Laser tracker multilateral measurement method and system for shielding environment

Abstract

The invention provides a laser tracker multilateral measurement method and system oriented to a shielding environment, and the method comprises the steps: S1, obtaining the distance measurement data between a measurement point on a target object and an optical distance measurement unit through at least four optical distance measurement units located in a measurement field under a shielding condition; s2, constructing a space coordinate system based on an optical ranging unit; s3, on the basis of a ranging data set between the measuring point and the optical ranging unit, constructing an overdetermined equation set containing the optical ranging unit and the measuring point coordinate; s4, solving the overdetermined equation set through a preset algorithm, and obtaining the coordinates of the optical ranging unit; and S5, based on the coordinates of the optical ranging unit, completing three-dimensional coordinate calculation of the target measuring point on the target table object through single or multiple ranging measurements according to measurement requirements.

Description

Technical Field

[0001] This invention relates to the field of three-dimensional coordinate measurement and spatial positioning technology, specifically to a multi-sided measurement method and system for laser trackers in occluded environments. Background Technology

[0002] Laser trackers, as high-precision, large-range three-dimensional coordinate measuring devices, are widely used in aerospace, shipbuilding, large equipment assembly, and precision assembly fields due to their advantages such as high measurement accuracy, long measurement distance, and strong field adaptability. In practical engineering applications, spatial coordinate measurements are typically performed at multiple points to assess the attitude, position, or assembly accuracy of the measured object.

[0003] In large-scale measurement scenarios, the measurement accuracy and stability of a single laser tracker are often insufficient to meet the requirements of high-precision assembly and alignment due to limitations in measurement angle error, measurement distance, and spatial geometry. Therefore, multilateral measurement technology based on the collaborative operation of multiple laser trackers has gradually been applied. This technology acquires distance information from the measurement point to each base station through multiple base stations and calculates the three-dimensional coordinates of the measurement point using a multilateral measurement model, thereby improving measurement accuracy and system robustness to a certain extent.

[0004] Most existing multilateral measurement methods are based on the following assumptions: first, the measurement point can be simultaneously observed by a sufficient number of laser tracker base stations; second, the ranging data is complete and can construct a system of equations that satisfy the solution conditions. In an ideal unobstructed environment, the above methods can achieve high-precision coordinate calculations. However, in actual engineering sites, especially during the assembly of large components, the measurement of the interior of complex structures, or the collaborative assembly and adjustment of multiple components, the line of sight between the measurement point and the laser tracker is often obstructed due to factors such as the component's own structure, tooling equipment, or personnel operation. This results in the loss of some ranging data, thus creating measurement scenarios with incomplete ranging data.

[0005] Patent CN112362037B proposes a laser tracker station planning method based on combined measurement. This method establishes a model incorporating constraints such as incident, elevation, distance, and interference, and searches for feasible stations in a discrete station space to reduce the number of stations and relocations, thereby improving measurement efficiency. Furthermore, patent CN116976193A discloses an optimal measurement station planning method for laser trackers. Based on a 3D model and measurement point data, it uses collision detection to determine optical path reachability and calculates the optimal station using an intelligent optimization algorithm. The core of these station planning solutions lies in "avoiding occlusion as much as possible, reducing relocations, and improving coverage and efficiency through station selection." However, in engineering sites, occlusion is often dynamic and cannot be completely eliminated. When occlusion has already caused the loss of distance measurement observations, relying solely on site planning is usually insufficient to fundamentally solve the problem of "incomplete observations leading to indeterminate / unstable coordinate calculations". At the same time, such solutions generally do not directly provide a unified modeling and solution process that can still stably calculate the three-dimensional coordinates of the measurement points under the condition of "incomplete distance measurement data".

[0006] Therefore, how to construct a laser tracker multilateral measurement method with good adaptability and robustness under conditions of occlusion and incomplete ranging data, and achieve stable calculation of base station self-calibration and measurement point three-dimensional coordinates while ensuring measurement accuracy, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a multi-sided measurement method and system for laser trackers in occluded environments.

[0008] According to one aspect of the present invention, a multi-sided measurement method for a laser tracker in an occluded environment includes: Step S1: Using at least four optical ranging units located within the measurement field, acquire distance measurement data between the measuring point on the target object and the optical ranging units under occlusion conditions.

[0009] Step S2: Construct a spatial coordinate system based on the optical ranging unit; Step S3: Based on the distance measurement data set between the measuring point and the optical ranging unit, construct an overdetermined set of equations that includes the coordinates of the optical ranging unit and the measuring point; Step S4: Solve the overdetermined equations using a preset algorithm to obtain the coordinates of the optical ranging unit; Step S5: Based on the coordinates of the optical ranging unit, and according to the measurement requirements, complete the calculation of the three-dimensional coordinates of the target measurement point on the target table object through one or more ranging measurements.

[0010] Preferably, in step S1, acquiring distance measurement data between the measuring point on the target object and the optical ranging unit includes: If the target object undergoes a rigid body posture change during the measurement process, a set of distance measurement data with redundancy is obtained by measuring the measurement points of the target object under at least two different postures. The redundancy indicates that the number of distance measurement data is sufficient to meet the number requirement for constructing overdetermined equations in step S3.

[0011] Preferably, in step S1, acquiring incomplete distance measurement data between the measuring point on the target object and the optical ranging unit includes: If the target object undergoes a rigid body posture change during the measurement process, a set of distance measurement data with redundancy is obtained by measuring the measurement points of the target object under at least two different postures, and by moving or adding optical ranging units.

[0012] Preferably, step S2 specifically includes: With one of the optical ranging units As the origin of the coordinate system, with the optical ranging unit Pointing to another optical ranging unit The direction is Axis, with optical ranging unit To optical ranging unit vector and optical ranging unit Pointing to another optical ranging unit vector The direction of the vector obtained by the product of the two is The axis is determined by the right-hand rule. The axes are used to construct a spatial coordinate system.

[0013] Preferably, step S3 specifically includes: Based on the distance measurement data set between the optical ranging unit and the measuring point under different postures of the target object, the coordinates of the optical ranging unit and the measuring point, and the constraint that the distance between the measuring points is constant, an overdetermined set of equations for a nonlinear least squares problem is constructed with the goal of minimizing the error between the distance value calculated by the coordinates and the actual distance value.

[0014] Preferably, step S4 specifically includes: The overdetermined equations are solved using a nonlinear least squares optimization algorithm to obtain the coordinates of all optical ranging units and the constant distance between all measuring points.

[0015] Preferably, step S5 specifically includes: Obtain the distance measurement data set between the optical ranging unit and the target measuring point. Combine the coordinates of all optical ranging units and the constant distance between all measuring points to construct and solve the overdetermined system of equations for the nonlinear least squares problem, and obtain the coordinates of the target measuring point.

[0016] Preferably, in step S1, acquiring distance measurement data between the measuring point on the target object and the optical ranging unit includes: If the target object maintains a fixed posture during the measurement process, distance measurement data with redundancy can be obtained by moving or adding optical ranging units, depending on the degree of occlusion.

[0017] Preferably, step S3 includes: Based on the distance measurement data set between the ranging unit and the measuring point, the coordinates of the optical ranging unit and the measuring point, and with the goal of minimizing the error between the distance value calculated by the coordinates and the actual distance value, an overdetermined set of equations for a nonlinear least squares problem is constructed.

[0018] Preferably, step S5 includes: Obtain the distance measurement data set between the target measuring point and the optical ranging unit. Combine the coordinates of all optical ranging units to construct and solve the overdetermined system of equations for the nonlinear least squares problem, and obtain the coordinates of the target measuring point.

[0019] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention addresses the problem of incomplete ranging data under occlusion conditions by constructing an occlusion-adaptive multilateral measurement model. Even when some ranging observations are missing, the three-dimensional coordinates of the measuring points can still be calculated, thus improving the adaptability and robustness of the multilateral measurement system in complex engineering sites.

[0020] 2. Under a unified technical framework, this invention is applicable to both objects that can change their posture and objects that have a fixed posture, avoiding the problem in the prior art that different measurement strategies are required for different object types, thus improving the versatility and engineering applicability of the method.

[0021] 3. This invention reduces the reliance on additional calibration fixtures or high-precision initial station information by jointly completing the self-calibration of the laser tracker base station location and the calculation of the measurement point coordinates, thereby reducing the difficulty of system deployment and implementation.

[0022] 4. After completing one self-calibration, the present invention can calculate the coordinates of the measuring point based on only a single distance measurement in subsequent measurement processes, which effectively improves the measurement efficiency and is suitable for application scenarios with high efficiency requirements, such as the assembly of large-size components and automatic alignment. Attached Figure Description

[0023] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of a multilateral measurement system for a movable target as described in the embodiment.

[0024] Figure 2 This is a schematic diagram of a multilateral measurement system for an immovable target as described in the embodiment.

[0025] Figure 3 This is a schematic diagram illustrating the establishment of the coordinate system involved in the embodiment.

[0026] Figure 4 This refers to the number of target points required for different degrees of occlusion in the embodiments.

[0027] Figure 5 The results show the accuracy analysis of the coordinate calculation of the measuring points involved in the example. Detailed Implementation

[0028] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0029] This embodiment provides a multi-sided measurement method for laser trackers in occluded environments. The method is applied to large aerospace components, and the measurement scenario and testing requirements are the digital assembly of large components. The method includes: Step S1: Using at least four optical ranging units located in the measurement field, under the condition of occlusion, acquire incomplete distance measurement data between the measuring point on the target object and the optical ranging unit. The incomplete distance measurement data refers to the set of ranging data formed because the measuring point is only observed by some optical ranging units due to occlusion between the measuring point and the optical ranging unit. Step S2: Construct a spatial coordinate system based on the optical ranging unit; Step S3: Based on the distance measurement data set between the measuring point and the optical ranging unit, construct an overdetermined set of equations that includes the coordinates of the optical ranging unit and the measuring point; Step S4: Solve the overdetermined equations using a preset algorithm to obtain the coordinates of the optical ranging unit; Step S5: Based on the coordinates of the optical ranging unit, and according to the measurement requirements, complete the calculation of the three-dimensional coordinates of the target measurement point on the target table object through one or more ranging measurements.

[0030] Within the above framework, different strategies are applied in real time based on the different states of the target object during the measurement process, as detailed below: like Figure 1 As shown, the pose of the target object may change during the measurement process. The specific implementation process is as follows: Step S1: Obtain a set of distance measurement data with redundancy by measuring the measurement points of the target object in at least two different postures, wherein the redundancy indicates that the number of distance measurement data is sufficient to meet the number requirement for constructing overdetermined equations in step S3.

[0031] Based on the above scheme, this embodiment takes two different attitudes as examples. At least four laser tracker base stations (i.e., optical ranging units) are deployed in the measurement field, each maintaining a fixed position during the measurement process. Multiple measurement points are deployed on the target object; these points can be spherical reflective targets or equivalent optical measurement targets. When the target object is in the first attitude, the distance measurement is performed on the measurement points using multiple laser tracker base stations (i.e., optical ranging units). Due to occlusion factors, some measurement points can only be observed by some base stations, meaning the observation path between the base station and the measurement point may be blocked, thus forming the first set of incomplete distance measurement data. A known rigid body attitude transformation is applied to the measured object using an attitude adjustment device, adjusting the measured object from the first attitude to the second attitude. When the measured object is in the second attitude, the distance measurement is repeated on the measurement points to obtain the second set of incomplete distance measurement data formed under occlusion conditions.

[0032] It should be emphasized that this embodiment restricts the base station location to a fixed position for ease of explanation, but in actual measurement, the redundant data can be obtained by moving or adding base stations.

[0033] Step S2: As Figure 3 As shown, using one of the optical ranging units As the origin of the coordinate system, with the optical ranging unit Pointing to another optical ranging unit The direction is Axis, with optical ranging unit To optical ranging unit vector and optical ranging unit Pointing to another optical ranging unit vector The direction of the vector obtained by the product of the two is The axis is determined by the right-hand rule. The axes are used to construct a spatial coordinate system.

[0034] Based on the above scheme, a coordinate system can be determined using any three laser tracker base stations. First, the origin is determined, then the X-axis, then the Z-axis, and finally the Y-axis. It should be noted that since the product of two vectors is perpendicular to the two vectors themselves (i.e., the product vector is perpendicular to the plane formed by the two vectors), the Z-axis can be determined. In this spatial coordinate system, the laser tracker base station serves as the origin. coordinates for Laser tracker base station lie in On the axis, its coordinates for Laser tracker base station Located on the XY plane, therefore its coordinates for Other base stations The coordinates are Therefore, in this coordinate system, the number of variables that need to be solved is reduced by 6, which further reduces the difficulty of subsequent solutions.

[0035] It is important to emphasize that if mobile base stations are needed to increase data, then the originating base station... Cannot be moved, base station The base station can only move along the X-axis. It can only move in the XY plane, thus ensuring that the spatial coordinate system remains anchored.

[0036] Step S3: Based on the distance measurement data set between the optical ranging unit and the measuring point under different poses of the target object, the coordinates of the optical ranging unit and the measuring point, and the constraint that the distance between the measuring points is constant, an overdetermined set of equations for a nonlinear least squares problem is constructed with the goal of minimizing the error between the distance value calculated by the coordinates and the actual distance value. Step S4: Solve the overdetermined equations using a nonlinear least squares optimization algorithm to obtain the coordinates of all optical ranging units and the constant distance between all measuring points.

[0037] Based on the above scheme, this embodiment constructs an occlusion-adaptive polygonal measurement model based on the ranging data obtained in the first and second postures. At the same time, during the modeling process, a distance constraint that remains unchanged between measurement points under different postures is introduced to jointly solve the laser tracker base station position and the three-dimensional coordinates of the measurement points, thereby realizing base station self-calibration.

[0038] The equation constructed based on the distance between the laser tracker base station and the site is as follows:

[0039] In the formula, This indicates the coordinates of the target laser tracker base station. This represents the coordinates of the target measurement point under the target's attitude. The variables are represented as an observation matrix. Represents the solution of the 2-norm. This indicates the distance between the target measurement point and the target optical ranging unit under the target's attitude. Based on the constraint that the distance between the two measuring points is constant, the equations are constructed as follows:

[0040] In the formula, This represents the coordinates of a target measurement point. Indicates the coordinates of another target measurement point. This represents the distance between two target measurement points under the same attitude. By incorporating data from the first and second attitudes, the following system of equations can be constructed:

[0041] Therefore, the smaller the residual between the calculated coordinates and the actual values, the more accurate the calculated coordinates and distances. Thus, a nonlinear least squares problem model is introduced, a solution function is constructed, and the coordinates and distances are calculated. The specific solution function is as follows:

[0042] Among them, the unknown vector The expression is as follows:

[0043] In the formula, Indicates the location of the base station. Indicates the coordinates of the measuring point. Indicates the distance between target points. This represents the coordinates of the i-th station. This represents the coordinates of the measurement point in the first attitude. This indicates the coordinates of the measurement point in the second attitude. This represents the coordinates of the target measurement point in the first pose of the target object. This represents the coordinates of the target measurement point in the second pose of the target object. The variables are represented as an observation matrix. Represents the solution of the 2-norm. This represents the distance between the j-th target measurement point and the i-th target base station in the i-th pose of the target object. This represents the distance between the first i-th measurement point and the j-th measurement point under the same posture.

[0044] It should be noted that the condition for the above-mentioned solution function to be overdetermined is that the number of equations is greater than the number of unknowns. Traditional modeling only establishes a system of equations based on the distance between the base station and the measurement points. This method, on the other hand, introduces the rule that the distance between two measurement points remains constant under different attitudes as a new constraint, constructing more equations. Although this introduces more unknowns, such as the distance between two measurement points and the coordinates of the measurement points under new attitudes, since the distance between two measurement points remains constant under different attitudes, this unknown will only be introduced once and will not increase with the increase of the number of different attitudes. The only thing that will increase with the number of attitudes is the coordinate position of the measurement points under different attitudes. The rate at which the number of equations increases with the number of attitudes exceeds the rate at which the number of unknowns increases, and this rate increases geometrically with the number of measurement points. Therefore, theoretically, as long as the number of measurement points reaches a threshold, regardless of the degree of occlusion, as long as the number of attitudes is sufficient, the number of equations can be greater than the number of unknowns, i.e., overdetermined equations can be constructed. At the same time, the more measurement points there are, the smaller the number of attitudes required. The specific proof is as follows: Let N be the number of measurement points, I be the number of laser trackers, and K be the number of attitudes. Then, the number of unknowns R is: The number of equations, S, is: ,in To quantify the degree of occlusion, the principle is as follows: Due to occlusion, the observation path between some base stations and the measurement point is blocked during measurement. Since each base station can obtain distance measurement data by observing one measurement point, the ratio between the actual number of distance data obtained from the observed measurement point and the theoretically obtainable number can measure the effectiveness of a single distance measurement. Therefore, the expression for the degree of occlusion can be derived:

[0045] in, This indicates the amount of data obtained in a single measurement of the target object.

[0046] From the above equation, we can obtain: Furthermore, a single distance measurement data point can be used to construct an equation, which further demonstrates the logical closed loop of the number of equations S.

[0047] It should be noted that, theoretically, the degree of occlusion... The value changes as the target changes, but in practice, because the change in attitude is relatively small, the degree of occlusion is not significant when the number of attitude changes is limited. The changes are negligible; however, if there are many changes in posture, it will cause occlusion. The variations are significant, but for ease of explanation, and since the actual measurement will not involve many changes in posture, they are all ignored in this embodiment.

[0048] When the number of equations S is greater than or equal to the number of unknowns R, it indicates that the solution function constructed above is an overdetermined equation, and a solution must exist, that is:

[0049] Furthermore, it can be seen that with each attitude change, the number of unknowns and equations increases as follows:

[0050]

[0051] because large growth rate Therefore, it must exist. , , The solution makes , and when At that time, more data can be obtained by changing the posture, depending on the number of base stations (I) and the degree of obstruction. With the number of measuring points N remaining constant, make the original The situation has become Thus, overdetermined equations are constructed; Traditional modeling only establishes equations based on the distance between the base station and the measurement point, that is: Therefore, under traditional modeling methods, the number of unknowns R' is The number of equations S' is To construct overdetermined equations, that is... , This model cannot transform the underdetermined equations into an overdetermined equations system by changing the pose of the target object.

[0052] Furthermore, as shown in the above formula, this can be achieved by increasing the number of measuring points N and the number of base stations I. This improves the degree of occlusion. The inclusiveness can also be achieved by simply increasing the number of measurement points N. This improves the degree of occlusion. And the tolerance of the number of base stations I, that is, it can be flexibly adjusted according to the actual situation. , , Three variables to achieve .

[0053] when hour, The growth rate is greater than At this point, the model reaches its maximum tolerance for occlusion during self-calibration, meaning that a solution can be obtained as long as the number of pose transformations is sufficient.

[0054] In practical applications, the number of pose transformations is usually limited. In this embodiment, the target object's pose is limited to two types: a first pose and a second pose. Under this limitation, the acceptable degree of occlusion is determined to satisfy the conditions for constructing the overdetermined equations. The relationship between the number of measurement points N and the measurement points is as follows: Figure 4 As shown in the figure, when the number of base stations I is 4, the feasible area that can complete self-calibration under different numbers of measurement points is illustrated.

[0055] Under the same conditions, i.e., the number of base stations I is 4, when using the traditional calibration method, even under unobstructed conditions, i.e. Even with traditional methods, six measurement points are needed to obtain sufficient data to construct an overdetermined system of equations. However, using the method in this embodiment, even with occlusion, when... Overdetermined equations can be constructed using only 5 measurement points.

[0056] Under the above conditions, when the specified number of measuring points N is 8, the method of this embodiment is adopted. That's it, whereas using traditional methods... Only then will it work.

[0057] Step S5 specifically includes: Obtain the distance measurement data set between the optical ranging unit and the target measuring point. Combine the coordinates of all optical ranging units and the constant distance between all measuring points to construct and solve the overdetermined system of equations for the nonlinear least squares problem, and obtain the coordinates of the target measuring point.

[0058] It should be noted that after completing step S4 calibration, when the measured object undergoes subsequent attitude changes, only one distance measurement is needed in the current attitude to complete the calculation of the three-dimensional coordinates of the measurement point, as detailed below: A set of observation equations is constructed by combining the distance between the base station and the measuring point, as well as the distance between any two measuring points:

[0059] Therefore, the corresponding least squares problem model is constructed:

[0060] In the formula, Indicates the coordinates of the measurement point under subsequent attitude. Indicates the distance between target points. This represents the coordinates of the i-th station. Represents the solution of the 2-norm. This represents the distance between the j-th target measurement point and the i-th target base station in the i-th pose of the target object. This represents the distance between the first i-th measurement point and the j-th measurement point under the same attitude. At this point, since the base station coordinates, the distance between the base station and the measurement points, and the distance between any measurement points are known, the only unknowns are the coordinates of the measurement points on the target object after the attitude change. The number of unknowns, R, is 3N, and the number of equations constructed is S. ,when This can form overdetermined equations. This coordinate calculation model, under the same conditions, varies with the degree of occlusion. It is more inclusive, such as Figure 4 As shown, the more measurement points there are, the larger the feasible region of the measurement points, and the better the effect on the degree of occlusion. The higher the tolerance.

[0061] It should be noted that this invention does not limit the specific numbers of attitude transformation, base stations, and measurement points. In other cases, the method proposed in this invention is still applicable.

[0062] like Figure 2 As shown, the specific implementation process for a multilateral measurement system dealing with immovable components is as follows: Step S1: Based on the degree of occlusion, obtain distance measurement data with redundancy by moving or adding optical ranging units.

[0063] Based on the above scheme, multiple laser tracker measurement stations are planned within the measurement field, so that each measurement point can be observed multiple times at different stations. Several reference points are set up within the measurement field, and the spatial position of the reference points remains unchanged during the measurement process. Distance measurements are performed on the reference points at different measurement stations to obtain complete reference point distance data.

[0064] Step S2: Constructing the coordinate system is the same as in step S2 above.

[0065] Step S3: Based on the distance measurement data set between the ranging unit and the measuring point, the coordinates of the optical ranging unit and the measuring point, and with the goal of minimizing the error between the distance value calculated from the coordinates and the actual distance value, construct an overdetermined system of equations for a nonlinear least squares problem. Step S4: Solve the overdetermined equations using a nonlinear least squares optimization algorithm to obtain the coordinates of all optical ranging units and the constant distance between all measuring points.

[0066] Based on the above scheme, when dealing with immovable target objects, a system of equations is constructed solely based on the distance between the measuring point and the base station:

[0067] And thus construct the solution function:

[0068] in Represented as

[0069] In the formula, Indicates the coordinates of the measuring point. This represents the coordinates of the i-th station. Represents the solution of the 2-norm. This represents the distance between the j-th target measurement point and the i-th target base station in the i-th pose of the target object. This method improves the performance against occlusion by increasing the number of base stations or moving the base stations. The degree of inclusivity.

[0070] Step S5: After completing the base station location calibration, using the ranging data obtained from multiple measurement stations, perform polygonal measurement calculations on the three-dimensional coordinates of the measurement points. The calculation equations are as follows:

[0071] In the formula, Indicates the coordinates of the remaining measuring points. This represents the coordinates of the i-th station. Represents the solution of the 2-norm. This represents the distance between the j-th target measurement point and the i-th target base station in the i-th pose of the target object.

[0072] To verify the feasibility and accuracy of the proposed method, Monte Carlo simulations were performed. The simulations were conducted within a simulated measurement region, using realistic instrument error specifications. The simulations included... Key points: Simulations of movable objects were performed at three occlusion levels. Simulations of immovable objects were performed at a single occlusion level. The occlusion scenario was randomly configured based on the occlusion level. In practice, traditional methods are not feasible in the presence of occlusion. Therefore, simulations using traditional methods without occlusion were performed as a reference for comparing the accuracy with the proposed method. 1000 Monte Carlo simulations were performed.

[0073] The sources of measurement error were considered in the simulation. The overall measurement uncertainty was addressed using... It means that its expression is

[0074] in, It is the distance between the laser rangefinder's position and the measurement point. This represents the inherent instrument error caused by a uniform random distribution. This represents the distance-related error, which is also generated by a uniform random distribution.

[0075] Figure 5The mean absolute error (MAE) and correlation of the coordinate calculation results for eight simulated keypoints in three directions are presented. For the measurement of movable objects, the MAE in occluded scenarios 1 (12%) and 2 (24%) is comparable to that of the conventional method under unoccluded conditions. Accuracy and repeatability decrease slightly due to the effect of occlusion. However, in occluded scenario 3 (36%), accuracy decreases significantly, indicating that this method is not applicable under such severe occlusion conditions. For immovable objects, the proposed method outperforms the conventional method in both accuracy and repeatability, even under severe occlusion. This superiority is attributed to the increased number of laser trackers in the proposed method and the corresponding measurement data. This advantage is attributed to the increased number of laser trackers and the corresponding measurement data in the proposed method.

[0076] The present invention also provides a multi-sided measurement system for a laser tracker in an occluded environment. The multi-sided measurement system for a laser tracker in an occluded environment can be implemented by executing the process steps of the multi-sided measurement method for a laser tracker in an occluded environment. That is, those skilled in the art can understand the multi-sided measurement method for a laser tracker in an occluded environment as a preferred embodiment of the multi-sided measurement system for a laser tracker in an occluded environment.

[0077] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0078] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A multi-sided measurement method for a laser tracker in occluded environments, characterized in that, include: Step S1: Under occlusion conditions, acquire distance measurement data between the measuring point on the target object and the optical ranging unit using at least four optical ranging units located in the measurement field; Step S2: Construct a spatial coordinate system based on the optical ranging unit; Step S3: Based on the distance measurement data set between the measuring point and the optical ranging unit, construct an overdetermined set of equations that includes the coordinates of the optical ranging unit and the measuring point; Step S4: Solve the overdetermined equations using a preset algorithm to obtain the coordinates of the optical ranging unit; Step S5: Based on the coordinates of the optical ranging unit, and according to the measurement requirements, complete the calculation of the three-dimensional coordinates of the target measurement point on the target table object through one or more ranging measurements.

2. The method according to claim 1, characterized in that, In step S1, the distance measurement data between the measuring point on the target object and the optical ranging unit is obtained, including: If the target object undergoes a rigid body posture change during the measurement process, a set of distance measurement data with redundancy is obtained by measuring the measurement points of the target object under at least two different postures. The redundancy indicates that the number of distance measurement data is sufficient to meet the number requirement for constructing overdetermined equations in step S3.

3. The method according to claim 1, characterized in that, Step S2 specifically includes: With one of the optical ranging units As the origin of the coordinate system, with the optical ranging unit Pointing to another optical ranging unit The direction is Axis, with optical ranging unit To optical ranging unit vector and optical ranging unit Pointing to another optical ranging unit vector The direction of the vector obtained by the product of the two is The axis is determined by the right-hand rule. The axes are used to construct a spatial coordinate system.

4. The method according to claim 2, characterized in that, Step S3 specifically includes: Based on the distance measurement data set between the optical ranging unit and the measuring point under different postures of the target object, the coordinates of the optical ranging unit and the measuring point, and the constraint that the distance between the measuring points is constant, an overdetermined set of equations for a nonlinear least squares problem is constructed with the goal of minimizing the error between the distance value calculated by the coordinates and the actual distance value.

5. The method according to claim 4, characterized in that, Step S4 specifically includes: The overdetermined equations are solved using a nonlinear least squares optimization algorithm to obtain the coordinates of all optical ranging units and the constant distance between all measuring points.

6. The method according to claim 5, characterized in that, Step S5 specifically includes: Obtain the distance measurement data set between the optical ranging unit and the target measuring point. Combine the coordinates of all optical ranging units and the constant distance between all measuring points to construct and solve the overdetermined system of equations for the nonlinear least squares problem, and obtain the coordinates of the target measuring point.

7. The method according to claim 1, characterized in that, In step S1, the distance measurement data between the measuring point on the target object and the optical ranging unit is obtained, including: If the target object maintains a fixed posture during the measurement process, distance measurement data with redundancy can be obtained by moving or adding optical ranging units, depending on the degree of occlusion.

8. The method according to claim 7, characterized in that, Step S3 includes: Based on the distance measurement data set between the ranging unit and the measuring point, the coordinates of the optical ranging unit and the measuring point, and with the goal of minimizing the error between the distance value calculated by the coordinates and the actual distance value, an overdetermined set of equations for a nonlinear least squares problem is constructed.

9. The method according to claim 8, characterized in that, Step S5 includes: Obtain the distance measurement data set between the target measuring point and the optical ranging unit. Combine the coordinates of all optical ranging units to construct and solve the overdetermined system of equations for the nonlinear least squares problem, and obtain the coordinates of the target measuring point.

10. A multi-sided measurement system for a laser tracker in occluded environments, characterized in that, include: Module M1: Using at least four optical ranging units located in the measurement field, under occlusion conditions, acquire incomplete distance measurement data between the measuring point on the target object and the optical ranging unit. The incomplete distance measurement data refers to the set of ranging data formed because the measuring point is only observed by a portion of the laser tracker base station due to occlusion between the measuring point and the optical ranging unit. Module M2: Constructs a spatial coordinate system based on the optical ranging unit; Module M3: Based on the distance between the measuring point and the optical ranging unit, construct an overdetermined system of equations containing the coordinates of the optical ranging unit and the measuring point. Module M4: Solves the overdetermined equations using a preset algorithm to obtain the coordinates of the optical ranging unit; Module M5: Based on the coordinates of the optical ranging unit, it calculates the three-dimensional coordinates of the target measurement points on the target table object through single or multiple ranging measurements according to measurement requirements.

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