Image vision servo precision compensation method for high-precision assembly of industrial robots

Abstract

The embodiment of the application discloses an image visual servo precision compensation method for high-precision assembly of an industrial robot, relates to the field of high-precision assembly of a robot, and can improve the assembly precision of the industrial robot based on image visual servo. The application controls the movement of the robot by analyzing the change of the feature hole on the image, continuously compensates through servo, finally ensures that the upper and lower workpieces to be assembled keep the feature hole alignment, and realizes the high-precision assembly of the industrial robot. The application can effectively reduce the influence of the absolute positioning error of the robot and the system calibration error on the assembly precision of the robot, and can meet the relative pose precision requirement in the butt joint assembly process of large workpieces.

Description

Technical Field

[0001] This invention relates to the field of high-precision robot assembly, and more particularly to an image vision servo accuracy compensation method for high-precision assembly of industrial robots. Background Technology

[0002] Industrial robots, with their high flexibility, high precision, and high efficiency, are widely used in assembly fields such as aerospace, automotive, and electronics, improving product quality and achieving automated assembly.

[0003] However, the aerospace field has very high requirements for assembly accuracy. When industrial robots are docking and assembling, the absolute positioning error of the robot body and the system calibration error are coupled at each layer, making it difficult to meet the assembly accuracy requirements. Therefore, how to improve the assembly accuracy of industrial robots has become an issue that needs in-depth research. Summary of the Invention

[0004] The embodiments of the present invention provide an image vision servo accuracy compensation method for high-precision assembly of industrial robots, which can improve the assembly accuracy of industrial robots based on image vision servoing.

[0005] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0006] S1, perform base coordinate system calibration and hand-eye calibration on the main robot (7), and perform coordinate system calibration on the main robot (7) based on the base coordinate system calibration and hand-eye calibration, and then perform camera calibration on the small field of view binocular vision measurement device (2);

[0007] S2, use a small field-of-view binocular vision measurement device (2) to detect the feature holes of the workpiece (5) to be assembled, and calculate the theoretical UV position of the feature holes of the workpiece to be assembled under the left camera of the small field-of-view binocular vision measurement device (2).

[0008] S3, move the main robot (7) to the designated position, and then use the small field of view binocular vision measurement device (2) to detect the feature hole of the workpiece to be assembled, and obtain the actual UV position of the feature hole under the left camera of the small field of view binocular vision measurement device (2) and the actual three-dimensional position of the feature hole. In the designated position, the feature hole of the workpiece (8) to be assembled, which is gripped by the end gripper (6) of the main robot (7), is located within the visual detection range of the small field of view binocular vision measurement device (2).

[0009] S4. Based on the camera calibration results in step S1, the theoretical UV position and actual UV position of the feature hole under the left camera of the small field-of-view binocular vision measurement device (2), calculate the image Jacobian matrix to obtain the pose change of the workpiece to be assembled under the coordinate system of the left camera of the small field-of-view binocular vision measurement device (2).

[0010] S5, convert the obtained pose change amount into the flange pose change amount in the base coordinate system of the main robot (7), and drive the main robot (7) to execute the flange pose change amount to move the workpiece to be assembled to the theoretical position.

[0011] S6, the feature hole of the workpiece (8) to be assembled is detected again to obtain the actual UV position and three-dimensional actual position of the feature hole of the workpiece to be assembled under the left camera of the small field of view binocular vision measurement device (2).

[0012] S7. Based on the theoretical UV position obtained in step S2 and the actual UV position obtained in step S6, the robot's pose is compensated to obtain the compensated UV. Then, steps S4 to S7 are executed repeatedly until the difference between the theoretical UV and the actual UV meets a fixed threshold.

[0013] The image-based visual servo accuracy compensation method for high-precision assembly of industrial robots provided in this invention analyzes changes in feature holes in an image to control the robot's movement. Through continuous servo compensation, it ultimately ensures that the feature holes of the upper and lower workpieces to be assembled remain aligned, thus achieving high-precision assembly of the industrial robot. This invention effectively reduces the impact of robot absolute positioning errors and system calibration errors on robot assembly accuracy, and can meet the relative pose accuracy requirements during the docking and assembly of large workpieces. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the system architecture provided in an embodiment of the present invention;

[0016] Figure 2 This is a schematic diagram of the method flow provided in an embodiment of the present invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Embodiments of the present invention will be described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in the specification of the present invention means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or couplings. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0018] This invention provides an image vision servo accuracy compensation method for high-precision assembly of industrial robots, such as... Figure 2 As shown, it includes:

[0019] S1, perform base coordinate system calibration and hand-eye calibration on the main robot (7), and perform coordinate system calibration on the main robot (7) based on the base coordinate system calibration and hand-eye calibration, and then perform camera calibration on the small field of view binocular vision measurement device (2);

[0020] S2, use a small field-of-view binocular vision measurement device (2) to detect the feature holes of the workpiece (5) to be assembled, and calculate the theoretical UV position of the feature holes of the workpiece to be assembled under the left camera of the small field-of-view binocular vision measurement device (2).

[0021] S3, move the main robot (7) to the designated position, and then use the small field of view binocular vision measurement device (2) to detect the feature hole of the workpiece to be assembled, and obtain the actual UV position of the feature hole under the left camera of the small field of view binocular vision measurement device (2) and the actual three-dimensional position of the feature hole.

[0022] In the specified position, the feature hole of the workpiece (8) to be assembled is grasped by the end gripper (6) of the main robot (7) and is located within the visual detection range of the small field-of-view binocular vision measurement device (2), specifically within the depth range.

[0023] S4. Based on the camera calibration results in step S1, the theoretical UV position and actual UV position of the feature hole under the left camera of the small field-of-view binocular vision measurement device (2), calculate the image Jacobian matrix to obtain the pose change of the workpiece to be assembled under the coordinate system of the left camera of the small field-of-view binocular vision measurement device (2).

[0024] S5, convert the obtained pose change amount into the flange pose change amount in the base coordinate system of the main robot (7), and drive the main robot (7) to execute the flange pose change amount to move the workpiece to be assembled to the theoretical position.

[0025] S6, the feature holes of the workpiece (8) to be assembled are detected again to obtain the actual UV position and three-dimensional actual position of the feature holes of the workpiece to be assembled under the left camera of the small field of view binocular vision measurement device (2); specifically, after the main robot finishes moving, the small field of view binocular measurement device (2) is used again to obtain the UV position of the feature holes of the workpiece (8) to be assembled in the image.

[0026] S7. Based on the theoretical UV position obtained in step S2 and the actual UV position obtained in step S6, the robot's pose is compensated to obtain the compensated UV. Then, steps S4 to S7 are executed repeatedly until the difference between the theoretical UV and the actual UV meets a fixed threshold.

[0027] The hardware configuration of the industrial robot assembly accuracy compensation system established in this embodiment includes a main robot (7), an auxiliary robot (3), a small field-of-view binocular vision measurement device (2), an auxiliary light source (4), a large field-of-view binocular vision measurement device (1), workpieces to be assembled (5, 8), fixtures for fixing the workpieces, grippers (6), and supporting structural components to complete the system hardware construction. Among them, the end of the main robot (7) is connected to the gripper (6), which is used to grip the workpiece (8) to be assembled; the end of the auxiliary robot (3) is connected to the small field-of-view binocular vision measurement device (2) and the auxiliary light source (4). The large field-of-view binocular vision measurement device (1) is installed on the top of the column. The observation range of the large field-of-view binocular vision measurement device (1) covers the activity space of the auxiliary robot (3) and the main robot (7). The column stands vertically on the worktable; the workpiece (5) to be assembled is fixed on the worktable by the fixture and remains stationary. During the equipment debugging process, the end position of the auxiliary robot can be determined by manual teaching to ensure that the small field-of-view binocular vision sensor connected to the end can observe the feature holes of the lower workpiece separately without interfering with the upper workpiece held by the main robot. After that, the end position of the auxiliary robot remains stationary. For example, the main robot (7) is calibrated using the large field-of-view binocular vision measurement device (1), and the hand-eye calibration of the main robot (7) is completed using the large field-of-view binocular vision measurement device (1) and the small field-of-view binocular vision measurement device (2). Based on the completion of the base coordinate system calibration and the hand-eye calibration, the coordinate system calibration of the camera and the main robot (7) is completed, and finally the camera calibration of the small field-of-view binocular vision sensor is performed.

[0028] In this embodiment, S1 includes: calibrating the base coordinate system of the main robot (7) using a large field-of-view binocular vision measurement device (1) to obtain the transformation matrix of the base coordinate system of the large field-of-view binocular vision measurement device (1) relative to the main robot (7); and performing hand-eye calibration on the main robot (7) using the large field-of-view binocular vision measurement device (1) and the small field-of-view binocular vision measurement device (2); wherein, based on the completion of the base coordinate system calibration and the hand-eye calibration, the coordinate system calibration of the camera and the main robot (7) is completed, and finally the camera calibration of the small field-of-view binocular vision sensor is performed. The camera calibration of the small field-of-view binocular vision measurement device (2) includes: performing camera calibration on the small field-of-view binocular vision sensor in the small field-of-view binocular vision measurement device (2) to obtain the left camera intrinsic parameter matrix and camera distortion parameters.

[0029] Specifically, by using a large field-of-view binocular vision measurement device to calibrate the base coordinate system of the main robot, the transformation matrix of the large field-of-view binocular vision measurement device E-track relative to the base coordinate system of the main robot can be obtained, i.e. The hand-eye calibration of the main robot was completed using both a large field-of-view binocular vision measurement device and a small field-of-view binocular vision measurement device. After completing the base coordinate system calibration and hand-eye calibration, complete the coordinate system calibration of the camera and the main robot, that is... Finally, camera calibration of the small field-of-view binocular vision sensor was performed, and the intrinsic parameter matrix M of the left camera was obtained. cameraL Camera distortion parameter dist L .

[0030] In this embodiment, S2 includes:

[0031] S21, using a small field-of-view binocular vision measurement device (2), the feature holes of the workpiece (5) to be assembled are detected, and the three-dimensional coordinates of the feature holes relative to the camera are obtained. Then, establish the workpiece coordinate system of the workpiece to be assembled (5), including:

[0032]

[0033]

[0034] AxisZ=AxisX×AxisY′

[0035] AxisY = AxisZ × AxisX

[0036] in, This refers to the 3D vector of feature aperture P1 in the camera coordinate system; P2 and P3 are similarly represented. AxisX, AxisY, and AxisZ represent the three coordinate axes, and AxisY′ refers to... and The resulting unit vector is used to calculate AxisZ, where P1, P2, and P3 represent the three extracted feature holes;

[0037] S22, take the workpiece thickness d on the AxisZ axis, and calculate the theoretical three-dimensional coordinates of the workpiece's feature hole under the camera:

[0038]

[0039]

[0040]

[0041] in, This refers to the theoretical three-dimensional vector of the feature hole Pt1 of the workpiece in the camera coordinate system; the same applies to Pt2 and Pt3.

[0042] S23, using the world coordinate system as the camera coordinate system, and employing a camera reprojection algorithm, the theoretical three-dimensional coordinates of the workpiece's feature holes from step S22 are reprojected onto the two-dimensional pixel plane, obtaining the theoretical UV positions of the multiple feature holes of the workpiece. t1 ,v t1},{u t2 ,v t2},{u t3 ,v t3},…}.

[0043] Furthermore, S3 includes:

[0044] S31, the feature hole of the workpiece (8) to be assembled is grasped by the end gripper (6) of the main robot (7) and located within the depth range and visual detection range of the small field of view binocular vision measurement device (2), and the transformation matrix of the end of the main robot (7) relative to the base coordinate system is recorded at this time.

[0045] S32, using a small field-of-view binocular vision measurement device (2), the three-dimensional spatial position of the feature hole of the workpiece (8) to be assembled is detected. Then, the three-dimensional spatial coordinates of the feature hole are obtained through the geometric spatial relationship between the feature holes. The coordinate system of the workpiece (8) to be assembled is established, and the coordinate transformation relationship of the coordinate system of the workpiece (8) to be assembled relative to the camera is recorded.

[0046] S33, using a small field-of-view binocular vision measurement device (2), the position of the feature hole of the workpiece (8) to be assembled is detected in the two-dimensional image UV position under the left camera. r1 ,v r1},{u r2 ,v r2},{u r3 ,v r3},…}, where u r1 ,v r1 These represent the two-dimensional coordinates of the feature aperture in the image coordinate system.

[0047] In this embodiment, S4 includes:

[0048] S41, based on the camera calibration results in step S1 and the theoretical and actual UV positions of the feature aperture under the left camera of the small field-of-view binocular vision measurement device (2), calculate the image Jacobian matrix:

[0049]

[0050] Among them, u i v is the x-coordinate of the i-th feature hole in the left camera pixel plane coordinate system; iLet u be the ordinate of the i-th feature hole in the left camera pixel plane coordinate system; center v is the x-coordinate of the center point in the left camera pixel plane coordinate system; center ρ is the ordinate of the center point in the left camera's pixel plane coordinate system; f is the focal length of the left camera; ρ u ρ is the width of a pixel; v Z represents the height of a pixel. i Let be the z-axis depth value of the i-th feature hole in the left camera coordinate system; x, y, z, a, b, and c are the pose offsets that the camera should move in the camera coordinate system while the workpiece to be assembled remains stationary, representing the offsets in the six directions respectively. This represents the offset of the feature aperture in the U direction within the image coordinate system. J represents the offset of the feature aperture in the V direction in the image coordinate system. i Let $\mathbf{x}$ represent the image Jacobian matrix, ..., $V$ represent the matrix formed by $x$, $y$, $z$, $a$, $b$, and $c$. In step S42, using the three feature holes selected in S21, a Jacobian matrix is ​​constructed for each feature hole, followed by matrix merging. The matrix merging methods include:

[0051] in, This represents the offset of feature hole 1 in the U direction in the image coordinate system. J1 represents the offset of feature hole 1 in the V direction in the image coordinate system, and J1 represents the image Jacobian matrix of feature hole 1. Since the merged Jacobian matrix is ​​a square matrix, x, y, z, a, b, and c can be obtained according to the above formula, which gives the pose offset that the camera should move when the workpiece to be assembled remains stationary in the camera coordinate system. To obtain the pose offset of the workpiece to be assembled when the left camera coordinate system is stationary, x, y, z, a, b, and c are taken as their inverses.

[0052] In this embodiment, S5 includes: converting the pose change of the workpiece to be assembled obtained in S4 into the pose change of the flange in the main robot base coordinate system. The conversion method includes:

[0053]

[0054] in, The next position the main robot should reach. This represents the change in the position of the workpiece to be assembled. and The hand-eye calibration results in S1; Convert the data to the form {x,y,z,a,b,c} and send it to the robot. This represents the transformation matrix of the large field-of-view binocular vision measurement device relative to the main robot's base coordinate system. This indicates that the hand-eye calibration of the main robot was completed using both a large field-of-view binocular vision measurement device and a small field-of-view binocular vision measurement device. This indicates that the coordinate system calibration of the camera and the main robot is completed after the base coordinate system calibration and hand-eye calibration are finished. This represents the transformation matrix of the end effector of the main robot relative to the base coordinate system. This indicates the coordinate transformation relationship between the workpiece coordinate system and the camera. This represents the transformation matrix between the camera coordinate system and the coordinate system of the position the workpiece should reach next.

[0055] In this embodiment, S7 includes: compensating for the u and v positions of the main robot (7), and the compensation method includes: Among them, u theory ,v theory The theoretical UV coordinates of multiple feature holes on the upper workpiece {{u t1 ,v t1},{u t2 ,v t2},{u t3 ,v t3},…},u real v real The UV position of the feature hole of the workpiece to be assembled in the 2D image under the left camera {{u r1 ,v r1},{u r2 ,v r2},{u r3 ,v r3},…}, where u last_buchang v last_buchang When calculating the compensation value for the first time, the value is assigned as:

[0056] Specifically, the positions of u and v are first compensated, and the compensation formula is as follows:

[0057] Among them, u theory ,v theory The theoretical UV coordinates of the multiple feature holes of the workpiece obtained in step S33 are {{u t1 ,v t1},{u t2 ,v t2},{u t3 ,v t3},…},u real v real The UV position of the feature hole of the workpiece to be assembled, obtained in step S71, in the two-dimensional image under the left camera, is {{u r1 ,v r1},{ur2 ,v r2},{u r3 ,v r3},…},u last_buchang v last_buchang When calculating the compensation value for the first time, the following values ​​are assigned: Then, update u buchang v buchang As the new target position, the difference between this position and the UV position of the feature hole of the workpiece to be assembled in the 2D image below the left camera is calculated. Substituting this difference into the Jacobian matrix formula, the machine...

[0058]

[0059] Robot motion offset: During the cyclic compensation process, the exit condition is: After the loop exits, the robot's position is the final assembly position, and the image vision servo compensation is completed.

[0060] In this embodiment, by analyzing the changes in feature holes in the image, the robot's movement is controlled. Through continuous servo compensation, the alignment of the feature holes on the upper and lower workpieces to be assembled is ultimately ensured, achieving high-precision assembly by the industrial robot. This invention effectively reduces the impact of robot absolute positioning error and system calibration error on robot assembly accuracy, and can meet the relative pose accuracy requirements during the docking and assembly of large workpieces.

[0061] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The above descriptions are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for image vision servo accuracy compensation for high-precision assembly of industrial robots, characterized in that, include: S1, perform base coordinate system calibration and hand-eye calibration on the main robot, and then perform coordinate system calibration on the main robot based on the base coordinate system calibration and hand-eye calibration, and then perform left camera calibration on the small field of view binocular vision measurement device; S21, using a small field-of-view binocular vision measurement device to detect the feature holes of the workpiece to be assembled, obtaining the three-dimensional coordinates of the feature holes relative to the left camera of the small field-of-view binocular vision measurement device, and then establishing the workpiece coordinate system of the lower workpiece, including: ,in, , , These are characteristic holes , , In the left camera coordinate system, the three-dimensional vectors AxisX, AxisY, and AxisZ represent the three coordinate axes. It refers to and The resulting unit vector is used to calculate AxisZ. , , This indicates the three feature holes that were extracted; S22, in Take the workpiece thickness on the shaft The three-dimensional coordinates of the feature holes of the workpiece to be assembled are calculated under the left camera. ,in, , and These are, in theory, the characteristic holes of the workpiece. , and The three-dimensional vector in the left camera coordinate system; S23, using the world coordinate system as the camera coordinate system, and employing a camera reprojection algorithm, the theoretical three-dimensional coordinates of the workpiece's feature holes in step S22 under the left camera are reprojected onto the two-dimensional pixel plane, thus obtaining the theoretical coordinates of the multiple feature holes of the workpiece in the image coordinate system of the left camera. Location ; S31, move the main robot until the feature hole of the upper workpiece grasped by the end gripper of the main robot is within the depth range and visual detection range of the small field of view binocular vision measurement device, and record the transformation matrix of the end of the main robot relative to the base coordinate system at this time. S32, the three-dimensional spatial position of the feature hole of the upper workpiece is detected by a small field-of-view binocular vision measurement device, and the three-dimensional spatial coordinates of the feature hole of the upper workpiece are obtained by the geometric spatial relationship between the feature holes of the upper workpiece. In this process, the coordinate system of the upper workpiece is established and the coordinate transformation relationship of the coordinate system of the upper workpiece relative to the left camera is recorded. S33, using a small field-of-view binocular vision measurement device, the actual position of the feature hole of the upper workpiece in the image coordinate system of the left camera is detected. Location , These represent the two-dimensional coordinates of feature aperture i in the image coordinate system, i=1,2,3…; S4, based on the camera calibration results in step S1, and the theoretical value of the feature aperture in the image coordinate system of the left camera... Location and actual Position, calculate the image Jacobian matrix, and obtain the pose change of the upper workpiece in the left camera coordinate system; S5, convert the pose change into the flange pose change in the base coordinate system of the main robot, and drive the main robot to execute the flange pose change to move the upper workpiece to the theoretical assembly position. S6, the feature holes of the upper workpiece are detected again to obtain the actual feature holes of the upper workpiece in the image coordinate system of the left camera. Location and actual three-dimensional location; S7, based on the theory obtained in step S23 Location and actual obtained in step S6 Position, compensate for the pose of the main robot, and obtain the compensation. Then, steps S4 to S7 are executed repeatedly until the theoretical result is reached. Location and actual The difference in position satisfies a fixed threshold. S4 includes: S41, based on the camera calibration results in step S1 and the theoretical coordinates of the feature aperture in the image coordinate system of the left camera of the small field-of-view binocular vision measurement device... Location and actual Location, calculate the image Jacobian matrix: ,in, and Feature holes The x and y coordinates in the left camera pixel plane coordinate system; and These are the x and y coordinates of the center point in the left camera pixel plane coordinate system, respectively. The focal length of the left camera; and These are the width and height of the pixel, respectively; Characteristic hole In the left camera coordinate system Towards depth value; , , , , , These represent the pose changes that the left camera should make when the upper workpiece remains stationary, in the left camera coordinate system. and These represent the characteristic holes. Offsets in the U and V directions in the image coordinate system Represents the Jacobian matrix of the image. Represents the matrix formed by x, y, z, a, b, and c; S42, construct the Jacobian matrix for the three feature holes extracted in S21, and then merge the matrices, including: ,in, and These represent characteristic holes P. i The offsets in the U and V directions in the image coordinate system, i=1,2,3. Characteristic hole P i The image Jacobian matrix.

2. The image vision servo accuracy compensation method for high-precision assembly of industrial robots according to claim 1, characterized in that, The end effector of the main robot is connected to a gripper, which is used to grip the workpiece to be assembled; the end effector of the auxiliary robot is connected to a small field-of-view binocular vision measurement device and an auxiliary light source. The large field-of-view binocular vision measurement device is installed on the top of the column. The observation range of the large field-of-view binocular vision measurement device covers the activity space of the auxiliary robot and the main robot. The column stands vertically on the workbench. The workpiece to be assembled is fixed on the worktable by tooling.

3. The image vision servo accuracy compensation method for high-precision assembly of industrial robots according to claim 2, characterized in that, S1 includes: The base coordinate system of the main robot is calibrated using a large field-of-view binocular vision measurement device, and the transformation matrix of the large field-of-view binocular vision measurement device relative to the base coordinate system of the main robot is obtained. Hand-eye calibration of the main robot was performed using a large field-of-view binocular vision measurement device and a small field-of-view binocular vision measurement device. The camera calibration of the small field-of-view binocular vision measurement device includes: calibrating the small field-of-view binocular vision sensor in the small field-of-view binocular vision measurement device to obtain the left camera intrinsic parameter matrix and camera distortion parameters.

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