313 results about "Ellipse" patented technology

The invention belongs to the field of cable eccentricity detection, and particularly relates to a cable eccentricity detection method and system based on X rays. The method comprises the following steps: calculating a gradient magnitude diagram and a gradient direction diagram through an X-ray image of a cable, screening a point with the local maximum gradient magnitude and low neighborhood divergence as a contour starting point, performing contour tracking to generate a contour point set, and selecting a next contour point based on a tangential prediction direction; performing ellipse fitting on the contour point set to obtain a geometric center, long and short axis parameters and a root-mean-square error of a fitting ellipse, dividing the fitting ellipse into an inner candidate ellipse and an outer candidate ellipse according to a long axis, and matching the inner candidate ellipse meeting the condition for each outer candidate ellipse; and screening out an outer candidate ellipse and an inner candidate ellipse which meet conditions from the candidate pairs, and calculating the eccentricity of the cable to be measured based on geometric center coordinates of the outer candidate ellipse and the inner candidate ellipse. According to the invention, the accuracy and reliability of cable eccentricity measurement results can be improved.

The invention belongs to the technical field of image data processing, and particularly relates to a quality detection method and system for metal pipe fitting forming, and the method comprises the steps: obtaining a plurality of groups of matched gap regions of a port edge image according to the gray scale difference of the neighborhood of each gap of the port edge image in a corresponding metal pipe fitting image; obtaining a suspected defect area of the port edge image according to curvature change of edge pixel points of the port edge image; acquiring similar arc segments of each suspected defect area according to the change of the distance from the arc segment on the ellipse of the metal pipe edge image to the ellipse center; obtaining the abnormal degree of each suspected defect region according to the deformation difference between the suspected defect region and the similar arc section and the gray difference between the suspected defect region and the corresponding suspected defect region of the same group of matched gap regions; and screening to obtain a final defect area. According to the invention, the accuracy of quality forming detection of the metal pipe fitting is improved.

The invention provides a non-training burr detection method and device for a cover plate inner hole, relates to the field of burr detection, and solves the technical problem of non-target area interference caused by incapability of effectively focusing on an inner hole area. The method comprises the following steps: acquiring a current frame image of a target cover plate, and storing the current frame image as a grey-scale map; performing threshold segmentation on the grey-scale map, and extracting a maximum outer contour region in the grey-scale map; and carrying out convex hull calculation, and removing a concave part in the maximum outer contour region to obtain a regular convex hull contour. And generating an optimal ellipse boundary through an ellipse fitting algorithm. And carrying out segmentation fitting to remove outliers to obtain a final ellipse boundary. And generating a binary mask based on the ellipse fitting region, extracting a pixel set of which the gray value is zero in the mask, and outputting a burr region. And calculating the total defect area, comparing the total defect area with a dynamically adjusted area threshold value, judging whether the cover plate is qualified or not, and feeding back a judgment result to the detection control system. The device is used in the burr detection process of the inner hole of the cover plate.

The invention relates to a camera calibration method and system based on solid circle feature points, and belongs to the field of machine vision. The method comprises the following steps: firstly, acquiring a plurality of images of different poses of a calibration plate, then sorting a plurality of large solid circles on the calibration plate from large to small according to the circle center spacing between the large solid circles, and then calculating a first perspective projection transformation matrix according to the circle center coordinates of the sorted large solid circles and the center coordinates of an ellipse; and obtaining internal and external parameters of the to-be-calibrated camera according to the first projection transformation matrix so as to realize calibration of the to-be-calibrated camera. The feature points are obtained by using the sorted large solid circles, so that the point location quality and the matching accuracy are improved, and the precision of calibration parameters is remarkably improved.

The invention discloses a steel pipe diameter and out-of-roundness measuring method based on ellipse fitting. The method comprises the following steps: acquiring section contour data of a steel pipe; utilizing an improved ellipse fitting algorithm to obtain an optimal ellipse model and a corresponding local point; reconstructing steel pipe section contour measurement data through a linear interpolation algorithm; and the maximum diameter and the minimum diameter of the steel pipe are calculated by using the reconstructed steel pipe section contour measurement data, so that the out-of-roundness of the steel pipe is determined. On the basis of geometric distribution of data points and high efficiency of an improved ellipse fitting algorithm, steel pipe section contour measurement data can be accurately reconstructed; according to the improved ellipse fitting algorithm, the confocal hyperbolic distance is used for replacing the algebraic distance, the actual geometric distance from the steel pipe section contour data points to the fitting ellipse can be accurately reflected, the fitting ellipse better conforms to the actual section contour of the steel pipe, effective data points are obtained, and the fitting precision is improved. Noise points and outliers generated by a measuring instrument and the environment are eliminated, and the measuring precision is improved.

The present disclosure relates to a method and device for a camera calibration algorithm using an unbiased conic estimator considering distortion, and may be configured to calculate an ellipse in a normalized coordinate system from a circular pattern in a space, express a center of a distorted ellipse in a camera coordinate system as a linear combination of moments of the ellipse, and perform camera calibration from an image of the circular pattern using the center as a control point.

The invention relates to a crack prediction method and device based on post-stack seismic orientation attribute difference, and the method comprises the steps: carrying out the guided filtering of original seismic data, and obtaining the filtering data; setting a plurality of azimuth angles, and respectively extracting a plurality of azimuth attribute data of the filtering data based on the plurality of azimuth angles; ellipse fitting is carried out on the multiple pieces of azimuth attribute data, and ellipse parameters are obtained; and fracture data are obtained through analysis according to the ellipse parameters. According to the method, the response characteristics of the crack can be captured from different directions, so that the distribution rule of the crack is more comprehensively described, and the crack prediction precision is remarkably improved.

The invention relates to the technical field of image processing, in particular to a rubber ring contour burr detection method and system based on geometric transformation, and the method comprises the steps: obtaining a rubber ring image, and extracting the outer contour of a rubber ring and the contour of each burr in the rubber ring image; fitting the outer contour of the rubber ring by adopting a least square method to obtain an ellipse, and mapping the ellipse into a standard circle: carrying out bilinear interpolation resampling on the rubber ring image, and carrying out polar coordinate transformation on the rubber ring image by taking the circle center of the standard circle as an original point to generate an expanded image; generating a reconstructed image with enhanced burr features from the expanded image through wavelet transform, determining burr parameters of the reconstructed image, mapping the burr parameters back to a Cartesian coordinate system of the rubber ring image, and generating a detection result containing burr number, position and size information; according to the invention, the accuracy and robustness of tiny burr detection can be improved.

The invention discloses a product detection method and device, electronic equipment and a readable storage medium, which are applied to the technical field of image processing, and the method comprises the steps: extracting a plurality of product edge feature points from an image of a circular product, carrying out the fitting of the plurality of product edge feature points to obtain an ellipse, and carrying out the building of a standard circle through the ellipse, then, a perspective transformation matrix is constructed by using an ellipse and a standard circle, perspective transformation is carried out on the multiple product edge feature points and images respectively, non-standard circles presented by qualified circular products in the images due to camera shooting angle or product position inclination are corrected, complete visual angle correction is achieved, and the product quality is improved. And finally, based on the plurality of transformation feature points obtained by perspective transformation and the target image obtained by perspective transformation, carrying out qualification detection on the circular product, so that the over-detection rate can be reduced, and the detection efficiency and precision of the circular product can be improved.

The invention provides a non-contact steel pipe end face size measurement method and system, and the method comprises the steps: traversing recognized contour points on the basis of obtaining an image and recognizing the contour of the image, calculating the distance between the contour points, judging the contour points which are too far away from each other as burrs, eliminating the influence of the points, carrying out the ellipse fitting of the contour, and obtaining the size of the end face of a steel pipe. And parameters such as the inner diameter, the outer diameter and the roundness can be calculated according to an ellipse fitting result. According to the invention, based on the original image of the pipe end, the contour of the pipe end is identified by combining image edge detection and a graphic method, the position relation between contour points and the contour is calculated through a self-research algorithm, pipe end burrs are accurately positioned, and the influence of the burrs on the measured pipe end size is eliminated. The problems that a manual measurement method is insufficient in precision and high in maintenance cost are solved, the burr sensitivity is improved, and the effective pipe end size is accurately obtained.

The invention provides a gear peeling time-varying meshing stiffness prediction method and system based on a back propagation neural network, and the method comprises the steps: considering a tooth surface peeling fault based on a gear tooth bearing contact analysis method, and constructing a helical gear pair time-varying meshing stiffness calculation model; a real irregular tooth surface peeling area is fitted by adopting a least square ellipse fitting method to obtain an ellipse appearance representation, any peeling position is completely described through six key geometric parameters, the geometric parameters of the ellipse appearance are systematically traversed and fitted, and diversified peeling appearance samples are generated. Introducing a tooth profile deviation matrix corresponding to the peeling morphology sample into a tooth surface bearing contact analysis model, and constructing a training data set; and constructing a back propagation neural network model of multiple hidden layers, and performing end-to-end training by using the training data set, so that the back propagation neural network model learns a nonlinear mapping relationship from geometric parameters to a time-varying meshing stiffness curve, thereby predicting the time-varying meshing stiffness under any peeling morphology.

Methods, systems and apparatuses may provide for technology that determines a major axis length of an ellipse in texture space based on a transformation matrix associated with a circle in screen space, inverts the major axis length, determines a product between the inverted major axis length and a determinant of the transformation matrix, and determines a minor axis length based on a modulus of the product between the inverted major axis length and the determinant of the transformation matrix. In one example, the technology selects a level of detail in the texture space based on the major axis length, the minor axis length, a direction of the major axis length, and a direction of the minor axis length.

According to one or more embodiments of the present disclosure, an ellipse model may be applied to detection results included in ultrasonic sensor data (USS data) to identify one or more objects that may be indicated by the detection results. The identification of the objects may include determining the locations, shapes, and / or classifications of at least portions of the objects. For example, in some embodiments, the ellipse model may be applied to detection arcs indicated in USS data and corresponding to detection of an object using multiple ultrasonic sensors. In some embodiments, the application of the ellipse model may include fitting an ellipse to the detection arcs. The resulting ellipse and / or its corresponding ellipsoidal parameters may indicate one or more properties about the object.

The invention belongs to the technical field of scanning measurement, particularly relates to a cable outer diameter and ovality measurement method and system based on line laser contour scanning, and aims to solve the technical problem of low measurement precision caused by the fact that an existing algorithm is sensitive to noise, asymmetry of light strips and contour discrete points. The measurement method comprises the following steps: S1, performing anisotropic Gaussian filtering on a pixel according to a local tangential direction of a preliminary center line; s2, calculating a second derivative value and a third derivative value of the sub-pixel center point in the normal direction; s3, performing initial weighted least square ellipse fitting by using the corrected contour point set and the corresponding fitting weight to obtain parameters of an initial ellipse; and S4, based on the lengths of the long axis and the short axis of the fitting ellipse, calculating to obtain the outer diameter and the ellipticity of the cable. According to the measurement method, the interference of abnormal data points introduced by local flaws such as oil stains and scratches on the surface of the cable is eliminated, and the accuracy and the stability of a fitting result are improved.

Embodiments are disclosed for determining a spin rate and axis of a ball using deep learning. In some embodiments, a method comprises: training a deep learning network on training images of spinning balls, each spinning ball having at least one feature point in a time series that forms a two-dimensional (2D) ellipse image in a 2D plane; capturing, with at least one camera, a series of images of a ball; predicting, with the trained deep learning network, spin measurements associated with the ball based on the series of images; determining a spin rate of the ball based on the spin measurements; determining coefficients of a 2D ellipse model based on the spin measurements and the spin rate; and determining, with the at least one processor, a spin axis of the ball in 3D space based on the 2D ellipse model and the spin rate.

The invention relates to the technical field of spacecraft navigation, and discloses a method for estimating the relative attitude of a failed spacecraft under the constraint of computing resources, and the method comprises the steps: carrying out the preprocessing of measurement data, obtaining the observation data of the relative attitude of a camera based on an ellipse recognition algorithm, and obtaining the measurement data of the relative attitude of a laser radar based on an iterative nearest point algorithm. Pseudo measurement factors are designed for the camera and the laser radar, and variational integral prediction factors are designed for attitude increments at adjacent moments of the failed spacecraft; factor graph optimization based on a moving window is carried out, and the relative attitude of the failed spacecraft is estimated; the momentum conservation characteristics of the failed spacecraft can be mined through a designed variational integral predictive factor, the constraint relation of attitude increments at adjacent moments is constructed, and the problem that the estimation precision of an existing scheme depends on high-frequency measurement input is solved; and low-frequency measurement data of the camera and the laser radar are fused through a built failure spacecraft full-state factor graph model, so that the relative pose estimation of the non-cooperative target under the low computing power load is realized.

The invention discloses a round hole pose measurement method based on reprojection optimization. The method comprises the steps that a binocular camera is used for collecting two target images containing a round hole, then initial pose parameters of the round hole are obtained, then a projection ellipse of the round hole on the plane of the binocular camera is generated through re-projection, the ellipse is detected in combination with the edge, the updating step length of the pose parameters of the round hole is obtained after processing is conducted through an ellipse error and a cosine attenuation strategy, and the pose parameters of the round hole are obtained. And the pose parameter of the circular hole is iteratively updated to realize the measurement of the pose of the circular hole. According to the method, the circular hole space pose parameters serve as variables to be optimized, the projection ellipse of the circular hole on the plane of the binocular camera is generated, the error between the projection ellipse and the ellipse obtained through the ellipse detection algorithm is minimum, the ellipse detection result is fully utilized, the defect that the ellipse detection result cannot meet the binocular vision epipolar constraint is overcome, and the binocular vision epipolar constraint requirement is met. Meanwhile, a cosine attenuation strategy is combined to calculate a learning rate, so that a circular hole space pose parameter calculation result is quickly converged, and the measurement precision is improved.

The invention relates to the technical field of intelligent monitoring, in particular to an old people behavior abnormity monitoring system based on thermal imaging, which comprises a processor and a memory, the processor executes a computer program stored in the memory so as to realize the following steps: according to a long axis included angle, a gravity center and an axial ratio of a minimum circumscribed ellipse of a target area on a to-be-judged image; and obtaining an included angle change representation value of a local window corresponding to the first suspected fall image, a gravity center shift degree corresponding to the to-be-judged image and an elliptical deformation degree corresponding to the to-be-judged image, and monitoring the fall behavior of the monitored object according to the included angle change representation value, the gravity center shift degree and the elliptical deformation degree. And the accuracy of monitoring the falling behavior of the monitored object can be improved.

The invention discloses a circular hole measurement method based on image feature recognition, a medium and a system. The method comprises the steps of S1, performing Gaussian filtering processing on an original image; s2, performing gray scale superposition projection through a sub-pixel circular boundary projection algorithm to generate a projection curve; s3, performing moving average filtering on the projection curve to generate a smooth curve; s4, performing differential operation based on the smooth curve to generate a differential curve; s5, screening an effective boundary feature point set on the differential curve; s6, for each extreme point in the effective boundary feature point set, calculating an adaptive threshold value in a neighborhood gray scale curve of the extreme point, and realizing sub-pixel-level positioning through gray scale straight line and smooth curve interpolation fitting; s7, generating an initial ellipse model from the sub-pixel feature points through a robustness ellipse fitting algorithm; and S8, iteratively optimizing a fitting result, removing abnormal points which deviate from the model and exceed a threshold value, and outputting an optimized ellipse parameter. The method has the advantages of high measurement precision and the like.

The present invention discloses a robust optimization method for autonomous optical navigation landmarks for planetary landing, which belongs to the field of deep space exploration technology. The implementation method of the present invention is as follows: using the height information of the lander to determine the scale of the image plane projected onto the planetary surface, and deriving the quadrilateral vertex expression of the field of view based on the geometric relationship; using the relationship between the field of view vertex deviation and the lander posture error, converting the posture uncertainty to the field of view vertex uncertainty, and using the error ellipse to describe the field of view vertex uncertainty distribution; screening the quadrilateral area formed by the intersection of common tangents, which is the field of view intersection under the lander posture uncertainty; using the nominal trajectory and camera parameters to estimate the field of view sequence, combining the field of view intersection acquisition method to obtain the field of view intersection sequence, the field of view intersection sequence is obtained by offline estimation, and the amount of onboard calculation of the lander is reduced; using the observability of the navigation system to establish the landmark optimization index, optimize the selection of the landmarks in the field of view intersection sequence, and reduce the influence of posture uncertainty on the selected landmarks.

The invention relates to a camera calibration method and device based on a circular calibration plate and computer equipment, and the method comprises the steps: calculating a first circle center coordinate of an original calibration plate image through a sub-pixel edge extraction algorithm, and further calculating a primary calibration parameter of a camera; based on the initial calibration parameters, performing geometric correction on the original calibration plate image to obtain a calibration plate front view image; secondary calibration is carried out on the to-be-calibrated camera based on the front view image of the calibration plate, secondary calibration parameters are obtained, and secondary calibration is completed based on inverse processing of sub-pixel edge extraction and geometric correction; and determining the final calibration parameter of the to-be-calibrated camera based on the secondary calibration parameter, thereby solving the problem of low calibration accuracy, fitting ellipse center data with higher precision, and performing high-precision correction on ellipse eccentricity through geometric correction and inverse processing, thereby obtaining a more accurate calibration result and improving the stability of camera calibration.

The invention discloses an ultrasonic guided wave damage ellipse imaging positioning method and equipment for a layer decreasing composite material laminated plate. The method comprises the following steps: S1, acquiring thickness change direction information of the laminated plate and position coordinates of an excitation transducer and a receiving transducer; s2, according to the material characteristic parameters, simulating and calculating the propagation time of ultrasonic guided waves transmitted from an excitation transducer to any point to generate a first theoretical propagation time map, and simulating and calculating the propagation time of the ultrasonic guided waves transmitted from any point to a receiving transducer to generate a second theoretical propagation time map to generate a second theoretical propagation time map; coupling influence of thickness change and material anisotropy on guided wave propagation is considered in the simulation process; s3, transmitting an ultrasonic guided wave signal, and extracting the actual flight time of a damaged wave packet; s4, calculating theoretical total propagation time, and determining a candidate area where damage exists; and S5, on the basis of repeated operation of the multiple groups of transducer pairs, taking a plurality of candidate region intersections to determine a final damage position. The objective of the invention is to solve the positioning error problem caused by the structural characteristics of a laminated plate in a traditional algorithm, and to realize more accurate damage detection and positioning.

The invention discloses an angle calibration method, electronic equipment and a storage medium. The method comprises the following steps: acquiring a sampling point output by an angle sensor, and performing ellipse linear fitting on the sampling point to obtain a first fitting curve; determining an abnormal point according to the first fitting curve; after abnormal points are removed, ellipse linear fitting is carried out again to obtain a second fitting curve; and calibrating the second fitting curve as a standard circle. According to the technical scheme provided by the embodiment of the invention, the deviation of the amplitude and the phase caused by the error of the mounting position of the sensor and the influence of other factors is calibrated, and the motor control precision is improved, so that the motor control stability is improved.

The invention discloses a high-rigidity structure target vibration recognition method and system based on computer vision, a terminal and a medium, and the method comprises the steps: constructing a training data set for target vibration recognition based on a bridge model, and training an EDVR model which is a video super-resolution network; obtaining a to-be-recognized image sequence, performing super-resolution processing on the to-be-recognized image sequence based on the trained EDVR model, and obtaining a fitting ellipse according to the to-be-recognized image sequence subjected to the super-resolution processing; and on the basis of the fitting ellipse, recognizing the displacement of the structural target spot and the vibration frequency of the structural target spot to obtain the vertical physical displacement of the target spot at each moment and the vertical vibration acceleration data of the target spot at each moment, and on the basis of the vertical physical displacement and the vertical vibration acceleration data, obtaining the deflection of the bridge and the frequency of the bridge. According to the invention, the EDVR model is adopted to carry out super-resolution processing on the structure target spot, so that the recognition effect on the vibration of the high-rigidity structure can be improved.

The invention relates to an intersecting line welding seam extraction method, a medium and equipment. The method comprises the following steps: constructing an initial intersecting line welding seam model, collecting workpiece contour point clouds, obtaining a plurality of main pipe local point clouds and a plurality of branch pipe local point clouds, fitting elliptic equations for the local point clouds, obtaining circle centers corresponding to the local point clouds, fitting straight lines according to the circle centers, and extracting intersecting line welding seams. Obtaining the surface parameters of the main pipe according to the elliptic equations, updating the initial intersecting line welding seam model according to the axis equations and the surface parameters of the main pipe, obtaining an optimized intersecting line model, obtaining the included angle between the axis equations of the main pipe and the branch pipes and a conversion matrix, and substituting the included angle and the conversion matrix into the optimized intersecting line model. And obtaining an intersecting line parameter equation so as to extract an intersecting line welding seam. The problems that in the prior art, machining precision is low, adaptability is insufficient, meanwhile, collection precision is low due to high workpiece reflective rate, and welding quality is affected are solved.

The invention discloses a shield segment splicing elliptic change detection method, relates to the technical field of shield segments, and breaks through the limitation that in traditional detection, elliptic change and slab staggering are detected separately, and judgment depends on artificial experience. An integrated design of circular seam point cloud accurate screening-double circular seam plane fitting correction-least square circle fitting and ellipsometry parameter linkage calculation is adopted, secondary correction is performed through a second circular seam plane equation, the problem that single circular seam plane fitting is easily influenced by model reconstruction errors is solved, the fitting precision is improved, and the fitting precision is improved. The technical closed loop of section geometric feature extraction-ellipse parameter quantization-slab staggering reference calibration is achieved, meanwhile, least square circle fitting of YZ section point clouds is combined with ellipse long axis, ellipse short axis, ellipse rate and deformation deviation calculation depth, ellipse judgment is achieved through double threshold values of ellipse rate grading and deformation deviation threshold values, the risk of misjudgment of a single parameter is avoided, and the method has the advantages of being high in practicability and high in practicability. And a high-precision reference surface is provided for subsequent slab staggering quantity calculation.

The invention relates to a nested identifier design and visual positioning method for target alignment in a complex scene. The method comprises nested positioning identifier design, concentric circle visual detection positioning and two-dimensional code visual detection positioning. The method comprises the following steps: firstly, designing an outer-layer positioning identifier by adopting a mode of eccentrically nesting two concentric circles with different sizes, and designing an inner-layer positioning identifier by adopting a mode of nesting a two-dimensional code; and secondly, obtaining a target ellipse set by adopting an ellipse detection method based on segmental arc detection classification, designing concentric ellipse constraints, obtaining a target concentric ellipse set, carrying out concentric circle center projection point positioning, and realizing identification positioning calculation. And finally, the target two-dimensional code is detected, and nested two-dimensional code pose calculation is realized by adopting an improved EPnP pose calculation method.

The invention discloses a deep hole inner diameter calculation method based on ellipse fitting, belongs to the technical field of size measurement, and solves the problems that the actual contours of some deep holes are not perfect circular holes, the inspection size pays more attention to the minimum value of the inner diameter, and the consistency of the diameter obtained by using circle fitting is not ideal. Comprising the following steps of: 1, scanning the inner wall of a deep hole by using an optical distance measuring sensor to obtain a plurality of pieces of inner hole surface distance data; 2, performing ellipse fitting on the scanning data to obtain a parameter equation of the scanning data; and 3, calculating the short axis length of the ellipse as the inner diameter of the deep hole according to the equation. According to the invention, the inner diameter size of the deep hole can be quickly and accurately calculated, and the consistency of measurement results is effectively improved.

The invention provides a bearing inner and outer diameter defect detection method and system based on industrial vision, and the method comprises the steps: collecting an outer diameter surface image of a bearing, and extracting all defect detection frames in the outer diameter surface image of the bearing; for each defect detection frame, determining a plurality of defect identification points of the defect detection frame based on an inscribed ellipse in the defect detection frame, and constructing a defect candidate part corresponding to the defect detection frame according to all the defect identification points; determining the identification confidence coefficient of the defect detection frame during defect identification through the direction consistency between the defect candidate part and the inscribed ellipse, and screening out an effective defect detection frame based on the identification confidence coefficient of each defect detection frame; and extracting all defect edge points in the effective defect detection frame, and fitting all the defect edge points to obtain the scratch defect corresponding to the effective defect detection frame. According to the scheme, the scratch defect is obtained based on defect edge point fitting, and a real defect area can be identified under the condition that the outer diameter surface of the bearing is smooth and is influenced by light reflection.

The invention discloses a 2D / 3D visual calibration plate for industrial manufacturing, which comprises a calibration plate body, a plurality of target patterns are arranged on the calibration plate body, the target patterns comprise circular patterns and / or square patterns, and the circular patterns are used for calculating an ellipse center point under imaging perspective deformation of an industrial robot camera; the checkered pattern comprises cross lines and digital labels and is used for calibrating the tail end of the industrial robot, and calibration comprises calculation of a coordinate transformation relation between a camera coordinate system and a robot coordinate system. According to the method, the calibration is more precise through the structural optimization of the calibration plate, the calibration process is simplified through the three-point method, the calculated amount is extremely small, the calibration precision and efficiency are remarkably improved, the coordinate axis orientation is assisted through the arrangement of the asymmetric pattern, the horizontal and vertical coordinate axes are judged through the assistance of the grid pattern, and the robustness is improved.