Mounting error acquisition method, device and 3D printer

Abstract

Embodiments of the present application provide a kind of installation error acquisition method, device and 3D printer.The method comprises: controlling acquisition device to scan the fixed area on hot bed and obtain background point cloud, control printing head and print calibration model on fixed area according to preset parameter, control acquisition device and collect panoramic point cloud containing fixed area and calibration model, panoramic point cloud and background point cloud are handled to obtain foreground point cloud containing calibration model, and according to foreground point cloud and the ideal installation position of acquisition device, the actual installation position of acquisition device is determined Installation error relative to ideal installation position.The method of the present application embodiment can effectively obtain the installation error of acquisition device, solve the problem of time-consuming and labor-consuming, low accuracy of repeated manual calibration, and then improve printing quality and intelligent level.

Description

Technical Field

[0001] This application relates to the field of 3D printing technology, and more specifically, to a method, apparatus and 3D printer for obtaining installation errors. Background Technology

[0002] A 3D printer, also known as a three-dimensional printer, is a machine that uses rapid prototyping technology. Based on digital model files, it uses molding materials to construct three-dimensional objects through a cumulative molding process. 3D printing technology has developed rapidly due to its many advantages, and the demand for 3D printers is increasing.

[0003] Installation errors are unavoidable during the mechanical assembly process of 3D printers. This is especially true for open-type printers, where installation errors can be even greater. Currently, the common method for addressing mechanical installation errors is to manually adjust the tightness of the mounting screws to manually calibrate the mechanical installation deviation. This often requires repetition, is time-consuming and labor-intensive, and the calibration effect is not ideal. Summary of the Invention

[0004] This application provides a method, apparatus, and 3D printer for obtaining installation errors, which can effectively obtain the installation errors of the 3D printer to achieve high-quality printing and intelligent level.

[0005] Firstly, a method for obtaining installation error is provided, applied to a 3D printer, which includes a data acquisition device, a heated bed, and a print head. The relative poses of the data acquisition device and the print head are fixed, and the data acquisition device moves with the print head. The method includes: controlling the data acquisition device to scan a fixed area on the heated bed to obtain a background point cloud; controlling the print head to print a calibration model on the fixed area according to preset parameters; controlling the data acquisition device to acquire a panoramic point cloud containing the fixed area and the calibration model; processing the panoramic point cloud and the background point cloud to obtain a foreground point cloud containing the calibration model; and determining the installation error of the actual installation position of the data acquisition device relative to the ideal installation position based on the foreground point cloud and the ideal installation position of the data acquisition device.

[0006] Based on the solution provided in this application, the foreground point cloud containing the calibration model can be determined by using the background point cloud containing a fixed area and the panoramic point cloud containing the fixed area and the calibration model acquired by the acquisition device. Simultaneously, printing a calibration model of a custom shape in the fixed area provides a reference coordinate for obtaining the installation error of the acquisition device. That is, the installation error of the acquisition device can be obtained based on the foreground point cloud and the ideal installation position of the acquisition device, facilitating the calibration of the acquisition device. Furthermore, based on this installation error, the point cloud data acquired by the acquisition device can be effectively calibrated, enabling self-calibration of the 3D printer. This reduces the precision requirements of the 3D printer in mechanical installation, solves the problems of time-consuming, labor-intensive, and low-accuracy operations caused by repeated manual calibration, and improves the accuracy and intelligence level of 3D printing.

[0007] Secondly, an installation error acquisition device is provided, comprising: a control unit for controlling a data acquisition device to scan a fixed area on a heated bed to obtain a background point cloud; controlling a printing nozzle to print a calibration model on the fixed area according to preset parameters; controlling the data acquisition device to acquire a panoramic point cloud containing the fixed area and the calibration model; a processing unit for processing the panoramic point cloud and the background point cloud to obtain a foreground point cloud containing the calibration model; and determining the installation error of the actual installation position of the data acquisition device relative to the ideal installation position based on the foreground point cloud and the ideal installation position of the data acquisition device.

[0008] Thirdly, a 3D printer is provided, comprising: a data acquisition device, a heated bed, a print head, and a main control chip. The relative poses of the data acquisition device and the print head are fixed, and the data acquisition device moves with the print head. The print head is used to print a calibration model on a fixed area of ​​the heated bed. The data acquisition device is used to acquire a foreground cloud including the heated bed and a panoramic view including the heated bed and the calibration model. The main control chip is used to control the print head and the data acquisition device, and to process the foreground cloud and panoramic cloud according to a method as described in the first aspect and any possible implementation thereof, to obtain the installation error of the actual installation position of the data acquisition device relative to the ideal installation position.

[0009] Fourthly, a computer-readable storage medium is provided for storing a computer program that, when run on a computer, causes the computer to perform the methods described in the first aspect and any possible implementation thereof. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the structure of a 3D printer provided in an embodiment of this application.

[0011] Figure 2 This is a top view of the 3D printer provided in the embodiments of this application.

[0012] Figure 3This is a schematic diagram illustrating the working principle of the 3D printer provided in the embodiments of this application.

[0013] Figure 4 This is a flowchart of an installation error acquisition method provided in an embodiment of this application.

[0014] Figure 5 These are the front view, left view, and top view of the calibration model provided in the embodiments of this application.

[0015] Figure 6 This is a schematic diagram of linear fitting of an empty bed when the heated bed is tilted or not tilted, as provided in the embodiments of this application.

[0016] Figure 7 This is a schematic diagram of the foreground point cloud being segmented by a straight line when the heated bed is tilted or not tilted, as provided in the embodiments of this application.

[0017] Figure 8 This is a schematic diagram illustrating the principle of calculating installation errors based on the ideal and actual coordinates of a calibration model, as provided in an embodiment of this application.

[0018] Figure 9 This is a schematic block diagram of an installation error acquisition device provided in an embodiment of this application.

[0019] Figure 10 This is a schematic diagram of the structure of a 3D printer provided in an embodiment of this application. Detailed Implementation

[0020] To facilitate understanding of the technical solution of this application, the following points are provided.

[0021] In this application, "at least one" means one or more, and "more than one" means two or more. In the textual description of this application, the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0022] In this application, the terms "first," "second," and various numerical designations are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The sequence numbers of the processes below do not imply the order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0023] In this application, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or apparatus.

[0024] In this application, terms such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Embodiments or designs described as "exemplary" or "for example" should not be construed as being more preferred or advantageous than other embodiments or designs. The use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner to facilitate understanding.

[0025] In this application, "above" or "below" the second feature can mean that the first and second features are in direct contact, or that they are in indirect contact through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. Similarly, "below," "under," and "below" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0026] In this application, the terms “center,” “upper,” and “lower” indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0027] In this application, unless otherwise expressly specified and limited, the terms "installed," "fixed," "set," etc., shall be interpreted broadly. When an element is referred to as being "fixed to" or "set on" another element, it may be directly on the other element or there may be an intervening element. When an element is considered to be "connected" to another element, it may be directly connected to the other element or there may be an intervening element present.

[0028] In this application, unless otherwise expressly specified and limited, the term "point cloud" may be replaced by "point cloud data", "point cloud information", "point cloud coordinates", etc.

[0029] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0030] A 3D printer, also known as a three-dimensional printer, is a machine that uses rapid prototyping technology to construct three-dimensional objects based on digital model files and molding materials through a cumulative molding process. Due to its numerous advantages, 3D printing technology (or rapid prototyping technology) has been widely used in the product manufacturing industry.

[0031] Figure 1 This is a schematic diagram of the structure of a 3D printer provided in an embodiment of this application. For example... Figure 1As shown, taking a fused deposition modeling (FDM) 3D printer as an example, the 3D printer 100 includes a filament roll 101, a feeding device 102, an extruder 103, a printing nozzle 104, and a heated bed 105. The feeding device 102 can be part of the printing nozzle 103 and can be connected to the filament roll 101. In the actual printing process, the feeding device 102 can obtain filamentous material from the filament roll 101, melt the filamentous material through the extruder 103, and then eject it from the printing nozzle 104 to harden and deposit it on the heated bed 105. The materials used in 3D printing are generally thermoplastic materials. These materials have fluidity at high temperatures, as well as good mechanical properties and a certain viscosity, allowing them to be extruded in the extruder 103. For example, materials for 3D printers include polymers, low-melting-point metals, and other materials that can be formulated into fluid pastes (such as paste-like ceramics, high-melting-point metal powder mixtures, cement, etc.). In addition, the 3D printer 100 may also include a control module, such as a control chip or a processing chip. In some implementations, the control module may be integrated into the print head 103, serving as a control device for controlling the flow rate and speed of the material.

[0032] Figure 2 This is a top view of the 3D printer provided in the embodiments of this application. Figure 2 As shown, the 3D printer 200 includes a heated bed 210, a print head 220, and a data acquisition device 230. The print head 220 includes a print head center 250 and a camera 230, while the data acquisition device 230 includes a camera center 260. It can be seen that the print head 220 and the data acquisition device 230 are fixed together so that the data acquisition device 230 can move along with the print head 220.

[0033] Optionally, the acquisition device 230 can be a depth camera, a laser profilometer, or a lidar, etc. Among them, the laser profilometer, as a high-precision measuring device, can achieve a measurement accuracy of 50 micrometers, which can help the 3D printer achieve high-precision leveling, high-precision real-time print quality inspection, and other functions, thereby improving the level of intelligence.

[0034] Optionally, this application embodiment uses a laser profilometer as an example to illustrate the acquisition device 230. The laser profilometer can be installed next to the print head 220 via a mechanical connection (e.g., a bracket), or it can be installed inside the print head 220. This application does not impose any limitations. It should be understood that once the laser profilometer and print head 220 are installed, their relative poses are fixed, i.e., their relative deviations along the X, Y, and Z axes are fixed. Here, it is assumed that the X, Y, and Z axes are parallel to the movement directions of the three drive axes of the 3D printer. Furthermore, the laser profilometer can scan the heated bed 210 according to a preset trajectory to obtain relevant point cloud data.

[0035] It should be noted that the above Figure 1 and Figure 2 The schematic diagram of the 3D printer shown is merely an example for ease of understanding and does not constitute any limitation on the technical solution of this application. The relative distances between the components shown in the figure, as well as the shape and size of each component, are not necessarily the same as or scaled up to the actual object.

[0036] It is understandable that during the mechanical installation of the laser profilometer and the print head 220, there may be installation errors between the ideal and actual positions of the laser profilometer, including installation deviations and deflections. Installation deviations often reach the millimeter level, and deflections often reach the degree level. This is especially true for some open-type printers or models with user-assembled profilometer accessories, where the installation errors may be even greater. Furthermore, the installation errors of the laser profilometer are mostly different for each 3D printer. To address mechanical installation deviations, manual adjustment of the mounting screws is generally used for calibration. This method often requires repetition, is time-consuming and labor-intensive, and the calibration effect is not ideal. Therefore, obtaining an effective measurement of the laser profilometer's installation error is a problem that needs to be considered.

[0037] Based on the above-mentioned technical problems, this application provides an installation error acquisition scheme, which can effectively acquire the installation error of the laser profilometer, reduce the precision requirements of mechanical installation, facilitate the calibration of the subsequently acquired point cloud based on the installation deviation, and solve the problems of repeated manual calibration being time-consuming, labor-intensive, and having low accuracy, thereby improving the level of intelligence in 3D printing.

[0038] Below, in conjunction with Figure 3 This section provides a detailed explanation of how 3D printers work. For ease of understanding and description, a laser profilometer will be used as an example to illustrate the process.

[0039] Figure 3 This is a schematic diagram illustrating the working principle of the 3D printer provided in the embodiments of this application. For example... Figure 3 As shown, the laser profilometer 300 (e.g., could also be) Figure 2 The acquisition device 230 shown includes a line laser emitter 310, a camera 320 and a processing chip (not shown). The optical axis of the line laser emitter 310 is installed at a certain angle to the optical axis of the camera 320 or the optical axes are relatively parallel.

[0040] Optionally, the aforementioned line laser emitter 310 can be a single-line, multi-line, single-point, or multi-point laser source. This is because lasers have the advantages of high collimation and strong directionality, which can improve the accuracy and efficiency of calibration.

[0041] Optionally, the camera 320 can be a charge-coupled device (CCD), a complementary metal-oxide-semiconductor (CMOS), or other photosensitive elements capable of receiving infrared light, ultraviolet light, etc. Furthermore, the processing chip includes independent dedicated circuitry, such as a dedicated SOC chip, FPGA chip, or ASIC chip comprising a CPU, memory, and bus, or it can include general-purpose processing circuitry. For example, when the laser profilometer is integrated into smart terminals such as mobile phones, televisions, computers, scanners, and 3D printers, the processing circuitry in the terminal can serve as at least part of the processor.

[0042] Based on the principle of laser triangulation, a line laser emitter 310 projects a line laser onto the object under test 330. A camera 320 captures an image, and the center line of the line laser is extracted from the image. Then, using the light plane equation and the calibrated intrinsic and extrinsic parameters of the camera 320, the point cloud data of the object under test 330 in the world coordinate system is calculated. The change in Z-axis height is represented by pixel movement in the camera 320.

[0043] In the first implementation, the line laser emitter 310 in the laser profilometer 300 emits a line laser beam towards the object under test 330. This line laser beam forms a scalpel plane, and each scalpel plane corresponds to a scalpel plane equation, which can be obtained through calibration. The camera 320 in the laser profilometer 300 acquires the line laser beam reflected by the object under test 330, forming a line image on the imaging plane. Any point on the line laser beam in this line image is extracted, and a ray is formed from the optical center of the camera 320 and any point on the line laser beam. The three-dimensional coordinates of any point in the camera coordinate system can be determined by the intersection of this ray and the scalpel plane, thus obtaining the point cloud data of the object under test 330 in the camera coordinate system. Based on the calibrated intrinsic and extrinsic parameters of the camera 320, the point cloud data of the object under test 330 in the world coordinate system can then be obtained. In this world coordinate system, the origin can typically be defined as a corner point on the heated bed of the 3D printer. The X and Y axes are the sides intersecting the corner point of the calibration model, and are parallel to the X and Y axes of the 3D printer's motion directions, respectively. Optionally, the world coordinate system can be constructed in other ways, and this application does not impose any restrictions on this.

[0044] In the second implementation, the center line of the laser in the line image can be extracted using a center line extraction algorithm. Starting from the optical center of the camera 220, a ray is formed with any center point of the laser. The intersection of this ray with the laser blade plane is then determined, and the three-dimensional coordinates of any center point can be determined, thereby obtaining the point cloud data of the object to be measured 330.

[0045] Compared to the first implementation method, which directly calculates the point cloud data of the object under test 330 from any point on the line laser, this second implementation method obtains the corresponding center point with sub-pixel coordinates by calculating the center line on the line laser. Obtaining the point cloud data through the sub-pixel center point improves the accuracy of the point cloud data. Optionally, the point cloud data obtained in this implementation method can be point cloud data in the camera coordinate system.

[0046] Optionally, the point cloud data obtained by the above two implementation methods or other implementations can be filtered to improve the accuracy of the point cloud data.

[0047] Optionally, the camera 320 in the laser profilometer 300 can also be used independently to acquire two-dimensional images of the object under test 3300 in order to further obtain information such as line width, shape, and texture of the object under test 330.

[0048] It should be noted that, Figure 3The laser profilometer 300 shown is merely an example for ease of understanding and does not constitute a limitation on the technical solution of this application. Optionally, this application does not limit the number of line laser emitters 310 and cameras 320, the wavelength of the laser emitted by the line laser emitter 310, the angle between the optical axis of the line laser emitter 310 and the optical axis of the camera 320, or the orientation of the line laser emitter 310 and the camera 320. For example, scenarios where the camera 320 illuminates vertically downwards and the line laser emitter 310 illuminates obliquely downwards, or where the line laser emitter 310 illuminates vertically downwards and the camera 320 illuminates obliquely downwards, or where both the line laser emitter 310 and the camera 320 illuminate obliquely downwards, also fall within the protection scope of the technical solution of this application.

[0049] Furthermore, while the above description uses a laser profilometer as the acquisition device, in other embodiments, the acquisition device may also be a single-point rangefinder based on triangulation or single-point direct time-of-flight, a multi-line rangefinder, a speckle structured light / binocular camera, or an indirect time-of-flight camera based on floodlight / speckle / linear array, etc., all of which fall within the scope of protection of this application.

[0050] Below, in conjunction with Figure 2 and Figure 3 The necessity of calibrating camera intrinsic parameters and correcting installation deviations of the laser profilometer (i.e., the acquisition device) is illustrated with examples.

[0051] In one example, according to the laser profilometer 300 (corresponding to...) Figure 2 The intrinsic parameters of the camera 320, calibrated in the acquisition device 230 shown, can correct the distortion of the camera 320 lens. For example, in Figure 2 A calibration plate 240 is provided on the side of the heated bed 210, and the calibration plate 240 is parallel to the heated bed 210. Based on Figure 3 The laser profilometer 300 works by first acquiring a calibration image including the calibration plate 240, and then calibrating the image according to a preset calibration algorithm to obtain the intrinsic parameters of the camera 320. The preset calibration algorithm can be the Zhang Zhengyou calibration algorithm or other calibration algorithms.

[0052] In one example, the above Figure 3 The point cloud data obtained by the laser profilometer 300 shown is in the camera coordinate system O of the laser profilometer 300. C The following represents the camera coordinate system O. C The origin corresponds to the optical center of the laser profilometer 300. Assume a point cloud exists in the camera coordinate system O. C The coordinate position below is represented as (X C Y C Z CConsidering that during the acquisition of multiple frames of point cloud data by the mobile laser profilometer 300, the camera coordinate system O with the camera optical center of the laser profilometer 300 as the origin... C The camera coordinate system O has shifted relative to the world coordinate system, making it impossible to directly use the camera coordinate system O. C Since the point cloud data is converted to the world coordinate system, it is temporarily impossible to stitch multiple point clouds together. Each point cloud needs to be mapped to the same world coordinate system in order to stitch multiple point clouds together.

[0053] For example, since the coordinates of the print head 220 in the world coordinate system are known, each frame of point cloud data can be mapped to the print head coordinate system first, and then the mapped point cloud coordinates of each frame can be transformed to the world coordinate system to achieve multi-frame point cloud stitching.

[0054] For example, during the scanning process of a 3D printer, control Figure 2 The print head 220 moves according to a preset printing trajectory. Since the laser profilometer 300 is mounted on one side of the print head 220, it moves along with the print head 220 as the print head 220 moves. Based on this, the host computer can obtain the real-time coordinates of the print head 220 in the world coordinate system, for example (P_X). W , P_Y W P_Z W Then, by obtaining the relative pose between the laser profilometer 300 and the print head 220, the camera coordinate system O can be established. C Multi-frame point cloud data is mapped to the world coordinate system.

[0055] It should be understood that the relative pose between the laser profilometer 300 and the print head 220 depends on the mounting position of the laser profilometer 300 relative to the print head 220. Theoretically, the laser profilometer 300 is positioned parallel to the print head 220 (e.g., ...). Figure 2 As shown, the bottom of the laser profilometer 300 and the bottom of the print head 220 are on the same straight line. However, during the mechanical installation of the laser profilometer 300, installation errors may be introduced, resulting in the actual installation position of the laser profilometer 300 not being the ideal installation position. Therefore, it is necessary to calculate the installation error of the laser profilometer 300 in order to calibrate the point cloud data collected by the laser profilometer 300.

[0056] For example, the installation error of the laser profilometer 300 includes installation deviation and installation deflection. The installation deflection angle is a fixed value over a certain distance. Since the laser profilometer 300 operates at a fixed position relative to the heated bed 330, the fixed deviation corresponding to the installation deflection angle can be expressed as Δ = h·tanθ, where h is the distance between the laser profilometer 300 and the heated bed 210, and θ is the angle between the optical axis of the line laser emitter 310 and the optical axis of the camera 320. Based on this, the final installation error of the laser profilometer 300 is equivalent to the sum of the installation deviation and the fixed deviation Δ, meaning that the final installation deviation of the laser profilometer 300 can be calibrated.

[0057] Furthermore, during the coordinate system transformation, the distance along the Z-axis of the laser profilometer 300 represents the relative distance between the laser profilometer 300 and the object under test 340. This distance is a longitudinal distance and can be measured in real time by the laser profilometer 300; that is, this distance is independent of the relative pose between the laser profilometer 300 and the print head 220. Therefore, the Z-axis coordinate is calibrated using the calibration plate 240 to obtain the Z-axis coordinate in the world coordinate system, which can then be used to calibrate the installation deviations of the laser profilometer 300 along the X and Y axes.

[0058] Based on the above Figures 1 to 3 The following is combined with Figures 4 to 8 The method for obtaining and calibrating the installation error of the data acquisition device is described in detail.

[0059] First, the panoramic point cloud, background point cloud, and foreground point cloud involved in the embodiments of this application will be described. The background point cloud can refer to the point cloud data obtained by scanning a fixed area on an empty heated bed before printing by the 3D printer. The panoramic point cloud can refer to the point cloud data obtained by scanning the area including the fixed area of ​​the heated bed and the calibration model after printing a calibration model on a fixed area by the 3D printer. The foreground point cloud can refer to the point cloud data including only the calibration model. It should be understood that the point cloud data involved in the embodiments of this application can be three-dimensional coordinate information, color information, light intensity information, etc. Optionally, to reduce the computational load, the background point cloud data and the panoramic point cloud can be collected with the same density.

[0060] Figure 4 This is a flowchart of an installation error acquisition and calibration method 400 provided in an embodiment of this application, applied to a 3D printer, such as... Figure 2 As shown, the 3D printer 200 includes a data acquisition device 230, a heated bed 210, and a print head 220. Optionally, the 3D printer 200 may also include a main control chip, which can control the execution of the installation error acquisition and calibration method. Figure 4 As shown, the method includes the following steps.

[0061] S410 controls the acquisition device to scan a fixed area on the heated bed to obtain a background point cloud.

[0062] For example, taking the laser profilometer 300 as the acquisition device 230, a fixed area is selected on the heated bed 210. The main control chip can control the laser profilometer 300 to scan the fixed area. Specifically, the laser emitter 310 in the laser profilometer 300 is controlled to emit a first beam to the fixed area. The first beam is reflected by the fixed area to the camera 320 in the laser profilometer 300, so that the camera 320 acquires the reflected first beam to generate a corresponding first image. Then, the first image is processed to obtain the background point cloud corresponding to the fixed area.

[0063] S420 controls the print head to print a calibration model on a fixed area according to preset parameters.

[0064] For example, the main control chip can control the print head 220 to print a calibration model on a fixed area of ​​the heated bed 210 according to preset parameters. This calibration model can be determined by preset parameters. For example, the preset parameters include at least one of the following: the length of the calibration model, the height of the calibration model, or the coordinate information of the calibration model on the heated bed 210. It should be understood that the purpose of printing the calibration model on a fixed area is to provide a reference coordinate system, facilitating subsequent determination of the installation error of the acquisition device.

[0065] For example, the calibration model can have various styles, such as single-point graphics, circles, rings, squares, triangles, or triangular prisms. In the embodiments of this application, the design of the calibration model style can consider one or more of the following aspects: easy to print quickly, high printing accuracy, easy to extract point coordinates, etc. The point coordinates can be the coordinates of the geometric center of a circle or the coordinates of the corner points of a triangle; this application does not limit this.

[0066] Figure 5 These are the front view, left view, and top view of a calibration model provided in this application embodiment. Taking a triangular prism as an example, as... Figure 5 As shown, the top view of the triangular prism is an isosceles right triangle with a leg length of 20mm. The front view and left view of the triangular prism are both rectangles, with corresponding side lengths of 20mm and 0.2mm respectively. It should be understood that... Figure 5 The provided calibration model is merely an example to facilitate understanding of the scheme, and this application does not impose specific limitations on the shape and calculation method of the calibration model.

[0067] S430 controls the acquisition device to collect panoramic view cloud data, including fixed areas and calibration models.

[0068] For example, based on step S420, after printing the calibration model in a fixed area on the heated bed 210, the laser profilometer 300 can be moved above the calibration model. For instance, the distance between the laser profilometer 300 and the calibration model is greater than a first threshold, ensuring that the field of view of the camera 320 in the laser profilometer 300 can completely cover the calibration model, so that the camera 320 can acquire the panoramic cloud. Further, the main control chip can control the laser emitter 310 in the laser profilometer 300 to emit a second beam to the fixed area including the calibration model. The second beam is reflected by the fixed area including the calibration model to the camera 310 in the laser profilometer 300, so that the camera 310 acquires the reflected second beam to generate a corresponding second image. This second image is then processed to obtain a panoramic cloud including the calibration model and the fixed area.

[0069] Optionally, the first threshold can be a preset value set based on experience. For example, the first threshold can be a threshold determined based on factors such as the application scenario, exposure time, or the accuracy of the collected information.

[0070] S440 processes the entire point cloud and background point cloud to obtain the foreground point cloud containing the calibration model.

[0071] Processing the overall viewpoint cloud based on the background point cloud allows for the separation of the foreground point cloud containing only the calibration model and the background point cloud containing only a fixed region from the overall viewpoint cloud. This application illustrates the separation of the foreground point cloud containing only the calibration model and the background point cloud containing only a fixed region from the overall viewpoint cloud through various implementation methods, as detailed below:

[0072] Method 1: Least squares method.

[0073] For example, the least squares method is used to fit the background point cloud to solve the equation of the straight line, and the distance from each point in the panoramic point cloud to the straight line is calculated. The background point cloud and the foreground point cloud are separated from the panoramic point cloud based on the distance. Point clouds whose distance from the point to the straight line is greater than a preset distance threshold belong to the calibration model, that is, the point cloud is classified as a foreground point cloud containing the calibration model. Point clouds whose distance from the point to the straight line is less than the preset distance threshold belong to the fixed area on the heated bed 210, that is, the point cloud is classified as the background point cloud.

[0074] Figure 6 This is a schematic diagram illustrating the linear fitting of a background point cloud collected from a fixed area on an empty heated bed 210 under both tilted and non-tilted conditions, as provided in an embodiment of this application. Figure 6As shown in (a), taking the heated bed 210 with a certain degree of inclination as an example, the least squares method is used to solve for the fitted straight line equation on the background point cloud in a fixed area. For example, the thin line in the middle can represent the fitted straight line equation, i.e., z = kx + b, and the thin lines on both sides represent the boundary lines that are all at a distance T from the fitted straight line. Similarly, as Figure 6 As shown in (b), taking the non-inclined heated bed 210 as an example, the least squares method is used to solve the fitted straight line equation for the background point cloud on the fixed area, for example, z = 2500. The thin lines on both sides represent the boundary lines that are all T away from the fitted straight line.

[0075] Furthermore, based on Figure 6 The fitted line equation is obtained, and the distance from each point in the overall point cloud to the fitted line is calculated. If the distance from the point to the line is greater than a threshold, the point cloud is a foreground point cloud containing the calibration model. If the distance from the point to the line is less than the threshold, the point cloud is a background point cloud containing a fixed region.

[0076] Method 2: Point cloud clustering.

[0077] For example, two initial plane equations are set, and the distance from each point cloud in the panoramic view cloud to these two planes is calculated. Based on the distance, it is determined which plane each point in the panoramic view cloud is closer to, and each point in the panoramic view cloud is classified into the two planes based on the distance from the point to the plane. The plane equations are updated according to the points classified into each plane to minimize the distance from the point to the plane, and the state of the point cloud belonging to the plane is updated. This process continues until the sum of the distances from each classified point in the panoramic view cloud to its respective plane is minimized, thus obtaining two planes with different heights. The point cloud of one plane is the foreground point cloud, and the point cloud of the other plane is the background point cloud. If two planes with different heights are obtained, the higher plane is the plane of the calibration model, and the point cloud belonging to this plane is the foreground point cloud containing the calibration model; the lower plane is the plane of the fixed region, and the point cloud belonging to this plane is the background point cloud containing the fixed region.

[0078] Method 3: Planar segmentation.

[0079] For example, the least squares method is used to process the background point cloud to solve for the plane equation with the smallest error. The distance from each point on the panoramic point cloud to the plane is calculated. If the distance is positive (i.e., the point cloud is above the plane), the point cloud is determined to be a foreground point cloud containing the calibration model; if the distance is negative (i.e., the point cloud is below the plane), the point cloud is determined to be a background point cloud containing a fixed region.

[0080] Method 4: Difference method.

[0081] For example, the foreground point cloud is obtained by subtracting the point cloud coordinates corresponding to the background point cloud one by one.

[0082] Method 5: Threshold segmentation.

[0083] For example, a height threshold is set based on the height of the hotbed obtained from the background point cloud, and the foreground point cloud and background point cloud are separated by the height threshold. For instance, a height threshold is preset to be the average height of the hotbed 210 obtained based on the background point cloud. For example, point clouds in the full-view cloud that are greater than the height threshold are identified as foreground point clouds containing the calibration model, and point clouds in the full-view cloud that are less than the height threshold are identified as background point clouds containing a fixed region.

[0084] It should be noted that methods 1 to 4 described above can be applied to cases where the heated bed 210 is tilted or not, and method 5 can be applied to cases where the heated bed 210 is not tilted. It should be understood that the implementation methods provided above are merely examples for ease of understanding and should not constitute any limitation on the technology of this application.

[0085] S450, based on the foreground cloud and the ideal installation position of the data acquisition device, determines the installation error of the actual installation position of the data acquisition device relative to the ideal installation position.

[0086] For example, the main control chip can determine the installation error of the acquisition device based on the foreground point cloud determined in step S440 above and the pre-stored ideal installation position of the acquisition device. The installation error of the acquisition device is determined by comparing the actual installation position and the ideal installation position of the acquisition device.

[0087] Figure 7 This is a schematic diagram illustrating the linear segmentation of the foreground cloud containing the calibration model under both tilted and non-tilted conditions of the heated bed 210, as provided in an embodiment of this application. Exemplary, Figure 7 The heated bed 210 shown in (a) has a certain degree of inclination. Figure 7 As shown in (b), the heated bed 210 is in a non-tilted state. The two sides of the calibration model correspond to the steps of the foreground and background point clouds, respectively. That is, the points where the two sides of the calibration model intersect with the emitted laser line of the laser profilometer 300 are the endpoints of the two sides of the calibration model (i.e., the right-angled side and the hypotenuse), for example, denoted as (X1, Y1) and (X2, Y2), respectively. The ideal coordinates and actual coordinates of these endpoints (X1, Y1) and (X2, Y2) are subtracted. The calculated difference is used as the installation error of the laser profilometer 300 relative to its theoretical installation position. This installation error is then used to calibrate the point cloud data subsequently acquired by the laser profilometer 300, ensuring print quality.

[0088] Figure 8 This is a schematic diagram illustrating the principle of calculating installation errors based on the ideal and actual coordinates of a calibration model, as provided in an embodiment of this application. Figure 2 Taking the 3D printer shown as an example, such as Figure 8As shown, it is assumed that the coordinate system of the laser profilometer and the coordinate system of the print head are aligned, i.e., the horizontal coordinate is the x-axis and the vertical coordinate is the y-axis. Since the relative pose between the laser profilometer 230 and the print head 220 is fixed, the theoretical mechanical offset between them is known.

[0089] For example, (D) x D y )=(X lky Y lky )-(X p Y p ). Among them, (D x D y (X) represents the theoretical mechanical installation offset between the laser profilometer 230 and the print head 220. lky Y lky () represents the coordinates of laser profilometer 230, (X) p Y p () indicates the coordinates of print head 220.

[0090] like Figure 8 As shown, if the print head 220 is moved to coordinate (C... x +D x C y +D y At this point, assuming no installation error, that is, the ideal position of the laser profilometer 230 is at coordinate (C). x C y At position (C), and at coordinate (C) x C y The value is also known. However, in actual installation, the actual installation position of the laser profilometer 230 often differs from the theoretical installation position (D). x′ D y′ This makes the actual position of the laser profilometer 330 at this time at coordinates (C). x +D x′ C y +D y′ Therefore, it is necessary to calculate the installation error (D) at this location. x′ D y′ ), to pass the installation error (D) x′ D y′ This is used to calibrate the point cloud data subsequently acquired by the laser profilometer 300 to ensure print quality.

[0091] Specifically, the deviation of the laser profilometer 300 on the x-axis is calibrated by using the endpoints of the right-angled side of the calibration model, and the deviation of the laser profilometer 300 on the y-axis is calibrated by using the endpoints of the hypotenuse of the calibration model.

[0092] In one example, based on the pre-stored ideal position of the laser profilometer 300 and the geometric properties of the calibration model, assuming the calibration model is an equilateral right triangle with known side lengths, the ideal coordinates of the endpoints of the right-angled sides of the calibration model in the ideal coordinate system of the laser profilometer 300 (i.e., the intersection of the right-angled sides of the calibration model and the theoretical laser line) are determined as (X... gt Y gt However, the actual coordinates of the endpoint of the right-angled side (i.e., the intersection of the right-angled side of the calibration model and the actual laser line) in the actual coordinate system of the laser profilometer 300 are (X1, Y1), then D x′ =X1-X gt .

[0093] In one example, based on the x-axis deviation obtained above, the hypotenuse endpoint (X2, Y2) in the actual coordinate system of the laser profilometer 300 needs to be calibrated on the x-axis first, so as to obtain the calibrated x-coordinate X in the ideal coordinate system of the laser profilometer 300. 2′ =X2+D x′ Then, based on the equation of the straight line y = -x of the hypotenuse of the calibration model in the ideal coordinate system of the laser profilometer 300, the theoretical value Y of the y-coordinate in the ideal coordinate system of the laser profilometer 300 is calculated. gt =-X 2′ The installation deviation of the laser profilometer 300 on the y-axis is equal to the theoretical value of y minus the actual measured value, i.e., D. y′ =Y gt -Y2=-X 2′ -Y2=-X2-D x′ -Y2.

[0094] In summary, the installation errors of the laser profilometer 300 on the x-axis and y-axis are D respectively. x′ and D y′ This data is then used to calibrate the point cloud data subsequently acquired by the laser profilometer 300.

[0095] It should be noted that, based on the above steps S410 to S450, the installation error of the acquisition device can be effectively obtained, enabling the calibration of the acquisition device. This calibration can then be applied to a 3D printer containing the acquisition device (e.g., [missing information]). Figures 1 to 3 After collecting point cloud data (as shown), the collected point cloud data can be calibrated based on the installation error obtained above to ensure the quality and stability of the 3D printer.

[0096] Optionally, steps S410 to S450 can be performed before each point cloud data acquisition (e.g., acquiring the first point cloud in step S460). Alternatively, steps S410 to S450 can be performed periodically, for example, once every 10 point cloud data acquisitions. In other words, this application does not specifically limit the conditions for obtaining the installation error of the acquisition device or the number of times it is used.

[0097] Optionally, after performing the above steps S410 to S450, the calibrated point cloud data can be obtained by performing steps S460 and S470.

[0098] S460, control the acquisition device to acquire the first point cloud, the coordinates of which are (X, Y, Z).

[0099] For example, by Figures 1 to 3 The 3D printer shown here and its working principle are explained. The main control chip can control the acquisition device to acquire the first point cloud. For the specific implementation method, please refer to the relevant instructions above, which will not be repeated here.

[0100] S470 calibrates the first point cloud based on the installation error to obtain the calibrated second point cloud.

[0101] For example, if the installation error of the laser profilometer 300 on the x-axis and y-axis is D respectively. x′ and D y′ Then the coordinates of the calibrated second point cloud are (X+D) x′ Y+D y′ In other words, by adding the coordinates x and y of the first point cloud acquired by the laser profilometer 300 to the installation errors of the laser profilometer 300 in the x-axis and y-axis directions, the calibration of the first point cloud, i.e., the second point cloud, can be achieved.

[0102] The above text combined Figures 1 to 8 The method for obtaining installation errors in the embodiments of this application has been described in detail. The following will combine... Figure 9 and Figure 10 This application describes an error calibration apparatus according to embodiments of the present application. It should be understood that the description of the apparatus embodiments corresponds to the description of the method embodiments; therefore, any parts not described in detail can be referred to the foregoing method embodiments.

[0103] Figure 9 This is a schematic block diagram of an installation error acquisition device provided in an embodiment of this application. Figure 9As shown, the device 1000 may include a control unit 1010 and a processing unit 1020. The control unit 1010 is used to control the acquisition device to scan a fixed area on the heated bed to obtain a background point cloud; control the printing nozzle to print a calibration model on the fixed area according to preset parameters; control the acquisition device to acquire a panoramic point cloud containing the fixed area and the calibration model; the processing unit 1020 is used to process the panoramic point cloud and the background point cloud to obtain a foreground point cloud containing the calibration model; and determine the installation error of the actual installation position of the acquisition device relative to the ideal installation position based on the foreground point cloud and the ideal installation position of the acquisition device.

[0104] It should be understood that the device 1000 here is embodied in the form of a functional unit. The term "unit" here may refer to application-specific integrated circuits (ASICs), electronic circuits, processors (e.g., shared processors, proprietary processors, or group processors) and memories for executing one or more software or firmware programs, combined logic circuits, and / or other suitable components that support the described functions.

[0105] The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above function; for example, a processing unit can be replaced by a processor to perform the processing operations in the above method embodiments.

[0106] Furthermore, the aforementioned processing unit can be a processing circuit. In embodiments of this application, Figure 9 The device mentioned can be the 3D printer described in the preceding embodiments, or it can be a chip or a chip system, such as a system on a chip (SoC). The processing unit is a processor, microprocessor, or integrated circuit integrated on the chip. No limitation is made here.

[0107] Figure 10 This is a schematic block diagram of the 3D printer provided in an embodiment of this application. Figure 10 As shown, the 3D printer 2000 includes a heated bed 2010, a print head 2020, a data acquisition device 2030, and a main control chip 2040. The print head 2020 is used to print a calibration model on a fixed area of ​​the heated bed 2010. The data acquisition device 2030 is used to acquire background point clouds containing only the heated bed 2010 and panoramic point clouds containing both the heated bed 2010 and the calibration model. The main control chip 2040 is used to control the print head 2020 and the data acquisition device 2030 according to the error acquisition method provided in one or more embodiments of this application, and to process the background point clouds and panoramic point clouds acquired by the data acquisition device 2030 to obtain the installation error of the actual installation position of the data acquisition device 2030 relative to the ideal installation position.

[0108] For example, the main control chip 2040 is used to control the acquisition device 2030 to scan a fixed area on the heated bed 2010 to obtain a background point cloud; control the printing nozzle 2020 to print a calibration model on the fixed area according to preset parameters; control the acquisition device 2030 to acquire a panoramic point cloud containing the fixed area and the calibration model; process the panoramic point cloud and the background point cloud to obtain a foreground point cloud containing the calibration model; and determine the installation error of the actual installation position of the acquisition device relative to the ideal installation position based on the foreground point cloud and the ideal installation position of the acquisition device 2030.

[0109] In one embodiment, the main control chip 2040 includes a processor for sending control signals to control various components, and also for executing the installation error acquisition method provided in the embodiments of this application. Optionally, as Figure 10 As shown, the main control chip 2040 may further include a memory. The main control chip 2040 can call and run the installation error acquisition program from the memory to implement the method in this embodiment. The memory may be a separate device independent of the main control chip, or it may be integrated into the main control chip.

[0110] Optionally, the memory may include read-only memory and random access memory, and provide instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information. The main control chip 2040 can be used to execute instructions stored in the memory, and when the main control chip 2040 executes instructions stored in the memory, the main control chip 2040 is used to perform various steps and / or processes in the above-described installation error acquisition method.

[0111] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0112] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The processor in the embodiments of this application can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0113] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0114] Optionally, embodiments of this application also provide a chip, including a processor, which can call and run computer programs from memory to implement the methods in embodiments of this application.

[0115] Optionally, embodiments of this application also provide a computer-readable storage medium for storing a computer program that causes a computer to perform the methods described in the embodiments of this application.

[0116] Optionally, embodiments of this application also provide a computer program product, including computer program instructions that cause a computer to execute the methods in the embodiments of this application.

[0117] Optionally, embodiments of this application also provide a computer program. The computer program causes a computer to perform the methods described in the embodiments of this application.

[0118] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0119] Although this application has been described with reference to preferred embodiments, various modifications can be made thereto and components can be replaced with equivalents without departing from the scope of this application. In particular, the technical features mentioned in the various embodiments can be combined in any manner, provided there is no structural conflict. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for obtaining installation error, characterized in that, An application to a 3D printer, the 3D printer including a pickup device, a heated bed, and a print head, wherein the relative pose of the pickup device and the print head is fixed, and the pickup device moves with the print head, the method includes: The acquisition device is controlled to scan a fixed area on the heated bed to obtain a background point cloud; The print head is controlled to print a calibration model on the fixed area according to preset parameters; The acquisition device is controlled to acquire a panoramic cloud containing the fixed area and the calibration model. The panoramic point cloud and the background point cloud are processed to obtain a foreground point cloud that contains only the calibration model; Based on the foreground cloud and the ideal installation position of the acquisition device, determine the installation error of the actual installation position of the acquisition device relative to the ideal installation position.

2. The method according to claim 1, characterized in that, The method further includes: The acquisition device is controlled to acquire a first point cloud, the coordinates of which are (X, Y, Z). The first point cloud is calibrated based on the installation error to obtain a calibrated second point cloud, the coordinates of which are: ; in, This indicates the installation error of the acquisition device in the x-axis direction. This indicates the installation error of the acquisition device in the y-axis direction.

3. The method according to claim 1 or 2, characterized in that, The process of processing the panoramic point cloud and the background point cloud to obtain a foreground point cloud containing only the calibration model includes: The difference between the total viewpoint cloud and the background point cloud is calculated to obtain a foreground viewpoint cloud that contains only the calibration model.

4. The method according to claim 1 or 2, characterized in that, The process of processing the panoramic point cloud and the background point cloud to obtain a foreground point cloud containing only the calibration model includes: Using the background point cloud, separate the foreground point cloud containing only the calibration model and the background point cloud containing only the fixed region from the overall view cloud.

5. The method according to claim 4, characterized in that, The step of separating the foreground point cloud containing only the calibration model and the background point cloud containing only the fixed region from the panoramic point cloud using the background point cloud includes: The least squares method is used to fit the background point cloud to solve the equation of the straight line, and the distance from each point in the panoramic point cloud to the straight line is calculated. Based on the distance, the background point cloud and the foreground point cloud are separated from the panoramic point cloud; Point clouds where the distance from a point to a line is greater than a preset distance threshold are classified as foreground point clouds; and point clouds where the distance from a point to a line is less than a preset distance threshold are classified as background point clouds.

6. The method according to claim 4, characterized in that, The step of separating the foreground point cloud containing only the calibration model and the background point cloud containing only the fixed region from the panoramic point cloud using the background point cloud includes: Set two initial plane equations and calculate the distance from each point in the panoramic view cloud to the two planes; Each point in the panoramic view cloud is classified into the two planes based on the distance from the point to the plane; The equations of the two initial planes are updated based on the points classified into each plane to minimize the distance from the points to the planes. At the same time, the state of the points belonging to the planes is updated until the sum of the distances from each point classified in the panoramic view cloud to its corresponding plane is minimized, resulting in two planes with different heights. In this context, the point cloud on one plane is the foreground point cloud, and the point cloud on the other plane is the background point cloud.

7. The method according to claim 4, characterized in that, The step of separating the foreground point cloud containing only the calibration model and the background point cloud containing only the fixed region from the panoramic point cloud using the background point cloud includes: The background point cloud is processed using the least squares method to solve for a plane equation with the smallest error; Calculate the distance from each point on the panoramic point cloud to the plane. If the distance from the point to the plane is positive, then the point is classified as the foreground point cloud; if the distance from the point to the plane is negative, then the point is classified as the background point cloud.

8. The method according to claim 4, characterized in that, The step of separating the foreground point cloud containing only the calibration model and the background point cloud containing only the fixed region from the panoramic point cloud using the background point cloud includes: Based on the background point cloud, a height threshold is set to obtain the hotbed height, and the foreground point cloud and the background point cloud are separated from the panoramic point cloud using the height threshold. Specifically, point clouds in the panoramic view cloud that are higher than the height threshold are defined as the foreground point clouds, and point clouds in the panoramic view cloud that are lower than the height threshold are defined as the background point clouds.

9. The method according to any one of claims 1 to 8, characterized in that, The calibration model includes at least one right-angled side and one hypotenuse; determining the installation error of the actual installation position of the acquisition device relative to the ideal installation position based on the foreground point cloud and the ideal installation position of the acquisition device includes: Determine the ideal coordinates of the endpoints of the right-angled sides of the calibration model in the ideal coordinate system of the acquisition device, and determine the actual coordinates of the endpoints of the right-angled sides of the calibration model in the actual coordinate system of the acquisition device; The installation error of the acquisition device in the x-axis direction is determined based on the ideal coordinates of the endpoints of the right-angled sides and the actual coordinates of the endpoints of the right-angled sides.

10. The method according to claim 9, characterized in that, The method further includes: Determine the actual coordinates of the hypotenuse endpoint of the calibration model in the actual coordinate system of the acquisition device; Based on the actual coordinates of the endpoint of the hypotenuse and the installation error of the acquisition device in the x-axis direction, the installation error of the acquisition device in the y-axis direction is determined.

11. An installation error acquisition device, characterized in that, include: The control unit is used to control the acquisition device to scan a fixed area on the heated bed to obtain a background point cloud; control the printing nozzle to print a calibration model on the fixed area according to preset parameters; and control the acquisition device to acquire a panoramic point cloud including the fixed area and the calibration model. The processing unit is used to process the panoramic point cloud and the background point cloud to obtain a foreground point cloud containing only the calibration model; and to determine the installation error of the actual installation position of the acquisition device relative to the ideal installation position based on the foreground point cloud and the ideal installation position of the acquisition device. The relative positions of the acquisition device and the print head are fixed, and the acquisition device moves with the print head.

12. A 3D printer, characterized in that, include: The system includes a data acquisition device, a heated bed, a print head, and a main control chip. The relative positions of the data acquisition device and the print head are fixed, and the data acquisition device moves with the print head. The print head is used to print a calibration model in a fixed area on the heated bed; The acquisition device is used to acquire a foreground cloud including the heated bed and a total view cloud including the heated bed and the calibration model; The main control chip is used to control the print head and the acquisition device, and to process the foreground point cloud and the total point cloud according to the installation error acquisition method as described in any one of claims 1 to 10, so as to obtain the installation error of the actual installation position of the acquisition device relative to the ideal installation position.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program that, when run on a computer, causes the computer to perform the method as described in any one of claims 1 to 10.

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