Hidden point coordinate measurement method based on inertia and vision collaborative attitude measurement

Abstract

The invention discloses a hidden point coordinate measurement method based on inertia and vision collaborative attitude measurement, relates to the technical field of laser tracker hidden point coordinate measurement, and can realize high-precision hidden point coordinate measurement. The method comprises the following steps: calibrating target structure parameters and a specified rotation transformation matrix; measuring vertex coordinates of the vertex of the target prism in a third coordinate system, and obtaining a first target attitude matrix measured by a fusion inertial measurement unit IMU and a second target attitude matrix measured by a monocular vision attitude measurement system; based on a specified rotation transformation matrix, adjusting the first target attitude matrix and the second target attitude matrix to the same reference system, and fusing the first target attitude matrix and the second target attitude matrix under the same reference system to obtain a target attitude matrix; and according to the vertex coordinates, the target structure parameters and the target attitude matrix, calculating the three-dimensional coordinates of the hidden point in the third coordinate system.

Description

Technical Field

[0001] This application relates to the field of hidden point coordinate measurement technology of laser trackers, and in particular to a method for measuring hidden point coordinates based on inertial and visual collaborative attitude measurement. Background Technology

[0002] Laser trackers, as a typical large-size optical measurement instrument, are widely used in aerospace, automotive manufacturing, and other fields due to their advantages such as high precision, large range, and good real-time performance. However, in actual complex measurement environments, there are spatial obstacles and occlusions between the measured geometric features and the laser tracker host. To solve the measurement challenge of non-line-of-sight geometric features, hidden point coordinate measurement technology based on a six-degree-of-freedom laser tracker has emerged.

[0003] In related technologies, the measurement of hidden point coordinates mainly involves using a hidden point measurement target probe to contact the target. A laser tracker simultaneously measures the spatial coordinates of the vertex of the corner prism on the hidden point measurement target and the spatial attitude of the target. Combining the measurement data with the precisely calibrated coordinates of the probe's center point in the hidden point measurement target coordinate system (i.e., the target structural parameters), a spatial coordinate transformation model is used to calculate the coordinates of the probe's center point in the laser tracker coordinate system. In summary, the target attitude is the core input data in the hidden point coordinate calculation process, and its measurement accuracy directly determines the accuracy of the hidden point coordinate calculation. Therefore, it is urgent to improve the measurement accuracy of the target attitude to enhance the accuracy of hidden point coordinate measurement. Summary of the Invention

[0004] In view of this, this application provides a method for measuring hidden point coordinates based on inertial and visual collaborative attitude measurement. The main purpose is to address the issue that the target attitude, as the core input data in the hidden point coordinate calculation process, directly determines the accuracy of the hidden point coordinate calculation. Therefore, it is urgent to improve the accuracy of hidden point coordinate measurement by enhancing the accuracy of target attitude measurement.

[0005] According to a first aspect of this application, a method for measuring the coordinates of hidden points based on inertial and visual collaborative attitude measurement is provided, the method comprising:

[0006] The target structure parameters and the specified rotation transformation matrix are calibrated. The target structure parameters are used to describe the vertex coordinates of the center point of the target probe in the first coordinate system. The specified rotation transformation matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the second coordinate system. The first coordinate system is the IMU reference target coordinate system, and the second coordinate system is the LED reference target coordinate system.

[0007] The vertex coordinates of the target prism are measured in the third coordinate system, and the first target attitude matrix is ​​obtained by fusion inertial measurement unit (IMU) and the second target attitude matrix is ​​obtained by monocular vision attitude measurement system. The third coordinate system is the laser tracker coordinate system.

[0008] Based on the specified rotation transformation matrix, the first target attitude matrix and the second target attitude matrix are adjusted to the same reference frame, and the first target attitude matrix and the second target attitude matrix under the same reference frame are fused to obtain the target attitude matrix. The target attitude matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the third coordinate system.

[0009] Based on the vertex coordinates, the target structure parameters, and the target pose matrix, the three-dimensional coordinates of the hidden point in the third coordinate system are calculated.

[0010] Optionally, the specified rotation transformation matrix is ​​calibrated, including:

[0011] The target attitude was adjusted multiple times, and the roll angle and pitch angle under each target attitude were continuously measured using the IMU. Based on the roll angle and pitch angle, the first normalized gravity vector corresponding to each target attitude was calculated. The first normalized gravity vector is the normalized gravity vector under the first coordinate system.

[0012] The monocular vision attitude measurement system is continuously used to measure the attitude measurement results for each target attitude, and the second normalized gravity vector corresponding to each target attitude is calculated based on the attitude measurement results. The second normalized gravity vector is the normalized gravity vector in the second coordinate system.

[0013] Based on the first and second normalized gravity vectors corresponding to each target posture, a set of rotation transformation matrix calibration equations is constructed.

[0014] The rotation transformation matrix calibration equations are calculated by singular value decomposition to obtain the least squares solution, which is then used as the specified rotation transformation matrix.

[0015] Optionally, the calibration target structure parameters include:

[0016] The three-dimensional coordinates of the reflecting sphere are measured using a laser tracker as the reference coordinates. The reflecting sphere is mounted on a magnetic ball seat fixed to the optical platform.

[0017] The target attitude is adjusted multiple times while keeping the target probe in close contact with the calibration ball cone surface. The vertex coordinates, IMU target attitude matrix and LED target attitude matrix are continuously acquired under each target attitude. The calibration ball has the same diameter as the reflector ball, has a cone-shaped internal structure, and is fixed on the same magnetic ball seat as the reflector ball.

[0018] Based on the specified rotation transformation matrix and the quaternion spherical linear interpolation algorithm, the IMU target attitude matrix and the LED target attitude matrix are fused to obtain a fused attitude matrix;

[0019] Based on the reference coordinates, the vertex coordinates of each target pose, and the fused pose matrix, a set of target structure parameter calibration equations is constructed.

[0020] The target structure parameter calibration equations are calculated by singular value decomposition to obtain the least squares solution, which is then used as the calibration target structure parameters.

[0021] Optionally, measuring the vertex coordinates of the target prism in the third coordinate system includes: aligning the laser tracker with the cornerstone prism on the target, measuring the three-dimensional coordinates of the cornerstone prism vertex in the third coordinate system, and obtaining the vertex coordinates.

[0022] Optionally, adjusting the first target pose matrix and the second target pose matrix to the same reference frame based on the specified rotation transformation matrix includes:

[0023] Obtain the first target attitude matrix and the second target attitude matrix. The first target attitude matrix is ​​used to describe the rotational transformation relationship from the first coordinate system to the fourth coordinate system, and the second target attitude matrix is ​​used to describe the rotational transformation relationship from the second coordinate system to the third coordinate system. The fourth coordinate system is the reference gravity coordinate system of the laser tracker.

[0024] By precisely leveling the target using a high-precision electronic level built into the laser tracker, the third coordinate system is adjusted to be parallel to the fourth coordinate system, thereby unifying the first target's posture into a rotational transformation relationship from the first coordinate system to the third coordinate system.

[0025] By calculating the dot product between the second target pose and the specified rotation transformation matrix, the second target pose is unified into a rotation transformation relationship from the first coordinate system to the third coordinate system.

[0026] Optionally, the process of fusing the first target attitude matrix and the second target attitude matrix under the same reference frame to obtain the target attitude matrix includes:

[0027] The roll angle and pitch angle are determined based on the first target attitude matrix, and the azimuth angle is determined based on the second target attitude matrix.

[0028] A correction quaternion is constructed based on the roll angle, the pitch angle, and the azimuth angle, and an original attitude quaternion is constructed based on the second target attitude matrix;

[0029] Based on the quaternion spherical linear interpolation algorithm, the corrected quaternion and the original attitude quaternion are fused to obtain the fused target attitude quaternion;

[0030] Based on a preset conversion formula, the target attitude quaternion is converted into the target attitude matrix.

[0031] Optionally, calculating the three-dimensional coordinates of the hidden point in the third coordinate system based on the vertex coordinates, the target structure parameters, and the target pose matrix includes: calculating the product between the target pose matrix and the target structure parameters, and using the sum of the product and the vertex coordinates as the three-dimensional coordinates of the hidden point in the third coordinate system.

[0032] According to a second aspect of this application, a hidden point coordinate measurement device based on inertial and visual cooperative attitude measurement is provided, the device comprising:

[0033] The calibration module is used to calibrate the target structure parameters and specify the rotation transformation matrix. The target structure parameters are used to describe the vertex coordinates of the target probe center point in the first coordinate system. The specified rotation transformation matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the second coordinate system. The first coordinate system is the IMU reference target coordinate system, and the second coordinate system is the LED reference target coordinate system.

[0034] The measurement module is used to measure the vertex coordinates of the target prism in the third coordinate system, and to obtain the first target attitude matrix measured by the fusion inertial measurement unit (IMU) and the second target attitude matrix measured by the monocular vision attitude measurement system, wherein the third coordinate system is the laser tracker coordinate system;

[0035] The adjustment module is used to adjust the first target attitude matrix and the second target attitude matrix to the same reference frame based on the specified rotation transformation matrix, and to fuse the first target attitude matrix and the second target attitude matrix under the same reference frame to obtain the target attitude matrix. The target attitude matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the third coordinate system.

[0036] The calculation module is used to calculate the three-dimensional coordinates of the hidden point in the third coordinate system based on the vertex coordinates, the target structure parameters, and the target pose matrix.

[0037] According to a third aspect of this application, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the first aspects above.

[0038] According to a fourth aspect of this application, a computer-readable storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of the first aspects above.

[0039] By employing the above technical solution, this application provides a method for measuring the coordinates of hidden points based on inertial and visual collaborative attitude measurement. In this embodiment, a specified rotation transformation matrix is ​​used to adjust the first target attitude matrix and the second target attitude matrix to the same reference system, and these are fused to obtain a target attitude matrix describing the rotation transformation relationship between the IMU reference target coordinate system and the laser tracker coordinate system. This avoids the limitations of monocular vision in terms of measurement range and dynamic performance, as well as the problem of IMU azimuth drift over time, achieving high-precision optimal estimation of the target attitude. Finally, based on the target prism vertex coordinates, target structural parameters, and the target attitude matrix, the three-dimensional coordinates of the hidden point in the laser tracker coordinate system are calculated, achieving high-precision measurement of the hidden point coordinates.

[0040] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0041] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0042] Figure 1 This paper illustrates a flowchart of a method for measuring the coordinates of hidden points based on inertial and visual collaborative attitude measurement, according to an embodiment of this application.

[0043] Figure 2 This illustration shows a schematic diagram of a hidden point coordinate measurement system based on inertial and visual collaborative attitude measurement, provided in an embodiment of this application.

[0044] Figure 3 This illustration shows a schematic diagram of the geometric relationship of target structure parameters provided in an embodiment of this application;

[0045] Figure 4 A schematic diagram of a calibration device structure provided in an embodiment of this application is shown;

[0046] Figure 5 A schematic diagram of the structure of a hidden point coordinate measuring device based on inertial and visual collaborative attitude measurement provided in an embodiment of this application is shown.

[0047] Figure 6 A schematic diagram of the device structure of a computer device provided in an embodiment of this application is shown. Detailed Implementation

[0048] The embodiments of this application are described in detail below. Examples of these embodiments 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 this application, and should not be construed as limiting this application.

[0049] 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 word “comprising” as used in the specification of this application 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.

[0050] 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 application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0051] Those skilled in the art will understand that the term "terminal" as used herein includes both devices that are wireless signal receivers, devices that are wireless signal receivers without transmitting capability, and devices with receiving and transmitting hardware, having receiving and transmitting hardware capable of performing bidirectional communication on a bidirectional communication link. Such devices may include: cellular or other communication devices having a single-line display, a multi-line display, or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service) that can combine voice, data processing, fax, and / or data communication capabilities; PDA (Personal Digital Assistant) that may include a radio frequency receiver, pager, Internet / intranet access, web browser, notepad, calendar, and / or GPS (Global Positioning System) receiver; and conventional laptop and / or handheld computers or other devices that have and / or include a radio frequency receiver. As used herein, "terminal" can be portable, transportable, installed in a means of transportation (air, sea, and / or land), or suitable and / or configured to operate locally, and / or in a distributed manner, operating in any other location on Earth and / or in space. "Terminal" as used herein can also be a communication terminal, an internet access terminal, or a music / video playback terminal, such as a PDA, a MID (Mobile Internet Device), and / or a mobile phone with music / video playback capabilities, or a smart TV, set-top box, etc.

[0052] The hidden point coordinate measurement method based on monocular vision attitude measurement is one of the mainstream technical solutions in the current field of hidden point coordinate measurement. The attitude measurement principle of this method is to utilize the cooperation between a monocular vision module and a spatial cooperative target to capture LED feature point images of the target in real time. Based on the images, the two-dimensional coordinates of the feature points are extracted, and the PnP (Perspective-n-Point) problem is solved using these coordinates to obtain the target's three-dimensional attitude. Using an Inertial Measurement Unit (IMU) for attitude measurement is also a technical solution for hidden point target attitude measurement. The IMU integrates inertial sensors such as gyroscopes and accelerometers to collect angular velocity and acceleration information of the IMU carrier in real time, and performs attitude estimation based on estimation algorithms such as complementary filtering or Kalman filtering, thus completing attitude estimation in both dynamic and static environments. However, the monocular vision-based attitude measurement method has inherent limitations in terms of measurement range, dynamic performance, environmental adaptability, and lens distortion compensation. These factors restrict the improvement of its measurement accuracy and ultimately affect the accuracy of hidden point coordinate measurement. IMU-based attitude measurement methods can only achieve high-precision measurement of roll and pitch angles through gravity vector constraints. However, the azimuth measurement data will drift over time due to the lack of an absolute reference, and cannot be used independently for hidden point coordinate measurement.

[0053] This application provides a method for measuring the coordinates of hidden points based on inertial and visual collaborative attitude measurement, such as... Figure 1 As shown, the method includes:

[0054] S1. Calibrate the target structure parameters and specify the rotation transformation matrix. The target structure parameters are used to describe the vertex coordinates of the target probe center point in the first coordinate system. The specified rotation transformation matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the second coordinate system. The first coordinate system is the IMU reference target coordinate system, and the second coordinate system is the LED reference target coordinate system.

[0055] In this embodiment, the measurement system obtains the target attitude matrix, i.e., the optimal estimate of the target attitude, by fusing the target attitude matrices measured by the Inertial Measurement Unit (IMU) and the monocular vision attitude measurement system, thereby achieving high-precision hidden point coordinate measurement. The structure of the measurement system is as follows: Figure 2 As shown, 10 is a six-degree-of-freedom laser tracker, 20 is a hidden point measurement target, 101 is a monocular camera, 102 is a gravity vector, 201 is a corner cube prism, 202 is an infrared LED, and 203 is an IMU.

[0056] Understandably, the system needs to calibrate relevant parameters before actual measurement. The specific calibration process for the target structure parameters and the specified rotation transformation matrix is ​​as follows:

[0057] For the calibration of a specified rotation transformation matrix, this application considers that the IMU can only accurately measure the roll and pitch angles using gravity field constraints, while its azimuth angle measurements drift over time and cannot be directly calibrated using relevant expressions. Therefore, this application adopts a calibration method based on gravity vector constraints, which can calibrate the specified rotation transformation matrix without requiring an azimuth angle. It should be noted that the specified rotation transformation matrix describes the rotation transformation relationship from the first coordinate system (I) to the second coordinate system (T), where the first coordinate system is the IMU reference target coordinate system, and the second coordinate system is the LED reference target coordinate system.

[0058] The system repeatedly adjusts the target, continuously using IMU to measure the roll and pitch angles at each target attitude. Based on the roll and pitch angles, the system calculates the first normalized gravity vector corresponding to each target attitude using the following formula 1, i.e., the normalized gravity vector in the first coordinate system I. I g.

[0059] Formula 1:

[0060] Where θ and φ are the pitch and roll angles measured by the IMU, respectively. Similarly, a monocular vision attitude measurement system is continuously used to capture LED feature point images of the target in each attitude in real time. Then, based on the two-dimensional coordinates of the feature points extracted from the images, the three-dimensional attitude of the target is solved to obtain the attitude measurement results. Then, based on the attitude measurement results, the second normalized gravity vector corresponding to each target attitude is calculated, that is, the measured value of the normalized gravity vector in the second coordinate system T. T g. It should be noted that the rotation transformation matrix and I g、 T g satisfies the relationship shown in Formula 2 below.

[0061] Formula 2:

[0062] Next, based on the first and second normalized gravity vectors corresponding to each target posture, a set of rotation transformation matrix calibration equations is constructed as shown in Formula 3 below.

[0063] Formula 3:

[0064] Finally, the rotation transformation matrix calibration equations are calculated using singular value decomposition to obtain the least squares solution. As the specified rotation transformation matrix.

[0065] Furthermore, regarding the calibration of target structural parameters, the geometric relationships of the target structural parameters are as follows: Figure 3 As shown, 204 is the vertex P of the target prism, and 205 is the center point O of the probe. The target structural parameters satisfy the following formula...

[0066] The relationship shown in Equation 4.

[0067]

[0068] in, The fused pose matrix is ​​obtained by fusing the target pose matrix measured by the IMU and the monocular vision pose measurement system. LT x P , LT y P , LT z P Let P be the coordinates of the target prism vertex P in the third coordinate system LT. I x O , I y O , I z O ) represents the coordinates of the target probe center point O in the first coordinate system I, i.e., the target structural parameters. LT x H , LT y H , LT z H ) represents the three-dimensional coordinates of the hidden point H in the third coordinate system LT.

[0069] When calibrating the target's structural parameters, the spherical mounted retroreflector (SMR) is first installed in a magnetic sphere fixed to the optical platform, and the three-dimensional coordinates of the SMR's center are measured using a laser tracker. Then, the target probe is placed inside a 6mm probe calibration sphere. The calibration device is as follows: Figure 4As shown, 301 is the probe, 302 is the probe head, 303 is the calibration sphere, and 304 is the magnetic ball seat. The calibration sphere has a conical internal structure. When the 6mm diameter probe head is in close contact with the conical surface, the center point of the probe head coincides with the center of the calibration sphere. Since the diameter of the calibration sphere is the same as that of the SMR, the coordinates of the center of the calibration sphere can be obtained by fixing the SMR with the same diameter as the calibration sphere on the same magnetic ball seat and measuring it using a laser tracker. Specifically, the system adjusts the target attitude multiple times while keeping the target probe head in close contact with the conical surface of the calibration sphere, continuously acquiring the vertex coordinates, IMU target attitude matrix, and LED target attitude matrix under each target attitude. Based on the specified rotation transformation matrix and the quaternion spherical linear interpolation algorithm, the IMU target attitude matrix and the LED target attitude matrix are fused to obtain the fused attitude matrix. Based on the reference coordinates, the vertex coordinates under each target attitude, and the fused attitude matrix, the target structure parameter calibration equation set shown in Formula 5 below is constructed.

[0070] Formula 5:

[0071] Finally, the target structure parameter calibration equations were calculated using singular value decomposition to obtain the least squares solution. As a parameter for calibrating the target structure, it is understood that the number of times the target attitude is adjusted, n, should be greater than or equal to 3.

[0072] S2. Measure the vertex coordinates of the target prism in the third coordinate system, and obtain the first target attitude matrix measured by the fusion inertial measurement unit (IMU) and the second target attitude matrix measured by the monocular vision attitude measurement system, wherein the third coordinate system is the laser tracker coordinate system.

[0073] In this embodiment, the laser tracker is aimed at the cornerstone prism on the target, and the three-dimensional coordinates of the cornerstone prism vertex in the third coordinate system are measured to obtain the vertex coordinates. LT x P , LT y P , LT z P Further, obtain the first target pose matrix. Second target attitude matrix The first target attitude matrix is ​​used to describe the rotational transformation relationship from the first coordinate system I to the fourth coordinate system G. The second target attitude matrix is ​​used to describe the rotational transformation relationship from the second coordinate system T to the third coordinate system LT. The fourth coordinate system is the reference gravity coordinate system of the laser tracker.

[0074] S3. Based on the specified rotation transformation matrix, adjust the first target attitude matrix and the second target attitude matrix to the same reference frame, and fuse the first target attitude matrix and the second target attitude matrix under the same reference frame to obtain the target attitude matrix. The target attitude matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the third coordinate system.

[0075] In this embodiment, the laser tracker is first precisely leveled using a built-in high-precision electronic level to align the third coordinate system (LT) with the fourth coordinate system (G), thus achieving the desired target posture. Unified as rotational transformation relationship from the first coordinate system to the third coordinate system

[0076] Furthermore, as shown in Equation 6 below, the difference between the IMU and visual pose measurement results is mainly due to the rotation transformation matrix from the I-frame to the T-frame. This is caused by the fact that the measurement objects and reference coordinate systems of the two attitude measurement data are different, and there is a fixed rotational transformation relationship between the two systems: from the I-frame to the T-frame and from the LT-frame to the G-frame. After precise leveling using the high-precision electronic level built into the laser tracker, the third coordinate system LT-frame can be adjusted to be parallel to the fourth coordinate system G-frame, thus realizing the attitude of the first target. Unified as rotational transformation relationship from the first coordinate system to the third coordinate system

[0077] Formula 6:

[0078] Furthermore, the attitudes of the two targets... With the specified rotation transformation matrix Substituting the data into Equation 6 above, we can unify the attitude measurement data of the two sensors into the same reference coordinate system.

[0079] Furthermore, based on the unified first target attitude matrix Determine the roll and pitch angles based on the unified second target attitude matrix. Determine the azimuth angle. Construct a correction quaternion based on the roll, pitch, and azimuth angles, and then use the second target attitude matrix. Construct the original pose quaternion.

[0080] Based on the quaternion spherical linear interpolation algorithm, the corrected quaternion and the original attitude quaternion are fused using the following formula 7 to obtain the fused target attitude quaternion q. f .

[0081] Formula 7:

[0082] Wherein, q fq is the fused target pose quaternion; q0 is the original pose quaternion obtained from the pose transformation measured visually; q c The correction quaternion is constructed jointly from the pitch and roll angles measured by IMU and the original azimuth angle provided by visual measurement; θ is the angle between the quaternions, satisfying θ=arccos(q0·q c ); α is a weighting factor used to adjust the fusion ratio of the two sensor data, as shown in Formula 8 below. α is determined by the measurement uncertainty σ of the monocular vision attitude measurement system and the IMU. V σ I Sure.

[0083] Formula 8:

[0084] Finally, based on the preset transformation formula shown in Formula 9 below, the target attitude quaternion q = (w, x, y, z) is transformed into the target attitude matrix.

[0085] Formula 9:

[0086] Where w is the scalar state, and x, y, z are the vector states.

[0087] S4. Based on the vertex coordinates, target structure parameters, and target pose matrix, calculate the three-dimensional coordinates of the hidden point in the third coordinate system.

[0088] In this embodiment, the system calculates the target attitude matrix using the following formula 10. With target structural parameters The product between them, and the product with the vertex coordinates ( LT x P , LT y P , LT z P The sum of ) is used as the three-dimensional coordinates of the hidden point in the third coordinate system. LT x H , LT y H , LT z H ).

[0089] Formula 10:

[0090] The method provided in this application adjusts the first target attitude matrix and the second target attitude matrix to the same reference system by specifying a rotation transformation matrix, and then fuses them to obtain a target attitude matrix describing the rotation transformation relationship between the IMU reference target coordinate system and the laser tracker coordinate system. This avoids the limitations of monocular vision in terms of measurement range and dynamic performance, as well as the problem of IMU azimuth drift over time, achieving high-precision optimal estimation of the target attitude. Finally, based on the target prism vertex coordinates, target structural parameters, and target attitude matrix, the three-dimensional coordinates of the hidden point in the laser tracker coordinate system are calculated, achieving high-precision measurement of the hidden point coordinates.

[0091] Furthermore, as Figure 1 To specifically implement the method, this application provides a hidden point coordinate measurement device based on inertial and visual collaborative attitude measurement, such as... Figure 5 As shown, the system includes: a calibration module 501, a measurement module 502, an adjustment module 503, and a calculation module 504.

[0092] The calibration module 501 is used to calibrate the target structure parameters and specify the rotation transformation matrix. The target structure parameters are used to describe the vertex coordinates of the center point of the target probe in the first coordinate system. The specified rotation transformation matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the second coordinate system. The first coordinate system is the IMU reference target coordinate system, and the second coordinate system is the LED reference target coordinate system.

[0093] The measurement module 502 is used to measure the vertex coordinates of the target prism in the third coordinate system, and to obtain the first target attitude matrix measured by the fusion inertial measurement unit (IMU) and the second target attitude matrix measured by the monocular vision attitude measurement system, wherein the third coordinate system is the laser tracker coordinate system;

[0094] The adjustment module 503 is used to adjust the first target posture matrix and the second target posture matrix to the same reference frame based on the specified rotation transformation matrix, and to fuse the first target posture matrix and the second target posture matrix under the same reference frame to obtain a target posture matrix. The target posture matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the third coordinate system.

[0095] The calculation module 504 is used to calculate the three-dimensional coordinates of the hidden point in the third coordinate system based on the vertex coordinates, the target structure parameters and the target posture matrix.

[0096] In a specific application scenario, the calibration module 501 is used to adjust the target attitude multiple times, continuously using the IMU to measure the roll and pitch angles of each target attitude, and calculating the first normalized gravity vector corresponding to each target attitude based on the roll and pitch angles. The first normalized gravity vector is the normalized gravity vector in the first coordinate system. It also continuously uses the monocular vision attitude measurement system to measure the attitude measurement results of each target attitude, and calculates the second normalized gravity vector corresponding to each target attitude based on the attitude measurement results. The second normalized gravity vector is the normalized gravity vector in the second coordinate system. Based on the first and second normalized gravity vectors corresponding to each target attitude, a set of rotation transformation matrix calibration equations is constructed. The set of rotation transformation matrix calibration equations is calculated using singular value decomposition to obtain a least-squares solution, which is then used as the specified rotation transformation matrix.

[0097] In a specific application scenario, the calibration module 501 is used to measure the three-dimensional coordinates of a reflective sphere using a laser tracker as the reference coordinates. The reflective sphere is mounted on a magnetic sphere fixed to an optical platform. The target attitude is adjusted multiple times while keeping the target probe in close contact with the cone surface of the calibration sphere. The vertex coordinates, IMU target attitude matrix, and LED target attitude matrix under each target attitude are continuously acquired. The calibration sphere has the same diameter as the reflective sphere, has an internal cone structure, and is fixed on the same magnetic sphere as the reflective sphere. Based on the specified rotation transformation matrix and the quaternion spherical linear interpolation algorithm, the IMU target attitude matrix and the LED target attitude matrix are fused to obtain a fused attitude matrix. Based on the reference coordinates, the vertex coordinates under each target attitude, and the fused attitude matrix, a set of target structure parameter calibration equations is constructed. The set of target structure parameter calibration equations is calculated using singular value decomposition to obtain a least squares solution, which is then used as the calibration target structure parameters.

[0098] In a specific application scenario, the measurement module 502 is used to align the laser tracker with the cornerstone prism on the target, measure the three-dimensional coordinates of the cornerstone prism vertex in the third coordinate system, and obtain the vertex coordinates.

[0099] In a specific application scenario, the adjustment module 503 is used to obtain the first target posture matrix and the second target posture matrix. The first target posture matrix is ​​used to describe the rotational transformation relationship from the first coordinate system to the fourth coordinate system, and the second target posture matrix is ​​used to describe the rotational transformation relationship from the second coordinate system to the third coordinate system. The fourth coordinate system is the reference gravity coordinate system of the laser tracker. By precisely leveling the laser tracker with a built-in high-precision electronic level, the third coordinate system is adjusted to be parallel to the fourth coordinate system, thereby unifying the first target posture into the rotational transformation relationship from the first coordinate system to the third coordinate system. By calculating the dot product between the second target posture and the specified rotational transformation matrix, the second target posture is unified into the rotational transformation relationship from the first coordinate system to the third coordinate system.

[0100] In a specific application scenario, the adjustment module 503 is used to determine the roll angle and pitch angle based on the first target attitude matrix, and the azimuth angle based on the second target attitude matrix; construct a correction quaternion based on the roll angle, the pitch angle, and the azimuth angle, and construct an original attitude quaternion based on the second target attitude matrix; fuse the correction quaternion and the original attitude quaternion based on the quaternion spherical linear interpolation algorithm to obtain the fused target attitude quaternion; and convert the target attitude quaternion into the target attitude matrix based on a preset conversion formula.

[0101] In a specific application scenario, the solution module 504 is used to calculate the product between the target pose matrix and the target structure parameters, and use the sum of the product and the vertex coordinates as the three-dimensional coordinates of the hidden point in the third coordinate system.

[0102] The apparatus provided in this application adjusts the first target attitude matrix and the second target attitude matrix to the same reference system by specifying a rotation transformation matrix, and fuses them to obtain a target attitude matrix describing the rotation transformation relationship between the IMU reference target coordinate system and the laser tracker coordinate system. This avoids the limitations of monocular vision in terms of measurement range and dynamic performance, as well as the problem of IMU azimuth drift over time, achieving high-precision optimal estimation of the target attitude. Finally, based on the target prism vertex coordinates, target structural parameters, and target attitude matrix, the three-dimensional coordinates of the hidden point in the laser tracker coordinate system are calculated, achieving high-precision measurement of the hidden point coordinates.

[0103] It should be noted that other corresponding descriptions of the functional units involved in the hidden point coordinate measurement device based on inertial and visual collaborative attitude measurement provided in this application embodiment can be found in the following references. Figures 1 to 4 The corresponding descriptions in [the document] will not be repeated here.

[0104] To address the aforementioned technical problems, embodiments of the present invention also provide a computer device. Please refer to [link / reference needed]. Figure 6 , Figure 6 This is a basic structural block diagram of the computer device in this embodiment.

[0105] like Figure 6 The diagram shows the internal structure of a computer device. The computer device includes a processor, non-volatile storage medium, memory, and a network interface connected via a system bus. The non-volatile storage medium stores the operating system, database, and computer-readable instructions. The database may store control information sequences. When the computer-readable instructions are executed by the processor, they enable the processor to implement a data relationship reconstruction method. The processor provides computing and control capabilities, supporting the operation of the entire computer device. The memory stores computer-readable instructions, which, when executed by the processor, enable the processor to implement a data relationship reconstruction method. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that… Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0106] In this embodiment, the processor is used to execute... Figure 5 The calibration module 501, measurement module 502, adjustment module 503, and calculation module 504 have specific functions. The memory stores the program code and various data required to execute these modules. The network interface is used for data transmission between user terminals or servers.

[0107] The present invention also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the data relationship reconstruction method of any of the above embodiments.

[0108] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0109] Those skilled in the art will understand that the steps, measures, and solutions in the various operations, methods, and processes discussed in this application can be alternated, modified, combined, or deleted. Furthermore, other steps, measures, and solutions in the various operations, methods, and processes discussed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted. Furthermore, steps, measures, and solutions in the prior art that are similar to those disclosed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted.

[0110] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for measuring the coordinates of hidden points based on inertial and visual collaborative attitude measurement, characterized in that, include: The target structure parameters and the specified rotation transformation matrix are calibrated. The target structure parameters are used to describe the vertex coordinates of the center point of the target probe in the first coordinate system. The specified rotation transformation matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the second coordinate system. The first coordinate system is the IMU reference target coordinate system, and the second coordinate system is the LED reference target coordinate system. The vertex coordinates of the target prism are measured in the third coordinate system, and the first target attitude matrix is ​​obtained by fusion inertial measurement unit (IMU) and the second target attitude matrix is ​​obtained by monocular vision attitude measurement system. The third coordinate system is the laser tracker coordinate system. Based on the specified rotation transformation matrix, the first target attitude matrix and the second target attitude matrix are adjusted to the same reference frame, and the first target attitude matrix and the second target attitude matrix under the same reference frame are fused to obtain the target attitude matrix. The target attitude matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the third coordinate system. Based on the vertex coordinates, the target structure parameters, and the target pose matrix, the three-dimensional coordinates of the hidden point in the third coordinate system are calculated.

2. The method according to claim 1, characterized in that, The calibration specifies the rotation transformation matrix, including: The target attitude was adjusted multiple times, and the roll angle and pitch angle under each target attitude were continuously measured using the IMU. Based on the roll angle and pitch angle, the first normalized gravity vector corresponding to each target attitude was calculated. The first normalized gravity vector is the normalized gravity vector under the first coordinate system. The monocular vision attitude measurement system is continuously used to measure the attitude measurement results for each target attitude, and the second normalized gravity vector corresponding to each target attitude is calculated based on the attitude measurement results. The second normalized gravity vector is the normalized gravity vector in the second coordinate system. Based on the first and second normalized gravity vectors corresponding to each target posture, a set of rotation transformation matrix calibration equations is constructed. The rotation transformation matrix calibration equations are calculated by singular value decomposition to obtain the least squares solution, which is then used as the specified rotation transformation matrix.

3. The method according to claim 1, characterized in that, The calibration target structure parameters include: The three-dimensional coordinates of the reflecting sphere are measured using a laser tracker as the reference coordinates. The reflecting sphere is mounted on a magnetic ball seat fixed to the optical platform. The target attitude is adjusted multiple times while keeping the target probe in close contact with the calibration ball cone surface. The vertex coordinates, IMU target attitude matrix and LED target attitude matrix are continuously acquired under each target attitude. The calibration ball has the same diameter as the reflector ball, has a cone-shaped internal structure, and is fixed on the same magnetic ball seat as the reflector ball. Based on the specified rotation transformation matrix and the quaternion spherical linear interpolation algorithm, the IMU target attitude matrix and the LED target attitude matrix are fused to obtain a fused attitude matrix; Based on the reference coordinates, the vertex coordinates of each target pose, and the fused pose matrix, a set of target structure parameter calibration equations is constructed. The target structure parameter calibration equations are calculated by singular value decomposition to obtain the least squares solution, which is then used as the calibration target structure parameters.

4. The method according to claim 1, characterized in that, The measurement of the vertex coordinates of the target prism in the third coordinate system includes: aligning the laser tracker with the cornerstone prism on the target, measuring the three-dimensional coordinates of the cornerstone prism vertex in the third coordinate system, and obtaining the vertex coordinates.

5. The method according to claim 1, characterized in that, The step of adjusting the first target attitude matrix and the second target attitude matrix to the same reference frame based on the specified rotation transformation matrix includes: Obtain the first target attitude matrix and the second target attitude matrix. The first target attitude matrix is ​​used to describe the rotational transformation relationship from the first coordinate system to the fourth coordinate system, and the second target attitude matrix is ​​used to describe the rotational transformation relationship from the second coordinate system to the third coordinate system. The fourth coordinate system is the reference gravity coordinate system of the laser tracker. By precisely leveling the target using a high-precision electronic level built into the laser tracker, the third coordinate system is adjusted to be parallel to the fourth coordinate system, thereby unifying the first target's posture into a rotational transformation relationship from the first coordinate system to the third coordinate system. By calculating the dot product between the second target pose and the specified rotation transformation matrix, the second target pose is unified into a rotation transformation relationship from the first coordinate system to the third coordinate system.

6. The method according to claim 1, characterized in that, The target attitude matrix is ​​obtained by fusing the first target attitude matrix and the second target attitude matrix under the same reference frame, including: The roll angle and pitch angle are determined based on the first target attitude matrix, and the azimuth angle is determined based on the second target attitude matrix. A correction quaternion is constructed based on the roll angle, the pitch angle, and the azimuth angle, and an original attitude quaternion is constructed based on the second target attitude matrix; Based on the quaternion spherical linear interpolation algorithm, the corrected quaternion and the original attitude quaternion are fused to obtain the fused target attitude quaternion; Based on a preset conversion formula, the target attitude quaternion is converted into the target attitude matrix.

7. The method according to claim 1, characterized in that, The step of calculating the three-dimensional coordinates of the hidden point in the third coordinate system based on the vertex coordinates, the target structure parameters, and the target pose matrix includes: calculating the product between the target pose matrix and the target structure parameters, and using the sum of the product and the vertex coordinates as the three-dimensional coordinates of the hidden point in the third coordinate system.

8. A hidden point coordinate measurement device based on inertial and visual collaborative attitude measurement, characterized in that, include: The calibration module is used to calibrate the target structure parameters and specify the rotation transformation matrix. The target structure parameters are used to describe the vertex coordinates of the target probe center point in the first coordinate system. The specified rotation transformation matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the second coordinate system. The first coordinate system is the IMU reference target coordinate system, and the second coordinate system is the LED reference target coordinate system. The measurement module is used to measure the vertex coordinates of the target prism in the third coordinate system, and to obtain the first target attitude matrix measured by the fusion inertial measurement unit (IMU) and the second target attitude matrix measured by the monocular vision attitude measurement system, wherein the third coordinate system is the laser tracker coordinate system; The adjustment module is used to adjust the first target attitude matrix and the second target attitude matrix to the same reference frame based on the specified rotation transformation matrix, and to fuse the first target attitude matrix and the second target attitude matrix under the same reference frame to obtain the target attitude matrix. The target attitude matrix is ​​used to describe the rotation transformation relationship from the first coordinate system to the third coordinate system. The calculation module is used to calculate the three-dimensional coordinates of the hidden point in the third coordinate system based on the vertex coordinates, the target structure parameters, and the target pose matrix.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

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

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