Initial calibration and optimization method for rotation axis and hand-eye relationship of line laser scanning system

Abstract

The invention discloses an initial calibration and optimization method for a rotation axis and hand-eye relationship of a line laser scanning system. The method comprises the following steps: establishing three coordinate systems including a camera coordinate system, a moving coordinate system and a base coordinate system and a conversion relationship in the scanning system; introducing an articulated arm coordinate system, and using an articulated arm measuring machine to complete initial calibration of rotating shaft parameters and translation vectors in a hand-eye matrix; initial calibration of the whole hand-eye matrix is completed by using the initial calibration parameters of the rotating shaft and an ICP algorithm; and comprehensively optimizing the rotating shaft parameters and the hand-eye matrix based on the standard cylinder and the special target. The method is high in calibration speed, high in efficiency, simple to operate and good in optimization effect, and the point cloud rotation splicing precision is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of visual inspection system calibration, and particularly relates to an initial calibration and optimization method for the rotation axis and hand-eye relationship of a line laser scanning system. Background Technique

[0002] In recent years, with the development of science and technology, China has achieved many innovative results in the fields of aerospace, transportation, robotics, etc. In order to improve the working performance and stability of machines, the industry has higher and higher requirements for the quality, precision, and even service life of important parts, especially parts such as aeroengine blades, gears, and bearings. Therefore, the technologies for dimensional inspection, defect identification, and three-dimensional reconstruction of large or rotary parts have received extensive attention and are hot research topics in the visual inspection industry.

[0003] Hand-eye calibration is mainly to obtain the coordinate transformation relationship between the camera and the robotic arm. Due to the installation error of the sensor, it is necessary to calibrate the sensor to find the coordinate transformation relationship between the camera and the robotic arm. Hand-eye calibration is divided into two categories: eye-to-hand and eye-in-hand. Eye-to-hand: The camera is installed outside the robotic arm, and the calibration board is installed at the end of the robotic arm. In this case, we need to find the transformation relationship between the camera coordinate system and the robotic arm base coordinate system; Eye-in-hand. The camera is installed on the robotic arm, and the calibration board is fixed outside the robotic hand. In this case, we need to find the coordinate transformation relationship between the camera coordinate system and the end effector of the robotic arm.

[0004] The line laser scanning system consists of a three-axis displacement stage, a rotary stage, and a laser sensor, and can achieve multi-dimensional scanning of line structured light, enabling the sensor's field of view to fully cover any part of the workpiece. The point clouds collected at various angles are rotated and stitched to complete the three-dimensional reconstruction of the blade morphology. The effect of point cloud rotation and stitching depends on the calibration accuracy of the rotation axis and the hand-eye matrix. To ensure the calibration accuracy, in the prior art, the calibration scheme disclosed in the literature "New Digital Dental Model Laser Scanning System" is as follows: The high-low ball method is used for rotation axis calibration. The laser scans the ball and fits the scanned data to obtain the position of the ball center. The rotary table is rotated and this operation is repeated to obtain the positions of multiple ball centers at the same height. A spatial circle is fitted to obtain the position of the center of the circle. Then, the position of the standard ball is raised and lowered and the steps are repeated to obtain a sequence of center positions of the circle. Finally, the best straight line of all the centers of the circle is fitted. The calibration scheme disclosed in the prior art literature "Precise Calibration Method for the Rotating Axis of Non-contact Optical Measurement of Aeroengine Blades" is as follows: The method of translational scanning is used to obtain the point cloud of a partial cross-section contour of the standard ball. The rotary table rotates to collect data multiple times. Then, the singular value decomposition method is used to fit the ball center, and the least squares method is used to solve the plane equation of the ball center trajectory and the normal vector of the rotation axis. Finally, the intersection point of the rotation axis and the trajectory plane is obtained, and this point is the axis center of the rotation axis. In the prior art, the calibration scheme disclosed in the literature "Research on Three-dimensional Surface Scanning and Detection Method of Rotary Workpieces Based on Structured Light" is as follows: A surface scanning and detection model of the rotary workpiece is established based on the cylindrical coordinate system, and the hand-eye relationship is calibrated by combining the homography transformation existing in the line structured light measurement system; Wang Zhenyou proposed a combined calibration method for the rotary table and the hand-eye relationship. Using a double-ball bar as the calibration object, after calibrating the rotation axis parameters and the hand-eye matrix, they are brought into the objective function for non-linear optimization to obtain the optimal solution. In the above-mentioned existing calibration methods for the rotation axis parameters and the hand-eye relationship, there are problems such as cumbersome processes and low efficiency. Therefore, a new method must be proposed to solve the deficiencies of the prior art. Summary of the Invention

[0005] 1. Technical problems to be solved:

[0006] In view of the above technical problems, the present invention provides an initial calibration and optimization method for the rotation axis and hand-eye relationship of a line laser scanning system, which is used to achieve hand-eye calibration from the camera coordinate system to the translation coordinate system, and this calibration method has high accuracy and is easy to operate.

[0007] 2. Technical solution:

[0008] The initial calibration and optimization method for the rotation axis and hand-eye relationship of a line laser scanning system. The line laser scanning system collects the contour point cloud of the object to be measured through its laser sensor. An articulated arm measuring machine is provided to implement the initial calibration and optimization method for the hand-eye relationship of the line laser scanning system; the initial calibration and optimization method for the hand-eye relationship specifically includes the following steps:

[0009] Step 1: Establish a base coordinate system, a translation coordinate system where the translation stage is located, and a camera coordinate system where the line laser sensor is located in the online laser scanning system. The transformation relationship from the camera coordinate system to the translation coordinate system is the hand-eye relationship. Obtain the transformation matrix from the camera coordinate system to the translation coordinate system and the transformation matrix from the translation coordinate system to the base coordinate system. The line laser scanning system is equipped with a translation stage composed of translation axes in the X, Y, and Z axis directions, and the line laser sensor can move in the coordinate axis directions corresponding to the directions. The line laser scanning system is equipped with a disk-shaped turntable, and the turntable drives the object to be measured on its surface to rotate under the drive of its rotating shaft, so as to realize the line laser sensor to collect contour point clouds of the object on the turntable. The end of the articulated arm measuring machine is provided with a connection structure, and the connection structure is used to fix the probe or the laser scanning head. The articulated arm measuring machine controls the movement of the end through its robotic arm structure.

[0010] Step 2: Move the three translation axes of the line laser scanning system to the zero position, and connect the articulated arm measuring machine to a spherical probe with a preset diameter. Use the probe to collect the coordinates of the origin of the base coordinate system, that is, the zero position, and multiple points on each coordinate axis in the articulated arm coordinate system at this time. Use the RANSAC algorithm to fit the points on the same coordinate axis into a straight line, and obtain the positions p of each coordinate axis and the origin in the articulated arm coordinate system under the base coordinate system. B , and further obtain the transformation matrix from the base coordinate system to the articulated arm coordinate system.

[0011] Step 3: Control the turntable to rotate one week, and the probe at the end of the articulated arm measuring machine moves following the console under the control of its robotic arm structure. The probe measures a randomly fixed point on the surface of the turntable. When the turntable rotates 10° each time, obtain the position of the probe, and then obtain the rotated coordinates of this point in the articulated arm coordinate system. Use the RANSAC algorithm to fit the multiple coordinates obtained during the rotation process into a circle, and obtain the center position of the turntable surface and the normal direction of the circle passing through the center position. Through the inverse matrix of the transformation matrix from the base coordinate system to the articulated arm coordinate system obtained in Step 2, transform the center coordinates and the normal direction to the base coordinate system, and obtain the coordinates of a point on the straight line where the rotation axis of the turntable is located and the direction of the rotation axis in the base coordinate system, which are the coordinates of a point on the straight line where the rotation axis of the turntable is located and the direction of the rotation axis under the base coordinate system.

[0012] Step 4: Replace the probe at the end of the articulated arm measuring machine with a spherical ruby probe. Use the ruby probe to collect points on the upper, lower, side, and front surfaces of the line laser sensor, and use RANSAC to fit a plane to obtain the position p of the origin of the camera coordinate system in the articulated arm coordinate system. c , use the transformation matrix from the base coordinate system to the articulated arm coordinate system obtained in Step 3 to transform the coordinate p c and the coordinate p BTransform from the articulated arm coordinate system to the base coordinate system, and then obtain the translation vector of the transformation matrix from the camera coordinate system to the translation coordinate system, that is, the initial hand-eye matrix.

[0013] Step 5: Place a target with a preset shape on the surface of the turntable, and use the line laser sensor and the articulated arm measuring machine to scan the target respectively to obtain two point clouds of the target; preliminarily transform the point cloud scanned by the line laser sensor to the articulated arm coordinate system, and then use the ICP algorithm to register the two point clouds in the articulated arm coordinate system to obtain the registration matrix for registering the point cloud scanned by the line laser sensor to the point cloud scanned by the articulated arm. This registration matrix is the initial hand-eye matrix.

[0014] Step 6: Select a cylinder with a preset size as the target to replace the target in Step 5. The line laser sensor scans the cylinder once every 90° rotation of the turntable to obtain a point cloud of one contour; perform RANSAC cylinder fitting on the point cloud scanned at 0°, and optimize the parameters of the rotation axis and the cylinder axis.

[0015] Step 7: Transform the optimized rotation axis to the articulated arm coordinate system, use the initial hand-eye matrix as the initial value of the optimization variable, construct an objective function, use the point cloud scanned by the line laser sensor in Step 5 as the source point cloud, and the point cloud scanned by the articulated arm as the target point cloud. Calculate the distance between the source point cloud and the target point cloud as the error metric, and minimize the sum of the squared residuals of the error metric to optimize the hand-eye matrix.

[0016] Further, in Step 2, a leapfrog cone is used as a reference object for data acquisition, which specifically includes:

[0017] S21: Move the three translation axes of the system to the zero position of the grating scale of the system. The probe of the articulated arm measuring machine is a probe with a diameter of 15 mm, and the probe measures the position of the zero position at this time; fix the leapfrog cone to a point on the translation axis in the Z-axis direction, and collect the position of this point; control the movement of the translation axis in the X-axis direction, and the probe collects a point cloud data of the leapfrog cone every preset distance. Stop collecting when moving to the limit position, and then the translation axis returns to the zero position; repeat the above process to complete the acquisition of point cloud data in the Y and Z axis directions.

[0018] S22: Use the RANSAC algorithm to fit a straight line to the obtained point cloud data; during the straight line fitting process, the parametric equation of the following formula is used to describe the space straight line:

[0019]

[0020] In the above formula, (x0 y0 z0) represents a known point on the straight line; (i j k) is the direction vector of the straight line; t is a parameter;

[0021] Let Then formula (1) is deformed into the following formula (2):

[0022] p = p0 + t·n, t ∈ R (2)

[0023] Randomly select two points p 1， collected on the same coordinate axis, and calculate the distance d of each other point p on this coordinate axis as follows i from the straight line where the axis is located i , and the expression is

[0024]

[0025] Preset the distance threshold from a point to the straight line corresponding to the coordinate axis. If the distance from the point to the corresponding straight line is less than the distance threshold, then the point is considered an inlier of the straight line, and it is retained and counted; otherwise, it is identified as an outlier of the straight line, and the outlier needs to be removed; repeat the above steps n times. After traversing all points, find all inliers that meet the inlier conditions; substitute the obtained inliers into formula (2) to obtain the optimized straight line equation, which is the fitted straight line equation;

[0026] S23: Obtain the coordinate axis direction n x , n y , n z of the base coordinate system and the position p B of the origin in the articulated arm coordinate system to obtain the transformation matrix for transforming the base coordinate system to the articulated arm coordinate system

[0027] Furthermore, step three specifically includes:

[0028] S31: Remove the leapfrog cone of the Z-axis and fix a leapfrog cone at a position near the edge of the turntable surface; the turntable rotates 10° each time, and the probe collects point cloud data once. At least 36 sets of point cloud data are collected;

[0029] S32: Use the RANSAC algorithm to fit a circle; during the spatial circle fitting process, the standard equation describing the spatial circle is as follows

[0030] (x - a) 2 +(y - b) 2 +(z - c) 2 = r 2 (4)

[0031] In the above formula, (a, b, c) represents the center of the spatial circle, and r is the radius of the spatial circle;

[0032] Randomly select the point cloud data of three points from the point cloud data collected in step S31, and calculate the distance d of each other point to the circle using the following formula i :

[0033]

[0034] The distance threshold for the preset distance from a point to a circle; if the distance from a point to the circle is less than this distance threshold, the point is considered an interior point inside the circle, and it is retained and counted; otherwise, it is identified as an exterior point, and the exterior points are excluded. Repeat this process n times. Substitute the obtained interior points into formula (4) to obtain the optimized spatial circle equation, which is the fitted circle equation.

[0035] S33: Obtain the center position of the circle based on the fitted circle equation The normal direction passing through the center of the circle Obtain the transformation matrix obtained in step S23 as follows The inverse matrix of:

[0036]

[0037] The center position The normal direction Transform it to the base coordinate system as follows:

[0038]

[0039] Furthermore, the translation vector of the hand-eye matrix obtained in step four

[0040] Furthermore, step five specifically includes:

[0041] S51: Fix a target with a preset shape on the turntable and face it towards the line laser sensor. The line laser sensor scans one side of the target along the positive Z-axis direction to obtain the point cloud P in the camera coordinate system Cramera ;

[0042] S52: Replace the probe of the articulated arm measuring machine with a laser probe. The turntable rotates 180°. The laser probe scans the target to obtain the point cloud P of the target part in the articulated arm coordinate system ArmCMM ;

[0043] S53: Set the initial value of the rotation matrix of the transformation matrix from the camera coordinate system to the translation coordinate system Based on the initial translation vector obtained in step four The initial hand-eye matrix T is as follows:

[0044]

[0045] According to the coordinate transformation relationship from the base coordinate system to the articulated arm coordinate system in step two, transform P Cramera to the articulated arm coordinate system, and then rotate P ArmCMM by 180° around the rotation axis obtained from the initial calibration to obtain the rotated point cloud P ArmCMM ;

[0046] S54: Set P Cramera as the source point cloud, and set the rotated point cloud P ArmCMM as the target point cloud; all points q i in the target point cloud constitute the set Q, then q i ∈Q; use KD-Tree in the source point cloud set to find the corresponding point set p i ∈P such that ||p i -q i || is minimized; obtain the matching point set P composed of all matching points; obtain the centroid of the matching point set in the articulated arm coordinate system as follows:

[0047]

[0048] In the above formula, represents the centroid of the source point cloud; represents the centroid of the target point cloud; N represents the number of the matching point set; then de-center

[0049]

[0050] In the above formula, p’ i , q’ i are the points after de-centering the source point cloud and the target point cloud respectively;

[0051] Construct the covariance matrix H for the de-centered point sets of the source point cloud and the target point cloud as follows:

[0052]

[0053] Perform SVD decomposition on the covariance matrix H, and the decomposition result is as follows:

[0054] H = UΣV T (12)

[0055] In the above formula, H represents the covariance matrix; U represents the matrix of the left singular vectors of matrix H; V T represents the matrix of the right singular vectors of H;

[0056] At this time, the rotation matrix R = VU T , translation vector

[0057] Apply the calculated rotation matrix and translation vector to the source point cloud P Cramera , and the source point cloud at the new position is as follows:

[0058] P new = RP + t, (13)

[0059] S55: Determine the iteration stop by calculating the magnitude of the transformed mean square error. Among them, calculate the mean square error E between the two point clouds after transformation as follows:

[0060]

[0061] When the change in the mean square error is less than the preset error threshold or the preset maximum number of iterations is reached, terminate the iteration. At this time, the obtained registration matrix is the true initial hand-eye matrix.

[0062] Furthermore, step six specifically includes the following steps:

[0063] S61: Select a standard cylinder of a preset size and fix it on the turntable. The line laser sensor collects the cylinder point cloud once every 90° rotation of the turntable, and convert the collected cylinder point cloud to the base coordinate system;

[0064] S62: Perform cylinder fitting on the point cloud scanned at 0°, and obtain the axis position and direction parameters of the fitted cylinder;

[0065] S63: Create an optimization object, and give the initial value x0 = [a b c 0 0 d e f 0 0], where the first five are the initial values of the turntable axis, and the last five are the initial values of the cylinder axis;

[0066] S64: Use the Plücker matrix to represent the axis of the standard cylinder; construct it through two points on the straight line where the standard cylinder axis is located. Assume that the straight line passes through points P1 and P2, then the Plücker coordinates of the straight line can be expressed as:

[0067] L = (d, m) (15)

[0068] Among them, d = P2 - P1 is the direction vector of the straight line, and m = P1 × P2 is the moment vector of the straight line;

[0069] Use the Plücker matrix calculation formula as follows to obtain the expression of this straight line:

[0070]

[0071] In the above formula, m = (m3, m2, m1) and d = (d1, d2, d3) are the moment vector and direction vector of the straight line respectively;

[0072] S65: Traverse the points in the point cloud obtained in step S61 in a random order to calculate the distance d from the points to the axis of the standard cylinder i ;

[0073] Calculate the sum of the squares of the errors from the points to the cylinder surface as follows:

[0074] err i =(d i -r)2 (17)

[0075] Among them, d i is the distance from the i-th point to the axis of the cylinder; r is the standard radius of the cylinder;

[0076] Accumulate the sum of squared errors of this point to obtain the total error err 总 as follows:

[0077]

[0078] Iteratively calculate the total error. Each time an iteration is performed, the parameters of the rotation axis and the axis of the cylinder will be automatically optimized until the obtained total error is lower than the preset threshold, at which point the iteration stops. At this time, the parameters of the rotation axis and the axis of the cylinder are the finally optimized parameters of the rotation axis and the axis of the cylinder.

[0079] 3. Beneficial effects:

[0080] (1) A method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system. This method uses an articulated arm measuring machine to initially calibrate the rotation axis parameters and the hand-eye matrix. By driving the end of the articulated arm measuring machine with a leapfrog cone and its matching probe, the trajectory dots on a plane are collected and a circle is fitted, and the center coordinates and the normal of the circle are directly obtained to achieve rapid initial calibration of the rotation axis. The calibration scheme is combined with an articulated arm measuring machine. The whole process is simple to operate, with fast acquisition speed, high efficiency, and stable data point quality. Compared with the commonly used method of collecting trajectory dots on different planes and fitting circles of multiple planes, the selected rotation axis calibration method has a simplified and efficient calculation process.

[0081] (2) A method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system. Based on the obtained initial rotation axis parameters and initial hand-eye matrix, the rotation axis and the hand-eye matrix are comprehensively optimized based on a standard cylinder and a special target, greatly improving the calibration accuracy.

[0082] (3) A method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system. Through verification experiments, it can be clearly seen that there are obvious stratifications in the overlapping area after the point cloud is stitched using the rotation axis parameters and hand-eye matrix before optimization, with large deviations. While the overlapping area after the point cloud is stitched using the optimized rotation axis parameters and hand-eye matrix is closely interlaced with extremely small deviations, indicating that the optimized rotation axis parameters and hand-eye matrix are extremely accurate, reflecting the remarkable effect of the optimization method. Description of the drawings

[0083] Figure 1 is a flowchart of the method for initial calibration and optimization of the rotation axis and hand-eye relationship of the line laser scanning system in the present invention;

[0084] Figure 2Schematic diagram of the layout of the line laser scanning system and the articulated arm measuring machine involved in the present invention and the corresponding coordinate system established

[0085] Figure 3 Schematic diagram of the calibration principle of the rotating shaft in Step 3 of the present invention, where (a) is the schematic diagram of the prior art; (b) is the schematic diagram of the present solution

[0086] Figure 4 Detail diagram of the calibration process of the rotating shaft in Step 3 of the present invention; (a) shows the schematic diagram of the position change of the jumping frog when it rotates with the turntable; (b) shows the schematic diagram of the position between the jumping frog and the probe

[0087] Figure 5 Effect diagram of RANSAC fitting the coordinate axes of the base coordinate system in Step 2 of the present invention

[0088] Figure 6 Effect diagram of RANSAC fitting a circle in Step 3 of the present invention

[0089] Figure 7 Deviation diagram of the overlapping area of the cylindrical point cloud stitching before and after optimization in the verification example

[0090] Figure 8 Diameter of the point cloud fitting cylinder before and after optimization in the verification example

[0091] Figure 9 External view of the blade in the blade scanning scenario in the verification example

[0092] Figure 10 Partially enlarged view of the overlapping area of the point cloud stitching before and after optimization in the blade scanning scenario in the verification example

[0093] Reference numerals: line laser sensor 1; X-axis translation stage 2; Y-axis translation stage 3; Z-axis translation stage 4; turntable 5; articulated arm measuring machine 6; jumping frog cone 7; probe 8; blade 9 Detailed implementation manner

[0094] The present invention will be specifically described below with reference to the accompanying drawings

[0095] As shown in the attached Figure 1 figure, it is a flowchart of the initial calibration and parameter optimization of the rotating shaft and hand-eye matrix of the line structured light multi-dimensional scanning system of the present invention. The schematic diagram of the layout of the line laser scanning system and the articulated arm measuring machine in this method and the corresponding coordinate system established are as shown in the attached Figure 2 figure. In the figure, 1 is the line laser sensor, 2 is the X-axis translation stage, 3 is the Y-axis translation stage, 4 is the Z-axis translation stage, 5 is the turntable, and 6 is the articulated arm measuring machine

[0096] Initial calibration and optimization method for the rotation axis and hand-eye relationship of a line laser scanning system. The line laser scanning system collects the contour point cloud of the object to be measured through its laser sensor, and an articulated arm measuring machine is provided to implement the initial calibration and optimization method for the hand-eye relationship of the line laser scanning system; the initial calibration and optimization method for the hand-eye relationship specifically includes the following steps:

[0097] Step 1: Respectively establish a base coordinate system, a translation coordinate system where the translation stage is located, and a camera coordinate system where the line laser sensor is located in the line laser scanning system. The transformation relationship from the camera coordinate system to the translation coordinate system is the hand-eye relationship; obtain the transformation matrix from the camera coordinate system to the translation coordinate system and the transformation matrix from the translation coordinate system to the base coordinate system. The line laser scanning system is provided with a translation stage composed of translation axes in the X, Y, and Z axis directions, and the line laser sensor can move in the coordinate axis directions corresponding to the directions. The line laser scanning system is provided with a disc-shaped turntable, and the turntable drives the object to be measured on its surface to rotate under the drive of its rotating shaft, so as to realize the line laser sensor to collect the contour point cloud of the object on the turntable. The end of the articulated arm measuring machine is provided with a connection structure, and the connection structure is used to fix the probe or the laser scanning head. The articulated arm measuring machine controls the movement of the end through its robotic arm structure;

[0098] Step 2: Move all three translation axes of the line laser scanning system to the zero position, and the articulated arm measuring machine is connected with a spherical probe with a preset diameter. Use the probe to collect the coordinates of the origin of the base coordinate system at this time, that is, the zero position, and multiple points on each coordinate axis in the articulated arm coordinate system. Use the RANSAC algorithm to fit the points on the same coordinate axis into a straight line, and obtain the positions p of each coordinate axis and the origin in the base coordinate system in the articulated arm coordinate system B , and then obtain the transformation matrix from the base coordinate system to the articulated arm coordinate system;

[0099] Step 3: Control the turntable to rotate one week, and the probe at the end of the articulated arm measuring machine moves following the console under the control of its robotic arm structure. The probe measures a randomly fixed point on the surface of the turntable. When the turntable rotates 10°, obtain the position of the probe once, and then obtain the rotated coordinates of this point in the articulated arm coordinate system. Use the RANSAC algorithm to fit a circle for the multiple coordinates obtained during the rotation process to obtain the center position of the turntable surface and the normal direction of the circle passing through the center position. Through the inverse matrix of the transformation matrix from the base coordinate system to the articulated arm coordinate system obtained in Step 2, transform the center coordinates and the normal direction to the base coordinate system, and obtain the coordinates of a point on the straight line where the rotation axis of the turntable is located and the direction of the rotation axis in the base coordinate system, which are the coordinates of a point on the straight line where the rotation axis of the turntable is located and the direction of the rotation axis in the base coordinate system;

[0100] Step 4: Replace the probe at the end of the articulated arm measuring machine with a spherical ruby probe; use the ruby probe to collect points on the upper, lower, side, and front surfaces of the line laser sensor, and use RANSAC to fit a plane to obtain the position p of the origin of the camera coordinate system in the articulated arm coordinate system. c , use the transformation matrix from the base coordinate system to the articulated arm coordinate system obtained in Step 3 to transform the coordinate p c and the coordinate p B from the articulated arm coordinate system to the base coordinate system, and then obtain the translation vector of the transformation matrix from the camera coordinate system to the translation coordinate system, that is, the initial hand-eye matrix.

[0101] Step 5: Place a target with a preset shape on the surface of the turntable, and use the line laser sensor and the articulated arm measuring machine to scan the target respectively to obtain two point clouds of the target; preliminarily transform the point cloud scanned by the line laser sensor to the articulated arm coordinate system, and then use the ICP algorithm to register the two point clouds in the articulated arm coordinate system to obtain the registration matrix for registering the point cloud scanned by the line laser sensor to the point cloud scanned by the articulated arm, and this registration matrix is the initial hand-eye matrix.

[0102] In this step, the target with a preset shape is preferably a metal target with more than one square protrusion on its surface. The square protrusions are arranged in an array, and the target as a whole is strip-shaped.

[0103] Step 6: Select a cylinder with a preset size as the target to replace the target in Step 5. The line laser sensor scans the cylinder once every 90° rotation of the turntable to obtain a point cloud of one contour; perform RANSAC cylinder fitting on the point cloud scanned at 0°, and optimize the parameters of the rotation axis and the cylinder axis.

[0104] Step 7: Transform the optimized rotation axis to the articulated arm coordinate system. Use the initial hand-eye matrix as the initial value of the optimization variable to construct an objective function. The point cloud scanned by the line laser sensor in Step 5 is used as the source point cloud, and the point cloud scanned by the articulated arm is used as the target point cloud. Calculate the distance between the source point cloud and the target point cloud as the error metric, and minimize the sum of the squared residuals of the error metric to optimize the hand-eye matrix.

[0105] Furthermore, in Step 2, a leapfrog cone is used as a reference object for data collection, which specifically includes:

[0106] S21: Move the three translation axes of the system to the zero position of the grating scale of the system. The probe of the articulated arm measuring machine is a probe with a diameter of 15 mm, and the probe measures the position of the zero position at this time; fix the leapfrog cone to a point on the translation axis in the Z-axis direction, and collect the position of this point; control the movement of the translation axis in the X-axis direction, and the probe collects a point cloud data of the leapfrog cone every preset distance. Stop collecting when moving to the limit position, and then the translation axis returns to the zero position; repeat the above process to complete the collection of point cloud data in the Y and Z axis directions.

[0107] S22: Fit a straight line to the obtained point cloud data using the RANSAC algorithm; during the straight line fitting process, the parametric equation of the spatial straight line is represented by the following formula:

[0108]

[0109] In the above formula, (x0 y0 z0) represents a known point on the straight line; (i j k) is the direction vector of the straight line; t is a parameter;

[0110] Let Then formula (1) is transformed into the following formula (2):

[0111] p = p0 + t·n, t ∈ R (2)

[0112] Randomly select two points p 1， p2 collected on the same coordinate axis, and calculate the distance d from each other point p on this coordinate axis to the straight line where the axis is located as follows i The expression is: i

[0113]

[0114] Preset the distance threshold from a point to the straight line corresponding to this coordinate axis. If the distance from the point to the corresponding straight line is less than the distance threshold, then this point is considered an inlier of this straight line, and it is retained and counted; otherwise, it is identified as an outlier of this straight line, and the outlier needs to be excluded; repeat the above steps n times. After traversing all points, find all inliers that meet the inlier conditions; use the obtained inliers to substitute into formula (2) to obtain the optimized straight line equation, which is the fitted straight line equation;

[0115] S23: Obtain the directions n x 、n y 、n z of the coordinate axes of the base coordinate system and the position p B of the origin in the articulated arm coordinate system to obtain the transformation matrix for transforming the base coordinate system to the articulated arm coordinate system

[0116] Furthermore, step three specifically includes:

[0117] S31: Remove the leapfrog cone of the Z axis and fix a leapfrog cone at a position near the edge of the turntable surface; the turntable rotates 10° each time, and the probe collects point cloud data once. At least 36 pieces of point cloud data are collected;

[0118] S32: Fit a circle using the RANSAC algorithm; during the spatial circle fitting process, the standard equation of the spatial circle is as follows:

[0119] ​(x - a) 2 +(y - b) 2 +(z - c) 2 =r 2 (4)

[0120] In the above formula, (a, b, c) represents the center of the spatial circle, and r is the radius of the spatial circle;

[0121] Randomly select the point cloud data of three points from the point cloud data collected in step S31, and use the following formula to calculate the distance d from each other point to the circle i :

[0122]

[0123] Preset the distance threshold of the distance from the point to the circle; if the distance from the point to the circle is less than this distance threshold, then this point is considered an inlier inside the circle, retain it and count it; otherwise, it is identified as an outlier, remove the outlier, repeat n times, use the obtained inliers to substitute into formula (4), and the optimized spatial circle equation obtained is the fitted circle equation;

[0124] S33: Obtain the center position of the circle based on the fitted circle equation The normal direction passing through the center of the circle Obtain the inverse matrix of the transformation matrix obtained in step S23 as follows :

[0125]

[0126] Transform the center position The normal direction to the base coordinate system as follows:

[0127]

[0128] Furthermore, the translation vector of the hand - eye matrix obtained in step four

[0129] Furthermore, step five specifically includes:

[0130] S51: Fix the target on the turntable and face the line laser sensor. The line laser sensor scans one side of the target along the positive Z - axis direction to obtain the point cloud P of it in the camera coordinate system Cramera ;

[0131] S52: Replace the probe of the articulated arm measuring machine with a laser probe. The turntable rotates 180°, and the laser probe scans the target to obtain the point cloud P of the target part in the articulated arm coordinate system ArmCMM ;

[0132] S53: Set the initial rotation matrix of the transformation matrix from the camera coordinate system to the translation coordinate system Based on the initial translation vector obtained in Step 4 The initial hand-eye matrix T is as follows:

[0133]

[0134] According to the coordinate transformation relationship from the base coordinate system to the articulated arm coordinate system in Step 2, transform P Cramera to the articulated arm coordinate system, and then rotate P ArmCMM by 180° around the rotation axis obtained from the initial calibration to get the rotated point cloud P ArmCMM ;

[0135] S54: Set P Cramera as the source point cloud, and set the rotated point cloud P ArmCMM as the target point cloud; all points q i in the target point cloud constitute the set Q, then q i ∈Q; Use KD-Tree in the source point cloud set to find the corresponding point set p i ∈P such that ||p i -q i || is the smallest; obtain the matching point set P composed of all matching points; obtain the centroid of the matching point set in the articulated arm coordinate system as follows:

[0136]

[0137] In the above formula, represents the centroid of the source point cloud; represents the centroid of the target point cloud; N represents the number of the matching point set; then de-center

[0138]

[0139] In the above formula, p’ i and q’ i are the de-centered points of the source point cloud and the target point cloud respectively;

[0140] Construct the covariance matrix H for the de-centered point sets of the source point cloud and the target point cloud as follows:

[0141]

[0142] Perform SVD decomposition on the covariance matrix H, and the decomposition result is as follows:

[0143] H = UΣV T (12)

[0144] In the above formula, H represents the covariance matrix; U represents the matrix of the left singular vectors of matrix H; VT The matrix representing the right singular vectors of H;

[0145] At this time, the rotation matrix R = VU T , and the translation vector

[0146] Apply the calculated rotation matrix and translation vector to the source point cloud P Cramera , and the source point cloud at the new position is as follows:

[0147] P new = RP + t (13)

[0148] S55: Determine the iteration stop by calculating the magnitude of the transformed mean square error; where the mean square error E between the two point clouds after transformation is calculated as follows:

[0149]

[0150] When the change in the mean square error is less than the preset error threshold or the preset maximum number of iterations is reached, terminate the iteration. At this time, the obtained registration matrix is the true initial hand-eye matrix.

[0151] Furthermore, step six specifically includes the following steps:

[0152] S61: Fix a standard cylinder of a preset size on the turntable. The line laser sensor collects the cylinder point cloud once every 90° rotation of the turntable, and convert the collected cylinder point cloud to the base coordinate system;

[0153] S62: Perform cylinder fitting on the point cloud scanned at 0°, and obtain the axis position and direction parameters of the fitted cylinder;

[0154] S63: Create an optimization object, and give the initial value x0 = [a b c 0 0 d e f 0 0], where the first five are the initial values of the turntable axis, and the last five are the initial values of the cylinder axis;

[0155] S64: Use the Plücker matrix to represent the standard cylinder axis; constructed by two points on the straight line where the standard cylinder axis is located; assume that the straight line passes through two points P1 and P2, then the Plücker coordinates of the straight line can be expressed as:

[0156] L = (d, m) (15)

[0157] where, d = P2 - P1 is the straight line direction vector, and m = P1 × P2 is the moment vector of the straight line;

[0158] Use the following Plücker matrix calculation formula to obtain the expression of this straight line:

[0159]

[0160] In the above formula, m = (m3, m2, m1) and d = (d1, d2, d3) are the moment vector and direction vector of the straight line respectively;

[0161] S65: Traverse the points in the point cloud obtained in step S61 in a random order to the distance d from the axis of the standard cylinder i ;

[0162] Calculate the sum of squared errors from the point to the cylindrical surface as follows:

[0163] err i = (d i - r) 2 (17)

[0164] where d i is the distance from the i-th point to the axis of the cylinder; r is the radius of the standard cylinder;

[0165] Accumulate the sum of squared errors of this point to obtain the total error err 总 as follows:

[0166]

[0167] Iteratively calculate the total error. Each time an iteration is performed, the parameters of the rotation axis and the axis of the cylinder will be automatically optimized until the obtained total error is lower than a preset threshold, and the iteration stops. At this time, the parameters of the rotation axis and the axis of the cylinder are the finally optimized parameters of the rotation axis and the axis of the cylinder. Specific embodiments:

[0169] As shown in the appendix Figure 3 shown, Figure 3 (a) The principle of calibrating the rotation axis commonly used. As shown in the figure, the trajectory dots collected on different planes are respectively fitted into circles. After obtaining all the centers of the circles, these centers are fitted into a straight line to obtain the rotation axis parameters. This method requires too much data to be collected and the calibration process is cumbersome. In this method, use Figure 3 (b) The principle shown in, collect the trajectory dots (C1, C2... C n ) on a plane, fit the circle, and directly obtain the center coordinates O' and the normal O'R of the circle to achieve rapid initial calibration of the rotation axis. Figure 4 is a calibration schematic diagram of the rotation axis. In the figure, 7 is the frog-hop cone; 8 is a probe with a diameter of 15 mm. As Figure 4 (a) shown, fix the frog-hop cone on the turntable, P1, P2, P3... P 36 represent the positions of the frog-hop cone rotated 10° each time, and then as Figure 4 (b) shown, gently attach the probe to the upper end of the frog-hop cone, and the frog-hop cone drives the probe to move, thereby completing the acquisition of each position point. The acquisition method of the points in the three moving axis directions is the same.

[0170] Verification example:

[0171] To verify the calibration effect of this method, the probe used in step two of this verification example is a special frog - jump cone probe with a 15 - mm spherical tip: Fix the first frog - jump cone on the Z - axis of the scanning system. The probe acquires the current position once, then moves the X - axis, and acquires a data point every 10 mm of movement. Stop acquiring when reaching the limit position, and then return to the zero position. Repeat the above steps to complete the acquisition of data points in the Y - and Z - axis directions; Use the RANSAC algorithm to fit a straight line. The preset distance threshold from a point to the straight line corresponding to this coordinate axis is taken as 0.02 mm. Traverse all points, and the points that meet the condition that the distance from the point to the corresponding straight line is less than the distance threshold of 0.02 mm are classified as inliers. The fitting effect diagram is as attached Figure 5 shown

[0172] Figure 6 is the fitting effect diagram of the fitting circle of the turntable rotating shaft in step three; In this fitting process, the threshold with the circle is preset as 0.02 mm. The fitting effect diagram is as attached Figure 6 shown

[0173] In the above RANSAC fitting process, the algorithm uses a randomly sampled subset to replace the overall data set, so as to be able to effectively handle the situation with outliers. This random sampling method makes the algorithm have a certain robustness to outliers and can reduce the influence of outliers on model fitting. Therefore, the fitting accuracy is relatively high

[0174] In this method, steps six and seven are both processes for optimizing the initially obtained hand - eye matrix

[0175] Figure 7 is the color map of the point - cloud deviation before and after optimization. During the verification process, a standard cylinder with a diameter of 19.970 mm and a length of about 150 mm is used as the target. The line - laser sensor acquires the cylinder point - cloud once every 60° rotation of the turntable; From Figure 7 (a), it can be seen that in this verification example, the error in the overlapping area of the two pieces of point - cloud scanned by the line - laser sensor when the turntable is at 0° and 60° before optimization is large. The deviation of point - cloud stitching is between 0.07 (corresponding to 0.077 in the figure) mm and 0.1 mm Figure 7 (b) is the error in the overlapping area of the two pieces of point - cloud after optimization. It can be seen from the figure that the deviation of point - cloud stitching is within 0.02 mm (the minimum in the figure is 0.016 mm); Figure 8 is the diameter of the point - cloud - fitted cylinder before and after optimization. The diameter of the fitted cylinder before optimization is 19.939 mm, which differs from the standard diameter by 0.031 mm. The diameter of the fitted cylinder after optimization is 19.968 mm, which differs from the standard diameter by only 0.002 mm

[0176] Figure 9 、 10This is a reference scenario for scanning leaves using the hand-eye matrix calibrated by this method, where Figure 9 is the external view of the blade 9; the blade and the overlapping area of ​​the point cloud before and after optimization are partially enlarged, and the Figure 10 Scan the blade in different areas in a different way, and rotate the point clouds of different areas in the opposite direction according to the turntable angle to form a spliced ​​image. Figure 10 (a) shown. Figure 10 (b) It can be seen that the overlapping area of ​​the point cloud before optimization has obvious stratification after enlarging. Figure 10 (c) shows that after the optimization, the overlapping area of ​​the point cloud is enlarged and there is no obvious stratification, and the two point clouds are closely interlaced and stitched together. Figure 7 , Figure 8 as well as Figure 10 The experimental comparison data before and after optimization shown in the figure shows that the optimization effect is very significant.

[0177] Although the present invention has been disclosed as above in terms of preferred embodiments, they are not intended to limit the present invention. Anyone skilled in the art can make various changes or modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection defined by the claims of this application.

Claims

1. Initial calibration and optimization method for the rotation axis and hand-eye relationship of the line laser scanning system, characterized by: The line laser scanning system collects the contour point cloud of the object to be measured through its laser sensor, and is provided with an articulated arm measuring machine for realizing the initial calibration and optimization method of the hand-eye relationship of the line laser scanning system; the initial calibration and optimization method of the hand-eye relationship specifically includes the following steps: Step 1: In the online laser scanning system, a base coordinate system, a translation coordinate system where the translation stage is located, and a camera coordinate system where the line laser sensor is located are respectively established, wherein the transformation relationship from the camera coordinate system to the translation coordinate system is a hand-eye relationship; a transformation matrix from the camera coordinate system to the translation coordinate system and a transformation matrix from the translation coordinate system to the base coordinate system are obtained; the line laser scanning system is provided with a translation stage composed of translation axes in the X, Y, and Z axis directions, and the line laser sensor can move in the direction of the coordinate axis in the corresponding direction; the line laser scanning system is provided with a disc-shaped turntable, and the turntable drives the object to be measured on the surface of the turntable to rotate under the drive of its rotating shaft, so that the line laser sensor can collect contour point clouds of the object on the turntable; a connecting structure is provided at the end of the articulated arm measuring machine, and the connecting structure is used to fix the probe or the laser scanning head, and the articulated arm measuring machine realizes the control of the end movement through its mechanical arm structure; Step 2: Move the three translation axes of the line laser scanning system to the zero position, and connect the articulated arm measuring machine to a spherical probe with a preset diameter; use the probe to collect the origin of the base coordinate system, i.e., the zero position, and the coordinate information of multiple points on each coordinate axis in the articulated arm coordinate system, and use the RANSAC algorithm to fit the points on the same coordinate axis into a straight line to obtain the position p of each coordinate axis and the origin in the articulated arm coordinate system under the base coordinate system. B , and then obtain the transformation matrix from the base coordinate system to the joint arm coordinate system; Step 3: Control the turntable to rotate one circle, and the probe at the end of the articulated arm measuring machine follows the movement of the console under the control of its mechanical arm structure; the probe measures a random fixed point on the turntable surface, and obtains the position of the probe every 10° rotation of the turntable, and then obtains the coordinates of the point after rotation in the articulated arm coordinate system; fits the multiple coordinates obtained during the rotation process to a circle using the RANSAC algorithm to obtain the center position of the turntable surface and the normal direction of the circle passing through the center position, and transforms the center coordinates and the normal direction to the base coordinate system through the inverse matrix of the transformation matrix from the base coordinate system to the articulated arm coordinate system obtained in step 2, and obtains the center coordinates and the normal direction in the base coordinate system, which are the coordinates of a point on the straight line where the axis of rotation of the turntable is located and the direction of the axis of rotation in the base coordinate system; Step 4: Replace the probe at the end of the articulated arm measuring machine with a spherical ruby ​​probe; use the ruby ​​probe to collect points on the top, bottom, side and front of the surface of the linear laser sensor, and use RANSAC to fit the plane to obtain the position p of the origin of the camera coordinate system in the articulated arm coordinate system. c , using the transformation matrix from the base coordinate system to the joint arm coordinate system obtained in step 3 to transform the coordinate p c and coordinates p B Transform from the joint arm coordinate system to the base coordinate system, and then obtain the transformation matrix from the camera coordinate system to the translation coordinate system, that is, the translation vector of the initial hand-eye matrix; Step 5: Place a target of a preset shape on the surface of the turntable, and use a line laser sensor and an articulated arm measuring machine to scan the target respectively to obtain two point clouds of the target; preliminarily transform the point cloud of the line laser sensor scanning the target into the articulated arm coordinate system, and then use the ICP algorithm to align the two point clouds in the articulated arm coordinate system to obtain a registration matrix of the line laser sensor scanning point cloud to the articulated arm scanning point cloud, which is the initial hand-eye matrix; Step 6: Select a cylinder of preset size as the target to replace the target in step 5. Every time the turntable rotates 90°, the linear laser sensor scans the cylinder once to obtain a point cloud of the contour; perform RANSAC cylinder fitting on the point cloud scanned at 0°, and optimize the parameters of the rotation axis and the cylinder axis; Step 7: Transform the optimized axis of rotation to the articulated arm coordinate system, use the initial hand-eye matrix as the initial value of the optimization variable, construct the objective function, use the point cloud of the target scanned by the line laser sensor in step 5 as the source point cloud, and the point cloud of the target scanned by the articulated arm as the target point cloud, calculate the distance between the source point cloud and the target point cloud as the error metric, and minimize the residual sum of squares of the error metric to optimize the hand-eye matrix.

2. The method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system according to claim 1, characterized in that: In step 2, the jumping frog cone is used as a reference for data collection, which specifically includes: S21: Move the three translation axes of the system to the zero point position of the system's grating ruler. The probe of the articulated arm measuring machine is a probe with a diameter of 15 mm. The probe measures the position of the zero point at this time; fix the jumping frog cone to a point on the translation axis in the Z-axis direction, and collect the position of the point; control the movement of the translation axis in the X-axis direction, and collect the point cloud data of the jumping frog cone once every preset distance. Stop collecting when it moves to the limit position, and then return the translation axis to the zero point position; repeat the above process to complete the collection of point cloud data in the Y and Z axis directions; S22: Use the RANSAC algorithm to fit a straight line to the obtained point cloud data; in the straight line fitting process, the spatial straight line is expressed by the following parametric equation: In the above formula, (x0 y0 z0) represents a known point on the line; (ijk) is the direction vector of the line; t is the parameter; make Then formula (1) is transformed into the following formula (2): p=p0+t·n,t∈R (2) Randomly select two points p collected on the same coordinate axis 1， p2, calculate each other point p of the coordinate axis as follows i The distance d to the line where the axis lies i , the expression is: A distance threshold between a point and the line corresponding to the coordinate axis is preset. If the distance between a point and the corresponding line is less than the distance threshold, the point is considered to be an interior point of the line and is retained and counted. Otherwise, it is considered to be an exterior point of the line and needs to be removed. Repeat the above steps n times, and after traversing all points, find all interior points that meet the conditions of interior points. Substitute the obtained interior points into formula (2) to obtain the optimized straight line equation, which is the fitted straight line equation. S23: Obtain the coordinate axis direction n of the base coordinate system according to the fitted straight line equation x 、n y 、n z and the position p of the origin in the joint arm coordinate system B , get the transformation matrix from the base coordinate system to the joint arm coordinate system 3. The method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system according to claim 2, characterized in that: Step three specifically includes: S31: Remove the jumping frog cone of the Z axis and fix a jumping frog cone on the surface of the turntable near its edge; collect point cloud data once every 10° rotation of the turntable and the probe collects point cloud data once, and collect at least 36 point cloud data; S32: Use the RANSAC algorithm to fit the circle; in the process of spatial circle fitting, the standard equation describing the spatial circle is as follows: (x-a) 2 +(y-b) 2 +(z-c) 2 =r 2 (4) In the above formula, (a, b, c) represents the center of the space circle, and r is the radius of the space circle; Three points of point cloud data are randomly selected from the point cloud data collected in step S31, and the distance d from each other point to the circle is calculated using the following formula: i : A distance threshold of the distance from the point to the circle is preset; if the distance from the point to the circle is less than the distance threshold, the point is considered to be an inner point in the circle, and it is retained and counted; otherwise, it is considered to be an outer point, and the outer point is removed. Repeat n times, and use the obtained inner point to enter formula (4) to obtain the optimized spatial circle equation, which is the fitted circle equation; S33: Get the center position of the circle based on the fitted circle equation Direction of the normal through the center of the circle The transformation matrix obtained in step S23 is obtained as follows: The inverse matrix of : The center position Normal direction Transform to the base coordinate system as follows:

4. The method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system according to claim 3, characterized in that: The translation vector of the hand-eye matrix obtained in step 4 5. The method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system according to claim 4, characterized in that: Step 5 specifically includes: S51: Fix the target on the turntable and face the line laser sensor. The line laser sensor scans one side of the target along the positive direction of the Z axis to obtain its point cloud P in the camera coordinate system. Cramera ; S52: Replace the probe of the articulated arm measuring machine with a laser probe, rotate the turntable 180°, and scan the target with the laser probe to obtain the point cloud P of the target part in the articulated arm coordinate system. ArmCMM ; S53: Set the initial value of the rotation matrix of the transformation matrix from the camera coordinate system to the translation coordinate system Based on the initial translation vector obtained in step 4 The initial hand-eye matrix T is as follows: According to the coordinate transformation relationship from the base coordinate system to the joint arm coordinate system in step 2, P Cramera Transform to the joint arm coordinate system, and then transform P ArmCMM Rotate 180° around the initial calibration axis to get the rotated point cloud P ArmCMM ; S54: P Cramera Set as the source point cloud, and rotate the point cloud P ArmCMM Set as the target point cloud; all points q in the target point cloud i is formed into a set Q, then q i ∈Q; Use KD-Tree to find the corresponding point set p in the source point cloud set i ∈P, such that ||p i -q i || minimum; get the matching point set P composed of all matching points; get the centroid of the matching point set in the joint arm coordinate system as follows: In the above formula, represents the centroid of the source point cloud; Represents the centroid of the target point cloud; N represents the number of matching point sets; Re-decentralization In the above formula, p' i ,q' i They are the decentralized points of the source point cloud and the target point cloud respectively; The covariance matrix H is constructed for the decentralized point sets of the source point cloud and the target point cloud, as follows: Perform SVD decomposition on the covariance matrix H, and the decomposition result is as follows: H=UΣV T (12) In the above formula, H represents the covariance matrix; U represents the matrix representing the left singular vectors of the matrix H; V T The matrix representing the right singular vectors of H; At this time, the rotation matrix R = VU T , translation vector Apply the calculated rotation matrix and translation vector to the source point cloud P Cramera , the source point cloud at the new position is as follows: P new =RP+t (13) S55: Determine the end of the iteration by calculating the size of the mean square error after the transformation; wherein the mean square error E of the two point clouds after the transformation is calculated as follows: The iteration is terminated when the mean square error change is less than the preset error threshold or reaches the preset maximum number of iterations. The registration matrix obtained at this time is the true initial hand-eye matrix.

6. The method for initial calibration and optimization of the rotation axis and hand-eye relationship of a line laser scanning system according to claim 5, characterized in that: Step six specifically includes the following steps: S61: A standard cylinder of a preset size is selected and fixed on the turntable. The laser sensor collects a cylindrical point cloud every time the turntable rotates 90°, and the collected cylindrical point cloud is converted into a base coordinate system. S62: Perform cylinder fitting on the point cloud scanned at 0° to obtain the axis position and direction parameters of the fitted cylinder; S63: Create an optimization object, give the initial value x0 = [abc 0 0 def 0 0], where the first five are the initial values ​​of the turntable axis and the last five are the initial values ​​of the cylinder axis; S64: Use the Plücker matrix to represent the standard cylinder axis; construct it from two points on the line where the standard cylinder axis lies; Assuming that the straight line passes through points P1 and P2, the Plücker coordinates of the straight line can be expressed as: L=(d,m) (15) Among them, d = P2-P1 is the direction vector of the line, and m = P1×P2 is the moment vector of the line; Using the following Plüuücker matrix calculation formula, we can get the expression of the straight line: In the above formula, m = (m3, m2, m1) and d = (d1, d2, d3) are the moment vector and direction vector of the line respectively; S65: traverse the distance d from the point in the point cloud obtained in step S61 to the axis of the standard cylinder in a random order i ; The sum of squares of the errors from a point to the cylindrical surface is calculated as follows: err i =(d i -r) 2 (17) Among them, d i is the distance from the i-th point to the cylinder axis; r is the standard cylinder radius; The sum of squared errors at this point is accumulated to obtain the total error err 总 As follows: The total error is calculated iteratively. Each time the iteration is performed, the rotation axis and cylindrical axis parameters are automatically optimized until the total error is lower than the preset threshold. The iteration stops and the rotation axis and cylindrical axis parameters are the final optimized rotation axis and cylindrical axis parameters.

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