and the leftmost scale position (marked as 0) of the guide rail is usually taken as the default initial position. Figure 2 The black rectangle in the figure marks the starting point.

[0079] In actual operation, the initial collection position is not fixed, and data can be collected from any position on the guide rail as needed, but in the embodiments of the present application, the scale 0 of the guide rail is taken as the starting point for illustration.

[0080] That is, in the embodiments of the present application, point cloud data is collected at the starting scale position by radar, and the collected point cloud data is recorded as the first group of point cloud data P0. Moreover, the coordinate system of the radar at the initial collection is defined as the global coordinate system, which means that all subsequent point cloud data will be aligned and fused based on this coordinate system.

[0081] It should be noted that by taking the radar coordinate system at the initial position as the global coordinate system, subsequent point cloud data can be unified under one reference framework, which can avoid the difficulty of alignment caused by inconsistent coordinate systems of multiple groups of data.

[0082] S4, move the fixed connection device along the guide rail by a certain scale, collect point cloud data by radar, and record the collected point cloud data as the second group of point cloud data.

[0083] In the embodiments of the present application, the fixed connection device is controlled to move to a new scale position along the guide rail. The distance of this movement is calibrated by the scale on the guide rail, so that the distance of each movement is known and controllable. The purpose of the movement is to collect data by moving the radar to a new position, gradually covering the target area, and obtaining more complete point cloud information.

[0084] Then, at the new scale position, the radar collects point cloud data again, and this set of data is recorded as the second set of point cloud data P1, which contains the environmental information at different positions relative to the first set of point cloud data P0 at the initial position.

[0085] S5, projecting the second set of point cloud data into the global coordinate system corresponding to the first set of point cloud data to adjust the coordinates of each point in the second set of point cloud data.

[0086] In the embodiments of the present application, the second set of point cloud data is projected into the global coordinate system in which the first set of point cloud data is located, so that the two sets of data can be accurately aligned in the same coordinate system.

[0087] Moreover, using the scale distance L moved by the guide rail and the angle a between the guide rail and the horizontal plane of the radar, the new position of the point cloud data in the global coordinate system is calculated, i.e. the y coordinate of each point in the second set of point cloud data is adjusted to y new = y - L*cos a, and the z coordinate of each point in the second set of point cloud data is adjusted to z new = z + L*sin a.

[0088] In this coordinate transformation formula, L*cos a is the projection of the guide rail movement in the y direction, and after subtracting this value, the y coordinate of the point is adjusted to the global coordinate system; L*sin a is the projection of the guide rail movement in the z direction, and after adding this value, the z coordinate of the point is adjusted to the global coordinate system.

[0089] After coordinate adjustment, the data of all collection positions can be unified in one coordinate system, thereby eliminating the coordinate deviation caused by radar movement and providing accurate data basis for generating a complete point cloud model.

[0090] S6, repeating steps S4 and S5 to collect and fuse point cloud data at multiple scale positions to form a complete point cloud set.

[0091] According to the requirements, continue to move the fixed device along the guide rail, and the radar collects new point cloud data at each scale position. These new point cloud data are recorded as corresponding groups (such as the third and fourth sets of point cloud data, etc.). And each time a new set of point cloud data is collected, it is projected into the global coordinate system according to the method of S5 and fused with the previously collected data.

[0092] Finally, through multiple repeated collection and fusion, all scale positions within the guide rail movement range are gradually covered, and multiple scale position point cloud data within the guide rail range are spliced together to generate a complete point cloud set covering the target area.

[0093] It can be understood that the fused point cloud set includes data collected at different angles and positions, which makes up for the defects caused by the limitation of the single radar field of view angle, and realizes large-range high-precision point cloud collection. Moreover, each projection and fusion is carried out in the global coordinate system, which can ensure the accuracy of data alignment and reduce splicing errors.

[0094] To achieve the above-mentioned embodiments, the present application further provides an electronic device, comprising: a processor, and a memory connected with the processor in communication; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to realize the method provided by the foregoing embodiments.

[0095] To achieve the above-mentioned embodiments, the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by a processor to realize the method provided by the foregoing embodiments.

[0096] To achieve the above-mentioned embodiments, the present application further provides a computer program product, comprising a computer program, which is executed by a processor to realize the method provided by the foregoing embodiments.

[0097] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in the present application comply with relevant laws and regulations and do not violate public order and good customs.

[0098] It should be noted that personal information from users should be collected for legitimate and reasonable purposes, and should not be shared or sold outside these legitimate uses. In addition, such collection / sharing should be carried out after receiving the informed consent of the user, including but not limited to informing the user to read the user agreement / user notice before the user uses the function, and signing the agreement / authorization including authorization of relevant user information. In addition, any necessary steps should be taken to protect and ensure access to such personal information data, and to ensure that other people with access to personal information data comply with their privacy policy and processes.

[0099] The present application is expected to provide an embodiment in which the user can selectively prevent the use or access of personal information data. That is, the present disclosure is expected to provide hardware and / or software to prevent or prevent access to such personal information data. Once the personal information data is no longer needed, the risk is minimized by limiting data collection and deleting data. In addition, such personal information is de-identified to protect the privacy of the user, if applicable.

[0100] In the foregoing detailed description, reference is made to descriptive terms such as "one embodiment", "some embodiments", "an example", "a specific example" or "some examples" etc. for describing various embodiments of the application. These descriptive terms are used for the purpose of the description and are not meant to limit or restrict the scope of the application. The use of these terms does not imply that the application is comprised of at least the features described in the specific example. In addition, the description is not meant to imply that the described embodiments are the only manner in which the application can be practiced. Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments or examples. Moreover, the described embodiments and features are not meant to be all inclusive but rather are meant to be exemplary only. Therefore, the scope of the application should be determined by the appended claims and their legal equivalents rather than by the description.

[0101] Furthermore, the terms "first", "second", etc. are used herein only to describe various embodiments and do not imply either a relative importance or a specific order of the features being described. Thus, features defined with "first", "second" etc. can include at least one of the features implicitly or explicitly. The meaning of "a plurality" herein is at least two, for example, two, three or four, unless expressly specified otherwise.

[0102] Any process or method descriptions or blocks in flow charts or otherwise described herein represent embodiments of the application that can be managed as one or more modules, segments, or portions of code that include one or more steps for implementing specific logic functions or steps, and the terms "module", "segment" or "portion" can be used in the description of this application interchangeably with the term "code". The various embodiments of the application can be further understood from the following examples.

[0103] The logic and / or steps represented in the flowcharts and / or described herein, for example, can be considered as a sequence of executable instructions stored in a computer readable medium, which can be executed by an instruction execution system, apparatus or device, such as a computer-based system, a processor-based system, or other system that can fetch the instructions from the instruction execution system, apparatus or device and execute the instructions, or a combination thereof. For the purposes of this specification, a "computer readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus or device. The computer readable medium can specifically be, but is not limited to, the following: an electronic connection (electronic apparatus) having one or more wires, a portable computer diskette (magnetic apparatus), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disk read-only memory (CDROM). In addition, the computer readable medium can even be paper or other suitable medium upon which the program can be printed, because the program can be electronically obtained, for example, by optically scanning the paper or other medium, then

[0104] It should be understood that portions of the application can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As such, if implemented in hardware, and in another embodiment, any of the following technologies, known in the art, or a combination thereof, can be used: discrete logic circuitry having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and the like.

[0105] Those of ordinary skill in the art can understand that all or part of the steps carried out by the above-mentioned embodiment methods can be completed by programs instructing relevant hardware, and the programs can be stored in a computer readable storage medium. When the programs are executed, they include one of the steps of the method embodiments or a combination thereof.

[0106] In addition, each of the function units in each embodiment of the present application can be integrated in one processing module, or each unit can be physically present separately, or two or more units can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software function module. When the integrated module is realized in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0107] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

[0108] It should be understood that the various forms of flow shown above can be reordered, added or deleted steps. For example, each step described in the present application can be executed in parallel, sequentially or in different order, as long as the desired results of the technical solutions of the present application can be achieved, which is not limited herein.

[0109] The above detailed description does not constitute a limitation on the scope of protection of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and replacements can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for collecting radar point clouds based on a graduated guide rail, characterized in that, The method comprises the following steps: S1, connecting the radar to the guide rail through a fixed device, the fixed device being capable of moving along the guide rail, the guide rail being capable of outputting scale position information of the fixed device in real time; S2, determining a relative position relationship between the guide rail and the radar through external parameter calibration, the calibration result comprising an included angle between the guide rail and a horizontal plane of the radar, specifically comprising: a vertical plane is arranged in front of the radar as a calibration target; the radar is adjusted so that the horizontal plane of the radar is perpendicular to the plane of the calibration target; the radar is moved to the minimum position and the maximum position of the guide rail scale respectively, and the distances d0 and d1 of the radar to the calibration target and the moving distance s of the guide rail are recorded respectively; the included angle between the guide rail and the horizontal plane of the radar is calculated according to the following formula, the expression being: wherein, a is the included angle between the guide rail and the horizontal plane of the radar; S3, collecting point cloud data by the radar at an initial scale position on the guide rail, the collected point cloud data being recorded as a first group of point cloud data, and taking the current radar coordinate system as a global coordinate system; S4, moving the fixed device along the guide rail by a certain scale, collecting point cloud data by the radar, and recording the collected point cloud data as a second group of point cloud data; S5, projecting the second group of point cloud data into the global coordinate system corresponding to the first group of point cloud data, and adjusting the coordinates of each point in the second group of point cloud data, the specific adjustment manner being: adjusting a y coordinate of each point in the second set of point cloud data to y new = y - L*cos a; adjusting a z coordinate of each point in the second set of point cloud data to z new = z + L * sin a; wherein, L is the scale distance of the fixed device moving along the guide rail; S6, repeating steps S4 and S5 to collect and fuse point cloud data at multiple scale positions to form a complete point cloud set.

2. The method of claim 1, wherein, The adjustment of the radar so that the horizontal plane of the radar is perpendicular to the plane of the calibration target comprises: for a single-line radar, adjusting the radar angle until the straight line fitting parameters satisfy the perpendicular condition by collecting calibration target point cloud data and fitting a straight line; for a multi-line or three-dimensional radar, adjusting the radar angle until the plane fitting parameters satisfy the perpendicular condition by collecting calibration target point cloud data and fitting a plane.

3. A radar point cloud acquisition device based on a graduated guide rail, characterized in that, The device is used to implement the radar point cloud collection method based on a guide rail with scales according to claim 1, and the device comprises: a radar for collecting point cloud data; a fixed device for fixing the radar on a guide rail and capable of moving along the guide rail; a guide rail, which is a linear guide rail with scales, supports the movement of the fixed device, and outputs scale position information of the fixed device in real time; a processing unit connected with the radar and the guide rail, used for processing point cloud data, including external parameter calibration, coordinate conversion and point cloud fusion.

4. The apparatus of claim 3, wherein, The processing unit is a consumer-level computer, an industrial control computer or other terminal equipment supporting data processing.

5. The apparatus of claim 3, wherein, The radar is a single-line radar, a multi-line radar or a radar device capable of collecting three-dimensional point cloud data.

6. An electronic device, comprising: It comprises: a processor and a memory in communication connection with the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method according to any one of claims 1-2.

7. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer-executable instructions that, when executed by a processor, implement the method of any of claims 1-2.

8. A computer program product, characterised in that, A computer program that, when executed by a processor, implements the method of any of claims 1-2.

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