Dual-robot wide-range collaborative measurement method and system

Abstract

A dual-robot wide-range collaborative measurement method and system. The method comprises: 1. measuring the coordinates of mark points; 2. scanning a target object; during scanning, if the field of view is limited, entering 3, or, if the field of view is not limited, continuing scanning until the scanning is complete; 3. calculating rotation matrices and translation vectors from mark point coordinate systems of adjacent stations to a tracking robot coordinate system, constructing a relational expression between the rotation matrices and the translation vectors of the adjacent stations, calculating a rotation matrix and a translation vector from the next station to the previous station, and constructing a relational expression from points scanned by the next station to the previous station; and 4. during scanning, if the field of view is limited, using the relational expression from the points scanned by the next station to the previous station to merge scanning point clouds of the two stations, until the scanning is complete. According to the present invention, automatic station changing between any two adjacent stations can be achieved, and scanning results of any station can be transformed into coordinate systems of other stations, thereby implementing the merging of scanning results between stations.

Description

A dual-robot large-range cooperative measurement method and system

[0001] The present application claims priority to the Chinese patent application filed on September 26, 2024, with the Chinese Patent Office, the application number of which is 2024113469961, and the title of which is "A dual-robot large-range cooperative measurement method and system", the whole content or part of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present application relates to the technical field of three-dimensional scanning, in particular to a dual-robot large-range cooperative measurement method and system. BACKGROUND

[0003] There are many three-dimensional scanning systems at present, but they are suitable for different scenes. Among them, the tracking three-dimensional scanning system is applied to the three-dimensional scanning tasks of various large workpieces due to its significant advantages of no need to paste points, high efficiency and high precision, and wide scanning range. When the tracking three-dimensional scanning system is applied to tasks such as scanning large aircraft models and scanning the front and back surfaces of large models, the maximum scanning depth and width of the tracking three-dimensional scanning system are limited to the tracking camera, which is only less than 10m, and the scanning task cannot be completed at one time. Therefore, it is necessary to manually move the tracking camera to the next measurement station for scanning task, and the point clouds of the two scanning tasks need to be registered to realize the merging of the two scanning results. However, in the point cloud registration, a part of the precision may be lost, and the manual movement of the tracking camera is not conducive to the application of the three-dimensional scanning system in the automatic scene. Another method of moving the measurement station is to preset some marker points around the target. When changing the measurement station, the merging of the two scanning results can be realized according to these marker points. However, manual presetting of the marker points is not conducive to the application in the automatic scene. SUMMARY

[0004] The present application provides a dual-robot large-range cooperative measurement method and system to solve the technical problems mentioned in the background.

[0005] To achieve the above-mentioned purpose, the technical solution of the present application is as follows:

[0006] The present application provides a dual-robot large-range cooperative measurement method, which comprises the following steps:

[0007] S1, first measure the three-dimensional coordinates of a plurality of marker points on the scanner in the measurement robot using a photogrammetric device;

[0008] S2, scanning the target object according to the set route using the scanner on the measuring robot, and tracking the measuring robot in real time using the tracking robot to obtain the spatial pose of the measuring robot; in the process of scanning, it is judged in real time whether the field of view of the tracking robot is limited, if yes, entering S3, otherwise, continuing to scan until the scanning of the target object is completed;

[0009] S3, calculating the rotation matrix and the translation vector from the coordinate system of the marker points of the adjacent two stations to the coordinate system of the tracking robot according to the three-dimensional coordinates of the plurality of marker points on the scanner in S1, and the Gauss-Newton method, constructing a relationship formula of the rotation matrix and the translation vector of the adjacent two stations, and calculating the rotation matrix and the translation vector of the next station to the previous station according to the relationship formula, and finally constructing a relationship formula of the points scanned by the next station to the previous station according to the rotation matrix and the translation vector of the next station to the previous station, so as to realize the merging of the point clouds scanned by the two stations.

[0010] S4, continuing to scan the target object according to the set route using the scanner on the measuring robot, if the field of view of the tracking robot is limited, merging the point clouds scanned by the two stations using the relationship formula of the points scanned by the next station to the previous station in S3, until the scanning of the target object is completed.

[0011] Further, the coordinate system in which the three-dimensional coordinates of the plurality of marker points in S1 are located is a marker point coordinate system, and the three-dimensional coordinates of the i-th marker point in the marker point coordinate system are specifically:

[0012] wherein, represents the i-th marker point in the marker point coordinate system, and represents the coordinate value of the i-th marker point in the marker point coordinate system on the X, Y and Z axes.

[0013] Further, S3 specifically includes the following steps:

[0014] S31, measuring the plurality of marker points around the scanner using the tracking robot at the m-th station to obtain the three-dimensional coordinates of the plurality of marker points on the tracking robot coordinate system of the 0-th frame of the m-th station, which are specifically as follows:

[0015] wherein, represents the i-th marker point located on the tracking robot coordinate system photographed by the 0-th frame of the m-th station; and represents the coordinate value of the i-th marker point on the X, Y and Z axes of the 0-th frame of the m-th station on the tracking robot coordinate system.

[0016] S32. Using the coordinates of the marker points measured by the tracking robot in S31 and their corresponding real coordinates as constraints, and based on the three-dimensional coordinates of multiple marker points on the scanner in S1, calculate the rotation matrix from the coordinate system of the marker point at the m-th station in frame 0 to the coordinate system of the tracking robot using the Gauss-Newton method. The optimal value and the translation vector from the coordinate system of the marker point in frame 0 of the m-th station to the coordinate system of the tracking robot. The optimal value;

[0017] S33. Construct the three-dimensional coordinates of the i-th marker point obtained in S31 in the tracking robot coordinate system and the rotation matrix finally obtained in S32. Translation vector Relationships;

[0018] S34. With the scanner stationary, the measuring robot moves to the (m+1)th measuring station and calculates the rotation matrix from the coordinate system of the marker point in frame 0 of the (m+1)th measuring station to the coordinate system of the tracker, using the steps described in S31 to S32. The optimal value and the translation vector from the coordinate system of the marker point in frame 0 of the (m+1)th station to the tracker coordinate system. The optimal value;

[0019] S35. Construct the three-dimensional coordinates of the i-th marker point obtained in S31 in the tracking robot coordinate system and the rotation matrix finally obtained in S34. Translation vector Relationships;

[0020] S36. Based on the relationships in S33 and S35, construct the relationships between the rotation matrix and translation vector of two adjacent stations.

[0021] S37. Calculate the rotation matrix from the (m+1)th station to the mth station based on the relation in S36. Translation vector

[0022] S38. Rotation matrix obtained using S37 Translation vector Construct a relational expression for transferring the k-th point of the target object scanned at the (m+1)-th station to the m-th station, that is, a relational expression for transferring the point scanned at the next station to the previous station, thereby realizing the merging of the point clouds scanned by the two stations.

[0023] Furthermore, step S32 specifically includes the following steps:

[0024] S341, coordinate values of the i-th marker point are converted from the marker point coordinate system to the tracking robot coordinate system, and the three-dimensional coordinate values of the i-th marker point in the tracking robot coordinate system in S31 are subtracted to obtain the conversion error v of the i-th marker point i ;

[0025] S342, then the conversion error v of the i-th marker point i is used to construct an optimization function about the conversion errors of multiple marker points by means of the Gauss-Newton method;

[0026] S343, by iteratively optimizing the optimization function, an update amount ΔX is obtained each time, and then the rotation matrix and the translation vector of the 0th frame marker point coordinate system to the tracking robot coordinate system of the mth station are updated using the update amount ΔX, and after multiple iterations of optimization, the optimal value of the rotation matrix of the 0th frame marker point coordinate system to the tracking robot coordinate system of the mth station, and the optimal value of the translation vector of the 0th frame marker point coordinate system to the tracking robot coordinate system of the mth station are obtained.

[0027] Further, the conversion error v of the i-th marker point in S341 is i , which is expressed by the following formula:

[0028] Further, the optimization function in S342 is as follows:

[0029] Wherein, N represents the number of point pairs of the marker points measured by the tracking robot and the corresponding real marker points; T represents the transpose of the matrix, and F(.) represents the to-be-optimized function solved by the Gauss-Newton method.

[0030] Further, the relationship in S33 is specifically:

[0031] The relationship in S35 is specifically:

[0032] The relationship of the rotation matrix and the translation vector of the adjacent two stations in S36 is specifically:

[0033] Further, the calculation formula of the rotation matrix and the translation vector in S37 is as follows:

[0034] Further, the relationship of the kth point of the target object scanned on the m+1th station in S38 to the mth station is specifically as follows:

[0035] wherein, represents the kth point of the target object scanned on the mth station after conversion.

[0036] Another aspect of the present application also provides a double-robot large-range collaborative measurement system using the above double-robot large-range collaborative measurement method for measurement, and the double-robot large-range collaborative measurement system comprises:

[0037] a measurement robot comprising a first automatic guided vehicle, a mechanical arm mounted on a first lifting mechanism in the first automatic guided vehicle, and a scanner mounted on an execution end of the mechanical arm;

[0038] a tracking robot comprising a second automatic guided vehicle, a holder mounted on a second lifting mechanism in the second automatic guided vehicle, and a binocular three-dimensional tracker mounted on the holder.

[0039] The present application has the following beneficial effects:

[0040] 1. The double-robot large-range collaborative measurement method provided by the present application can realize automatic station switching between any two adjacent stations, and can transform the scanning results of any station into the coordinate system of other stations to realize the merging of scanning results between stations.

[0041] 2. The present application also provides a double-robot large-range collaborative measurement system comprising a measurement robot and a tracking robot, both of which are driven by respective automatic guided vehicles, and realize automatic three-dimensional scanning without manual movement, which is highly automated and reduces the labor intensity of scanning personnel. BRIEF DESCRIPTION OF DRAWINGS

[0042] Fig. 1 is a flowchart of the double-robot large-range collaborative measurement method in the present application;

[0043] Fig. 2 is a structural schematic diagram of the double-robot large-range collaborative measurement system in the present application. DETAILED DESCRIPTION

[0044] In order to facilitate the understanding of the present application, the present application will be described more fully below with reference to the accompanying drawings. The preferred embodiments of the present application are shown in the drawings. However, the present application can be realized in many other different forms, and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0045] It is to be noted that when an element is referred to as being "fixed" or "set" on another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or indirectly connected to the other element.

[0046] In addition, the terms "first", "second", "third", etc. are used only for descriptive purposes and should not be construed as indicating or implying relative importance or an indicated number of technical features. Therefore, the features defined as "first", "second", etc. can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0047] Referring to FIG. 1, the embodiment of the present application provides a double-robot large-range cooperative measurement method, comprising the following steps:

[0048] S1, first, using a photogrammetric device to measure the three-dimensional coordinates of a plurality of mark points on a scanner in a measurement robot;

[0049] S2, using the scanner on the measurement robot to scan the target object according to the set route, and simultaneously using the tracking robot to track the measurement robot in real time to obtain the spatial pose of the measurement robot; during the scanning process, it is judged in real time whether the field of view of the tracking robot is limited, if yes, it is entered into S3, otherwise the scanning is continued until the scanning of the target object is completed;

[0050] Specifically, the tracking robot is installed with a depth camera, and the tracking robot is built-in with a visual recognition algorithm, and the depth camera and the visual recognition algorithm can be used to judge in real time whether the field of view of the tracking robot is limited; in addition, the judgment rule of whether the field of view is limited is that when the tracking robot cannot track the target (i.e. the plurality of mark points on the scanner), it is determined that the field of view is limited;

[0051] S3, according to the three-dimensional coordinates of the plurality of mark points on the scanner in S1, and by means of the Gauss-Newton method, the rotation matrix and the translation vector of the coordinate system of the mark points of the adjacent two stations to the coordinate system of the tracking robot are calculated, and the relationship formula of the rotation matrix and the translation vector of the adjacent two stations is constructed, and the rotation matrix and the translation vector of the next station to the last station are calculated according to the relationship formula, and finally the relationship formula of the points scanned by the next station to the last station is constructed according to the rotation matrix and the translation vector of the next station to the last station, so as to realize the merging of the scanning point clouds of the two stations.

[0052] S4, continue to scan the target object by using the scanner on the measuring robot according to the set route, if the field of view of the tracking robot is limited, then use the relationship formula of the point scanned by the next measuring station in S3 to the last measuring station to combine the point clouds of the two measuring stations until the scanning of the target object is completed.

[0053] In some embodiments, the coordinate system in which the three-dimensional coordinates of the plurality of marker points in S1 are located is a marker point coordinate system, and the three-dimensional coordinates of the i-th marker point in the marker point coordinate system are specifically:

[0054] wherein, represents the i-th marker point in the marker point coordinate system, and represents the coordinate values of the i-th marker point in the marker point coordinate system on the X, Y and Z axes.

[0055] In some embodiments, S3 specifically comprises the following steps:

[0056] S31, measure a plurality of marker points around the scanning instrument using the tracking robot at the m-th measuring station to obtain the three-dimensional coordinates of the plurality of marker points in the tracking robot coordinate system at the 0-th frame of the m-th measuring station, which are specifically as follows:

[0057] wherein, represents the i-th marker point located in the tracking robot coordinate system photographed at the 0-th frame of the m-th measuring station; and represents the coordinate values of the i-th marker point in the tracking robot coordinate system at the 0-th frame of the m-th measuring station on the X, Y and Z axes.

[0058] S32, taking the marker point coordinates measured by the tracking robot in S31 and the corresponding real coordinates as constraints, calculating the optimal value of the rotation matrix of the marker point coordinate system at the 0-th frame of the m-th measuring station to the tracking robot coordinate system and the optimal value of the translation vector of the marker point coordinate system at the 0-th frame of the m-th measuring station to the tracking robot coordinate system according to the three-dimensional coordinates of the plurality of marker points on the scanning instrument in S1 and by means of the Gauss-Newton method;

[0059] S33, constructing the relationship between the three-dimensional coordinates of the i-th marker point in the tracking robot coordinate system obtained in S31 and the rotation matrix and the translation vector finally obtained in S32;

[0060] S34, under the premise that the scanner is stationary, the robot moves to the m+1th measuring station, and the rotation matrix of the 0th frame of the m+1th measuring station is calculated according to the steps S31 to S32 , and the optimal value of the translation vector of the 0th frame of the m+1th measuring station to the tracker coordinate system ;

[0061] S35, the relationship between the three-dimensional coordinates of the i th marker point in the tracking robot coordinate system obtained in S31 and the rotation matrix and the translation vector obtained in S34 is established;

[0062] S36, the relationship between the rotation matrix and the translation vector of the adjacent two measuring stations is established according to the relationship in S33 and the relationship in S35;

[0063] S37, the rotation matrix and the translation vector of the m+1th measuring station to the mth measuring station are calculated according to the relationship in S36;

[0064] S38, the rotation matrix and the translation vector obtained in S37 are used to establish the relationship of the kth point in the target object scanned on the m+1th measuring station to the mth measuring station, i.e. the relationship of the point scanned on the next measuring station to the previous measuring station, so as to realize the merging of the point clouds scanned on the two measuring stations.

[0065] In some embodiments, the S32 specifically comprises the following steps:

[0066] S341, the coordinate value of the i th marker point is converted from the marker point coordinate system to the tracking robot coordinate system, and is subtracted from the three-dimensional coordinate value of the i th marker point in the tracking robot coordinate system in S31 to obtain the conversion error v i of the i th marker point;

[0067] S342, then the conversion error v i of the i th marker point is used to construct an optimization function about the conversion errors of multiple marker points by means of the Gauss-Newton method;

[0068] S343, the optimization function is iteratively optimized to obtain an update amount ΔX each time, and then the rotation matrix and the translation vector of the 0th frame of the mth measuring station to the tracking robot coordinate system are updated by using the update amount ΔX, and after multiple iterative optimizations, the rotation matrix of the 0th frame of the mth measuring station to the tracking robot coordinate system is obtained the optimal value of the translation vector from the coordinate system of the mth station 0th frame marker to the coordinate system of the tracking robot the optimal value of the translation vector from the coordinate system of the mth station 0th frame marker to the coordinate system of the tracking robot

[0069] Specifically, is a third-order matrix, is a three-dimensional vector.

[0070] In some embodiments, the conversion error v i , which is specifically as follows:

[0071] In some embodiments, the optimization function in S342 is specifically as follows:

[0072] wherein N represents the number of point pairs of the markers measured by the tracking robot and the corresponding real markers; T represents the transpose of the matrix, and F(.) represents a to-be-optimized function solved by the Gauss-Newton method.

[0073] S343 specifically comprises the following steps:

[0074] S3431, first, the conversion error v i and the partial derivative of is specifically as follows:

[0075] wherein I is a third-order unit matrix, and ^ is an antisymmetric symbol; is a partial derivative symbol;

[0076] S3432, then, the Gauss-Newton method is used to solve the update amount ΔX at each time in the optimization function iteration process, which is specifically as follows:

[0077] ΔX=H -1 J (10)

[0078] wherein H represents a first cumulative number, which is a 6-order matrix, J represents a second cumulative number, which is a 6-dimensional vector, and ΔX is a 6-dimensional vector;

[0079] S3433, the update amount ΔX is converted into a rotation matrix ΔR and a translation vector Δt, and the rotation matrix and the translation vector are updated, and after multiple iteration optimizations, the optimal value of the rotation matrix from the coordinate system of the mth station 0th frame marker to the coordinate system of the tracking robot, and the optimal value of the translation vector from the coordinate system of the mth station 0th frame marker to the coordinate system of the tracking robot The optimal value is expressed by the following formula:

[0080] R k+1 =ΔRR k (14)

[0081] t k+1 =ΔRt k +Δt (15)

[0082] Where Δt represents the translation vector increment in each iteration, The increment of the rotation vector in each iteration is represented by Δt. n, t k All are three-dimensional vectors, θ is a scalar, and ΔR and R are... k R k+1 R is a third-order matrix. k Let t represent the rotation matrix at the k-th iteration. k Let the translation vector and rotation matrix be the vector for the k-th iteration. Optimal value, translation vector The optimal value can be obtained by iterating through formulas (14)-(15).

[0083] In some embodiments, the relation in S33 is specifically:

[0084] The specific relation in S35 is as follows:

[0085] The relationship between the rotation matrix and translation vector of two adjacent stations in S36 is as follows:

[0086] In some embodiments, the rotation matrix in S37 Translation vector The calculation formula is as follows:

[0087] In some embodiments, the specific formula for the transfer of the k-th point of the target object scanned at the (m+1)-th station to the m-th station in step S38 is as follows:

[0088] in, This represents the k-th point of the target object scanned at the m-th station after the conversion.

[0089] The dual-robot large-scale collaborative measurement method provided by this invention can realize automated station switching between any two adjacent measuring stations, and can transform the scanning results of any measuring station to the coordinate system of other measuring stations, thereby realizing the merging of scanning results between measuring stations.

[0090] The application also provides a double-robot large-range cooperative measurement system using the above double-robot large-range cooperative measurement method for measurement, and the double-robot large-range cooperative measurement system comprises:

[0091] The measurement robot comprises a first automatic guided vehicle, a mechanical arm installed on a first lifting mechanism in the first automatic guided vehicle, and a scanner installed on an execution end of the mechanical arm.

[0092] The tracking robot comprises a second automatic guided vehicle, a holder installed on a second lifting mechanism in the second automatic guided vehicle, and a binocular three-dimensional tracker installed on the holder.

[0093] The double-robot large-range cooperative measurement system provided by the application comprises a measurement robot and a tracking robot, and the measurement robot and the tracking robot are driven by respective automatic guided vehicles, so that automatic three-dimensional scanning is realized without manual movement, the degree of automation is high, and the labor intensity of scanning personnel is reduced.

[0094] In use, the double-robot large-range cooperative measurement system needs to acquire a map of a scene where a target is located through other hardware (such as a laser radar), and then set measurement stations and scanning points for the first automatic guided vehicle and the second automatic guided vehicle according to the map.

[0095] The above is only a specific embodiment of the application, but the protection scope of the application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the application, which should be covered within the protection scope of the application. Furthermore, the technical solutions of each embodiment of the application can be combined with each other, but it must be based on the realization by a person skilled in the art, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, and is not within the protection scope required by the application. Therefore, the protection scope of the application should be subject to the protection scope of the claims.

Claims

1. A double-robot large-range cooperative measurement method, characterized in that, The method comprises the following steps: S1, first, using a photogrammetric device to measure the three-dimensional coordinates of a plurality of mark points on a scanner in a measuring robot; S2, using the scanner on the measuring robot to scan the target object according to a set route, and simultaneously using a tracking robot to track the measuring robot in real time to obtain the spatial pose of the measuring robot; in the process of scanning, it is judged in real time whether the field of view of the tracking robot is limited, if yes, entering S3, otherwise, continuing to scan until the scanning of the target object is completed; S3, according to the three-dimensional coordinates of the plurality of mark points on the scanner in S1, and by means of Gauss-Newton method, the rotation matrix and the translation vector of the mark point coordinate system of the adjacent two stations to the tracking robot coordinate system are calculated, and the relationship formula of the rotation matrix and the translation vector of the adjacent two stations is constructed, and the rotation matrix and the translation vector of the next station to the last station are calculated according to the relationship formula, and finally the relationship formula of the points scanned by the next station to the last station is constructed according to the rotation matrix and the translation vector of the next station to the last station, so that the merging of the scanning point clouds of the two stations is realized; S4, continuing to use the scanner on the measuring robot to scan the target object according to the set route, if the field of view of the tracking robot is limited, the relationship formula of the points scanned by the next station to the last station in S3 is used to merge the scanning point clouds of the two stations until the scanning of the target object is completed.

2. The dual-robot wide-range collaborative measurement method according to claim 1, wherein, The coordinate system in which the three-dimensional coordinates of the plurality of landmark points in the S1 are located is a landmark point coordinate system, and the three-dimensional coordinates of the i-th landmark point in the landmark point coordinate system are specifically: wherein represents the coordinates of the i-th landmark point in the coordinate system of the landmarks, and The coordinate value of the i-th mark point in the X, Y and Z axes in the mark point coordinate system.

3. The dual-robot wide-range collaborative measurement method according to claim 2, wherein, The S3 specifically comprises the following steps: S31, using the tracking robot to measure a plurality of marker points around the scanner at the mth measuring station to obtain three-dimensional coordinates of the plurality of marker points in the 0th frame of the tracking robot coordinate system of the mth measuring station, specifically as follows: wherein represents the i-th mark point located on the tracking robot coordinate system and photographed by the m-th measuring station at the 0-th frame; and The coordinate value of the i-th mark point in the X, Y and Z axes in the tracking robot coordinate system of the 0th frame of the m-th station; S32, taking the coordinates of the landmark points measured by the tracking robot in S31 and the corresponding real coordinates as constraints, calculating the rotation matrix from the landmark point coordinate system of the 0th frame at the mth station to the tracking robot coordinate system according to the three-dimensional coordinates of the plurality of landmark points on the scanner in S1 and with the aid of the Gauss-Newton method the optimal value of the mth station 0th frame marker coordinate system to the tracking robot coordinate system translation vector The optimal value of S33, constructing the three-dimensional coordinates of the i-th landmark point in the tracking robot coordinate system obtained in S31 and the rotation matrix finally obtained in S32 Translation vector The relationship formula between and S34, under the premise that the scanner is stationary, the measuring robot moves to the m+1th measuring station, and the rotation matrix from the 0th frame of the m+1th measuring station to the tracker coordinate system is calculated using the steps described in S31 to S32 the optimal value of the (m+1)th station and the translation vector of the coordinate system of the 0th frame marker of the (m+1)th station to the tracker coordinate system The optimal value of S35, the three-dimensional coordinates of the i-th landmark point obtained in S31 in the tracking robot coordinate system and the rotation matrix obtained in S34 are combined to obtain the three-dimensional coordinates of the i-th landmark point in the global coordinate system. Peace translation vector The relationship formula between and S36, according to the relationship formula in S33 and the relationship formula in S35, the relationship formula of the rotation matrix and the translation vector of the adjacent two stations is constructed; S37, calculating the rotation matrix of the point of the m+1th station turning to the mth station according to the relational expression in S36 Peace translation vector S38, using the rotation matrix obtained in S37 Peace translation vector The relationship formula of the k-th point in the target object scanned by the m+1th station to the mth station is constructed, that is, the relationship formula of the points scanned by the next station to the last station, so that the merging of the scanning point clouds of the two stations is realized.

4. The dual-robot wide-range collaborative measurement method according to claim 3, characterized in that, The S32 specifically comprises the following steps: S341. Transfer the coordinates of the i-th marker point from the marker point coordinate system to the tracking robot coordinate system, and subtract the three-dimensional coordinates of the i-th marker point in the tracking robot coordinate system from the coordinates of the i-th marker point in S31 to obtain the transformation error v of the i-th marker point. i ; S342, then the conversion error v of the i-th mark point is used i and an optimization function about conversion errors of the plurality of mark points is constructed by means of Gauss-Newton method; S343. By iteratively optimizing the optimization function, an update amount ΔX is obtained in each iteration. Then, the rotation matrix from the coordinate system of the marker point in frame 0 of the m-th station to the coordinate system of the tracking robot is obtained using the update amount ΔX. Peace translation vector After updating and multiple iterations of optimization, the rotation matrix of the 0th frame of the mth station marker coordinate system to the tracking robot coordinate system is obtained optimum value of the mth station 0th frame marker coordinate system to tracking robot coordinate system translation vector The optimal value of 5. The dual-robot wide-range collaborative measurement method according to claim 4, wherein, the conversion error v of the i-th landmark point in S341 i , which is expressed by the following formula:

6. The dual-robot wide-range collaborative measurement method according to claim 5, wherein, The optimization function in S342 is specified as follows: Wherein, N represents the number of point pairs of the mark points measured by the tracking robot and the corresponding real mark points; T represents the transpose of the matrix, and F(.) represents the to-be-optimized function solved by the Gauss-Newton method.

7. The dual-robot wide-range collaborative measurement method according to claim 6, wherein, The relationship in S33 is specifically: The relationship in the S35 is specifically: The relationship of the rotation matrix and the translation vector of the two adjacent stations in S36 is specifically:

8. The dual-robot wide-range collaborative measurement method according to claim 7, wherein, The rotation matrix in S37 And the translation vector The calculation formula is as follows:

9. The dual-robot wide-range collaborative measurement method according to claim 8, wherein, The relationship of the kth point in the target object scanned on the m+1th station in the S38 to the mth station is specifically as follows: wherein, The k-th point in the target object scanned by the mth station after conversion.

10. A dual robot large-scale cooperative measurement system, characterized in that, The double-robot large-range collaborative measurement system comprises: A measuring robot comprising a first automatic guided vehicle, a mechanical arm mounted on a first lifting mechanism in the first automatic guided vehicle, and a scanner mounted on an execution end of the mechanical arm; A tracking robot comprising a second automatic guided vehicle, a gimbal mounted on a second lifting mechanism in the second automatic guided vehicle, and a binocular three-dimensional tracker mounted on the gimbal.

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