A visual-based steel geometric defect automatic inspection robot and positioning and correction method

Abstract

The application discloses a kind of based on vision's geometric defect automatic inspection robot positioning and deviation rectification method of section steel, and relates to section steel detection technical field.The application includes mobile module, operating module, scanning module;The scanning module includes three-dimensional camera, and the component to be inspected is scanned;The operating module is robot arm, carries scanning module and sends scanning module to appropriate position to scan;Mobile module includes reference platform and mobile platform, for carrying operating module and scanning module to travel to specified position to scan operation, and can monitor the direction of travel of mobile platform in real time, controls and direction correction to mobile platform according to feedback result.The application has large detection work range, high precision, high degree of automation, low cost, and can satisfy the detection requirement of section steel structure processing plant.

Description

Technical Field

[0001] This invention belongs to the technical field of steel section inspection equipment, and more specifically, it relates to a vision-based automatic inspection robot for geometric defects in steel sections and a positioning and correction method. Background Technology

[0002] Steel profiles are widely used in steel structure buildings as purlins, wall beams, roof panels, and wall panels due to their light weight and ease of assembly. Since the mechanical properties of steel profiles are extremely sensitive to initial geometric defects generated during manufacturing, transportation, storage, and use, which ultimately affect their failure modes and stability, the detection of initial defects in steel profiles is crucial, and obtaining accurate defect models of steel profiles has become a topic of great interest.

[0003] Currently, the mainstream defect detection methods rely on manual inspection using tools such as vernier calipers, theodolites, and levels. This method is not only inefficient and costly in terms of labor, but also lacks satisfactory accuracy. In recent years, the use of 3D laser scanning technology for steel defect detection has become very popular. However, to ensure accuracy, manual placement of points on the components is required. While this guarantees accuracy, it still requires significant labor costs and remains inefficient. Furthermore, the high cost of the equipment hinders the widespread adoption of this technology.

[0004] To address the shortcomings of mainstream methods, several technologies have emerged in recent years that utilize vehicle-mounted robots for detecting geometric defects in steel profiles. These technologies typically employ SLAM (Simultaneous Localization and Mapping) or wireless sensor positioning for localization and correction. While these two new technologies can meet the accuracy requirements and automation needs of steel profile geometric defect detection, their equipment costs are relatively high. The latter, in particular, requires a complete overhaul of the steel profile processing plant and the installation of signal base stations, which hinders the market adoption of the technology.

[0005] For large steel component processing plants, detecting the initial geometric defects of the steel materials they process is an important task. However, neither traditional manual inspection nor emerging handheld 3D laser scanning technology nor existing robotic steel component scanning technology can simultaneously meet their needs for a large working range, high precision, and cost reduction, resulting in a relatively low level of automation. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a vision-based automatic inspection robot for geometric defects in steel profiles and a positioning and correction method. The robot has a large detection range, high accuracy, high degree of automation, and low cost, which can meet the inspection requirements of steel structure processing plants.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0008] A vision-based automatic inspection robot for geometric defects in structural steel includes a moving module, an operating module, and a scanning module. The scanning module includes a 3D camera for scanning the component to be inspected. The operating module is a robotic arm that carries the scanning module and moves it to a suitable position for scanning. The moving module carries the operating module and moves it to a designated position. The moving module can perform positioning and orientation correction during its movement.

[0009] Preferably, the mobile module includes a reference platform and a mobile platform. The reference platform includes a reference platform bracket, a first laser rangefinder, and a second laser rangefinder. The first and second laser rangefinders are mounted on the reference platform bracket, and the beams of the two laser rangefinders are parallel to each other. The visible beam emitted by each laser rangefinder is concentric with the beam of the rangefinder laser emitted. During measurement, the reference platform bracket is fixedly connected next to the component to be inspected. The mobile platform includes a photosensitive plate, a first vision camera, a second vision camera, and a vehicle-type robot. The first and second vision cameras are located on opposite sides of the photosensitive plate, which has scale lines. The lasers emitted by the first and second laser rangefinders can illuminate the photosensitive plate. The photosensitive plate, the first vision camera, the second vision camera, and the robot arm are all fixedly connected to the vehicle-type robot and move with the vehicle-type robot.

[0010] A vision-based method for the localization and correction of geometric defects in steel profiles using an automated inspection robot is presented. The localization method for the automated inspection robot is as follows:

[0011] The first and second laser rangefinders are on the same horizontal line. With their lens origin as the origin, coordinate systems P1(x1, y1, z1) are established respectively. T And P2(x2, y2, z2) T Both coordinate systems P1 and P2 are right-handed, with the z1 and z2 axes pointing vertically upwards, and the y1 and y2 axes coinciding with the visible lasers emitted by the first and second laser rangefinders. Since the working environment is flat, the first and second laser rangefinders are installed on the same horizontal line, with z1 = z2 = 0. The distance between the origins of the two coordinate systems is known as l′, allowing us to obtain the transformation relationship between P1 and P2:

[0012]

[0013] The photosensitive plate has standard markings to estimate the position of the vehicle-type robot; a coordinate system P for the moving platform is established with the edge markings on the photosensitive plate closest to the first-vision camera and the point at the same height as the light spot as the origin. m (x m y m , z m ) T The coordinate system is y = y + ...m The axis, with the vertical upward direction as z. m The axes are also represented using a right-handed coordinate system for coordinates and attitude; when the working conditions are flat, z1 = z2 = z m =0; When the robot is on the correct path, the y1 axis, y2 axis, and y m The axes always remain parallel;

[0014] When it is necessary to determine the precise positioning of the reference platform at a certain moment, the visible lasers emitted by the first laser rangefinder and the second laser rangefinder leave two visible light spots on the photosensitive plate. The visible light spot left by the laser emitted by the first laser rangefinder is the first light spot, and the visible light spot left by the laser emitted by the second laser rangefinder is the second light spot. This can be obtained by visually observing the first light spot and the second light spot at the scale position on the photosensitive plate through the first vision camera and the second vision camera. Because the working environment is flat, the first light spot and the second light spot have the same vertical height on the photosensitive plate, and their coordinates are (u1, v1) and (u2, v1) respectively. Furthermore, it is known that the coordinates of the first light spot in the reference coordinate system P1 are (0, l1, z1), and the coordinates of the second light spot in the reference coordinate system P2 are (0, l2, z2). According to formula (1), the transformed coordinates of the second light spot in the reference coordinate system can be derived as (l', l2, z1).

[0015] We can obtain x at this time m The axis deflection angle relative to the x1 axis

[0016]

[0017] When the relative deflection angle is known, the coordinate system P of the moving platform can be determined accordingly. m Find the coordinates of the origin in the P1 coordinate system (x0, y0, 0), and derive P. m The conversion relationship with P1;

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] Where R is the rotation transformation matrix and T is the translation transformation matrix;

[0024] After locating the trolley, it can be determined whether the trolley's direction of travel is incorrect; assuming the working environment of the mobile platform is flat, let the target coordinates on the photosensitive plates of the first and second light spots be (u... 10 v1) and (u 20 v1), when time s, the first visual camera and the second visual camera determine u through computer vision. 10 ≠u1 or u 20 When u2 is not equal to u2, route correction is required, i.e., deviation correction.

[0025] Let the moving platform be in coordinate system P1, with velocities dx1, dy1 along the x-axis, y-axis, and counterclockwise around the z-axis, respectively.

[0026] The correction method for automated inspection robots includes the following steps:

[0027] S1. Positioning: First, pause the mobile platform and perform positioning according to the above-described automatic inspection robot positioning method to determine the reference platform's follow-up coordinate system P. m Deflection angle relative to coordinate system P1 and the coordinate system P at this time m The coordinates of the origin in coordinate system P1 (x m1s y m1s , z m1s );

[0028] S2. Determine the target point: While locating the mobile platform, the system retrieves and returns the sequence number i of the previous normal shooting site, thereby determining the site N. i+1 The target site is identified and its coordinates in coordinate system P1 are obtained.

[0029] S3. Determine the error: Based on the target position N i+1 Coordinates can be used to determine the target x of the correction task. 10 y 10 , Given the correct coordinates and orientation of the mobile platform at the target point, respectively, the deflection angles can be used to obtain the error values ​​Δx and Δy.

[0030] Δx=x m1s -x 10 (8)

[0031] Δy=y m1s -y 10 (9)

[0032]

[0033] because but

[0034]

[0035] S4. Determine the speed of the mobile platform: Set the speed control law k for each of the three degrees of freedom. x k y ,

[0036]

[0037] S5. Correction: Adjust dx1, dy1, Convert to three-degree-of-freedom velocity dx in the mobile platform's follower coordinate system m dy m , And control the mobile platform to move to the target location;

[0038]

[0039]

[0040]

[0041] S6. Confirm and take photos: Move to the designated station N i+1 Afterwards, the positioning should be checked again. If the error values ​​are all 0, the shooting can continue and the scanning work can be carried out normally.

[0042] The beneficial effects of adopting the above technical solution are as follows:

[0043] 1. The scanning robot and depth camera combination in this invention scans the geometric defect information of steel components. It has the characteristics of low cost, high precision, high degree of automation and no need for marking points. It can meet the large-scale application needs of large steel component manufacturers and improve their production efficiency.

[0044] 2. The positioning and correction method proposed in this invention can accurately locate the robot vehicle in space and further provide good coarse registration conditions for subsequent point cloud stitching. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the robot's overall structure;

[0046] Figure 2 This is a schematic diagram of the route planning and station locations;

[0047] Figure 3 This is a schematic diagram of a work scenario;

[0048] Figure 4 This is a schematic diagram of point cloud stitching;

[0049] Figure 5 This is a flowchart of the workflow;

[0050] Figure 6 This is a schematic diagram of the coordinates of the moving module;

[0051] Figure 7 This is a schematic diagram of the positioning and correction principle of the mobile module;

[0052] Figure 8 This is a schematic diagram of the working operation of the moving module of the component under test;

[0053] In the diagram: 101, reference platform support; 102, first laser rangefinder; 103, second laser rangefinder; 111, photosensitive plate; 112, first vision camera; 113, second vision camera; 114, vehicle-type robot; 115, robot arm; 116, 3D camera. Detailed Implementation

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0055] like Figure 1 As shown, the automated inspection robot includes a movement module, an operation module, and a scanning module. The scanning module includes a 3D camera 116, which scans the component to be inspected. The 3D camera 116 saves the component point cloud model from various viewpoints and uses a point cloud stitching algorithm. The point cloud stitching algorithm performs coarse registration of the point cloud model from multiple viewpoints using the saved distance values ​​from the ranging laser and the inverse coordinate solution of the robot arm. Then, it introduces the ICP algorithm to perform fine registration of the point cloud to generate a component point cloud model that meets the accuracy requirements.

[0056] The mobile module includes a reference platform and a mobile platform. The reference platform includes a reference platform bracket 101, a first laser rangefinder 102, and a second laser rangefinder 103, which are mounted on the reference platform bracket 101. The beams of the two laser rangefinders are parallel to each other, and the visible beam emitted by each laser rangefinder is concentric with the beam of the ranging laser emitted. During measurement, the reference platform bracket 101 is fixedly connected to the component to be inspected. The mobile platform includes a photosensitive plate 111, a first vision camera 112, a second vision camera 113, and a vehicle-type robot 114. The vehicle-type robot 114 is an omnidirectional vehicle-type robot. The first vision camera 112 and the second vision camera 113 are located on opposite sides of the photosensitive plate 111. The photosensitive plate 111 has scale lines, and the lasers emitted by the first laser rangefinder 102 and the second laser rangefinder 103 illuminate the photosensitive plate 111, leaving light spots. The visible light spot left by the laser emitted by the first laser rangefinder 102 is the first light spot, and the visible light spot left by the laser emitted by the second laser rangefinder 103 is the second light spot. The photosensitive plate 111, the first vision camera 112, the second vision camera 113, and the robotic arm 115 are all fixedly connected to the vehicle-type robot 114 and move with it. The movement module can perform positioning and orientation correction during movement.

[0057] The operation module consists of a robotic arm 115. The robotic arm 115 carries a scanning module and delivers it to the appropriate position for scanning. The robotic arm 115 is mounted on a vehicle-mounted robot 114, which then delivers the operation module to the designated position. Once the mobile platform stops at the expected scanning point, the robotic arm 115 can, based on the component shape, scanning requirements, and other actual conditions, deliver the 3D camera 116 to a suitable position for scanning, and then return and save its coordinate information.

[0058] The working principle of the entire automated inspection robot system is as follows:

[0059] Taking the scanning of a point cloud model of a steel structure under test by an inspection robot as an example. Figure 2 As shown, to ensure that the designed robot system can effectively perform scanning along the length of the component, a precise straight-line travel path needs to be planned before scanning begins, based on the length L of the component to be measured and the scanning coverage of the scanning module at a single station. n scanning stations are then strategically placed along this path to achieve precise, station-by-station scanning by the designed robot system.

[0060] After scanning begins, the mobile module moves along a predetermined path and pauses briefly at each preset scanning station. For example... Figure 3 As shown, when the mobile module arrives at the designated station N iWhen the robot arm stops moving, it adjusts its posture to precisely position the scanning module at the appropriate location for scanning the component. The system automatically collects point cloud data of the component in the vicinity of the site, and simultaneously returns and records the spatial coordinate information of the scanning module.

[0061] like Figure 4 As shown, the mobile platform is at site N i With site N i+1 The scanning ranges of the two stations overlap in some areas; save N according to the workflow described above. i With N i+1 After capturing the point cloud model, the algorithm can, based on the relationship between the moving platform's position, the robot arm's motion, and the overlapping viewpoints, convert N... i With N i+1 The point cloud model was photographed, stitched together, and registered. Further stitching and registration were performed from N1 to N. n The point cloud model can be used to obtain a complete model that satisfies the requirements for detecting geometric defects in structural components.

[0062] During the movement of the automated inspection robot 114, its path may deviate due to the incomplete constraint of its travel system. To ensure scanning accuracy, global position feedback localization is needed to correct its travel path. Subsequent point cloud stitching and registration also require accurate spatial coordinates of the vehicle model robot 114. Based on this requirement, a feedback control method was designed to automatically return coordinates and correct the travel path of the vehicle model robot 114.

[0063] The positioning method for automated inspection robots is as follows:

[0064] like Figure 6 , Figure 7 As shown, the first laser rangefinder 102 and the second laser rangefinder 103 are placed on the same horizontal line, with their lens origin as the origin. A coordinate system P1(x1,y1,z1) is established respectively. T And P2(x2,y2,z2) T Both coordinate systems P1 and P2 are right-handed, with the z1 and z2 axes pointing vertically upwards, and the y1 and y2 axes coinciding with the visible laser emitted by the first laser rangefinder 102 and the second laser rangefinder 103. Since the designed system operates in a flat environment, the first laser rangefinder 102 and the second laser rangefinder 103 are installed on the same horizontal line, with z1 = z2 = 0. The distance between the origins of the two coordinate systems is known as l′, and the transformation relationship between P1 and P2 can be obtained as follows:

[0065]

[0066] like Figure 6As shown, the photosensitive plate 111 has standard scales to estimate the position of the vehicle robot 114. A coordinate system P for the moving platform is established with the edge scale line on the photosensitive plate 111 closest to the first visual camera 112 and the point at the same height as the light spot as the origin. m (x m y m , z m ) T The coordinate system is y = y + ... m The axis, with the vertical upward direction as z. m The axes are also represented using a right-handed coordinate system for coordinates and attitude. When the working conditions are flat, z1 = z2 = z m =0. When the vehicle robot 114 is on the correct travel path, the y1 axis, y2 axis, and y m The axes always remain parallel.

[0067] When it is necessary to determine the precise positioning of the reference platform at a certain moment, it can be obtained by visually observing the first and second light spots at the scale positions of the photosensitive plate 111 through the first visual camera 112 and the second visual camera 113. Because the working environment is flat, the first and second light spots have the same vertical height on the photosensitive plate 111, which are (u1, v1) and (u2, v1) respectively. Furthermore, it is known that the coordinates of the first light spot in the reference coordinate system P1 are (0, l1, z1), and the coordinates of the second light spot in the reference coordinate system P2 are (0, l2, z2). According to formula (1), the transformed coordinates of the second light spot in the reference coordinate system can be derived as (l', l2, z1).

[0068] We can obtain x at this time m The axis deflection angle relative to the x1 axis

[0069]

[0070] When the relative deflection angle is known, the coordinate system P of the moving platform can be determined accordingly. m Find the coordinates of the origin in the P1 coordinate system (x0, y0, 0), and derive P. m The conversion relationship with P1.

[0071]

[0072]

[0073]

[0074]

[0075]

[0076] After locating the car, it is possible to determine whether the car's direction of travel is incorrect.

[0077] Assuming the mobile platform operates in a flat environment, let the target coordinates of the first and second light spots on the photosensitive plate 111 be (u... 10 v1) and (u 20 (u1). At time s, the first visual camera 112 and the second visual camera 113 determine u using computer vision. 10 ≠u1 or u 20 When the value is not equal to u2, route correction is required, i.e., deviation correction.

[0078] Let the moving platform be in coordinate system P1, with velocities dx1, dy1 along the x-axis, y-axis, and counterclockwise around the z-axis, respectively.

[0079] The corrective action involves the following steps:

[0080] S1. Positioning: First, pause the mobile platform. Using the method described in the previous section, determine the reference platform's tracking coordinate system P. m Deflection angle relative to coordinate system P1 and the coordinate system P at this time m The coordinates of the origin in coordinate system P1 (x m1s y m1s , z m1s ).

[0081] S2. Determine the target point: While locating the mobile platform, the system retrieves and returns the sequence number i of the previous normal shooting site, thereby determining the site N. i+1 The target site is determined and its coordinates in coordinate system P1 are obtained.

[0082] S3. Determine the error: Based on the target position N i+1 Coordinates can be used to determine the target x of the correction task. 10 y 10 , Given the correct coordinates and orientation of the mobile platform at the target point, respectively, the deflection angles can be used to obtain the error values ​​Δx and Δy.

[0083] Δx=x m1s -x 10 (8)

[0084] Δy=y m1s -y 10 (9)

[0085]

[0086] because but

[0087]

[0088] S4. Determine the speed of the mobile platform: Set the speed control law k for each of the three degrees of freedom. x k y ,

[0089]

[0090] S5. Correction: Adjust dx1, dy1, Convert to three-degree-of-freedom velocity dx in the mobile platform's follower coordinate system m dy m , And control the mobile platform to move to the target location.

[0091]

[0092]

[0093]

[0094] S6. Confirm and take photos: Move to the designated station N i+1 Afterwards, the positioning should be checked again. If the error values ​​are all 0, the shooting can continue and the scanning work can be carried out normally.

[0095] When multiple steel sections require geometric defect detection, multiple reference platforms can be set up for point cloud coordinate positioning and automated detection can be achieved. For example... Figure 8 As shown, taking the case where there are two components to be tested as an example, the lengths of component one and component two to be tested are preset first, and component one is scanned. The outward control method is the same as described above, with reference platform one controlling the moving platform to travel along the outward path. After reaching the preset length of component one, it automatically deflects β towards component two and continues to travel. After traveling an appropriate distance, it deflects -β back to the original deflection direction, that is, it reaches the return point through ② and deflects the moving platform back to the original direction of travel. At this time, the first visual camera 112 and the second visual camera 113 can detect the visible light spot left by reference platform two on the photosensitive plate 111, and can detect the position coordinates of the reference platform relative to reference platform two. Using the above algorithm, the moving platform is controlled to retreat to the starting position of component two and start scanning component two.

[0096] The automatic inspection robot for steel structures designed in this invention, through its mobile module, meets the requirements of low-cost, wide-range, and high-precision positioning and geometric defect detection in large steel structure processing plants. It is conducive to the healthy development of my country's steel structure industry and has also contributed to the safety of my country's civil engineering to a certain extent.

[0097] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A vision-based automated inspection robot for geometric defects in structural steel, characterized in that, It includes a movement module, an operation module, and a scanning module; the scanning module includes a 3D camera to scan the component to be inspected; the operation module is a robotic arm that carries the scanning module and delivers it to a suitable position for scanning; the movement module carries the operation module and delivers it to a designated position; the movement module can perform positioning and orientation correction during movement. The mobile module includes a reference platform and a mobile platform. The reference platform includes a reference platform bracket, a first laser rangefinder, and a second laser rangefinder. The first and second laser rangefinders are mounted on the reference platform bracket, and the beams of the two laser rangefinders are parallel to each other. The visible beam emitted by each laser rangefinder is concentric with the beam of the rangefinder laser emitted. During measurement, the reference platform bracket is fixedly connected to the component to be inspected. The mobile platform includes a photosensitive plate, a first vision camera, a second vision camera, and a vehicle-type robot. The first and second vision cameras are located on opposite sides of the photosensitive plate, which has scale lines. The lasers emitted by the first and second laser rangefinders can illuminate the photosensitive plate. The photosensitive plate, the first vision camera, the second vision camera, and the robot arm are all fixedly connected to the vehicle-type robot and move with the vehicle-type robot.

2. A method for positioning and correcting deviations in a vision-based automatic inspection robot for geometric defects in steel profiles as described in claim 1, characterized in that, The positioning method for automated inspection robots is as follows: The first and second laser rangefinders are on the same horizontal line, and coordinate systems are established with their lens origin as the origin. and ; and The coordinate systems are all right-handed. shaft and The axis is vertically upward. shaft and The axis coincides with the visible laser emitted by the first and second laser rangefinders; since the working environment is flat, the first and second laser rangefinders are installed on the same horizontal line. The distance between the origins of the two coordinate systems is known. ,get and Conversion relationship: （1）； The photosensitive plate has standard markings to estimate the position of the vehicle-type robot; a coordinate system for the moving platform is established with the edge markings on the photosensitive plate closest to the first-view camera and the point at the same height as the light spot as the origin. The coordinate system is along the direction of travel of the mobile platform. The axis, vertically upward direction is The axis, also using a right-handed coordinate system, represents coordinates and attitude; when the working conditions are flat ground, When the vehicle robot is on the correct travel path, axis, Shaft and The axes always remain parallel; When it is necessary to determine a certain moment When the reference platform is precisely positioned, the visible lasers emitted by the first and second laser rangefinders leave two visible light spots on the photosensitive plate. The visible light spot left by the laser emitted by the first laser rangefinder is the first light spot, and the visible light spot left by the laser emitted by the second laser rangefinder is the second light spot. This can be obtained through visual observation of the first and second light spots at their respective scale positions on the photosensitive plate using the first and second vision cameras. Because the working environment is flat, the first and second light spots have the same vertical height on the photosensitive plate, with coordinates as follows: and ; It is known that the first light spot is in the reference coordinate system at this time. The coordinates in are The second light spot in the reference coordinate system The coordinates in are Based on formula (1), the transformed coordinates of the second light spot in the reference coordinate system are derived as follows: ; At this time Axial relative Axis deflection angle , （2）； （3）； （4）； （5）； （6）； （7）； When the relative deflection angle is known, the coordinate system of the moving platform is determined accordingly. The origin is Coordinate values ​​in a coordinate system And deduce and The transformation relationship; Where R is the rotation transformation matrix and T is the translation transformation matrix; After locating the trolley, a determination is made as to whether the trolley's direction of travel is incorrect; assuming the working environment of the mobile platform is flat, let the target coordinates on the photosensitive plates of the first and second light spots be respectively... and ,when The first and second vision cameras use computer vision to make judgments at all times. or At this time, route correction is required, that is, deviation correction. Assuming the mobile platform is In the coordinate system, axis, Axis and winding The counterclockwise velocities of the axis are respectively , , ; The correction method for automated inspection robots includes the following steps: S1. Positioning: First, pause the mobile platform and perform positioning according to the above-described automatic inspection robot positioning method to determine the reference platform's follow-up coordinate system. Relative coordinate system deflection angle and the coordinate system at this time Origin in coordinate system coordinates ; S2. Determine the target point: While locating the mobile platform, the system will retrieve and return the sequence number of the previous normal shooting site. Thus determining the site For the target site and obtain its coordinate system The coordinates; S3. Determine the error: Based on the target position Coordinates to determine the objective of the correction task. , , ; these represent the deflection angles of the mobile platform at the correct coordinates and attitude of the target point, respectively, yielding the error value. , , , （8）； （9）； （10）； because ,but: （11）； S4. Determine the speed of the mobile platform: Set the speed control rates for the three degrees of freedom respectively. , , , （12）； S5, Correction: [This will...] , , Convert to three-degree-of-freedom velocity in the mobile platform's follower coordinate system , , And control the mobile platform to move to the target location; （13）； （14）； （15）； S6. Confirm and take photos: Move to the designated station. Afterwards, the positioning was performed again. When the error value was 0, the shooting continued and the scanning work was carried out normally.

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