324 results about "Rotation matrix" patented technology

The invention relates to a course axis drift suppression method and device, a holder and a medium, and the method comprises the steps: receiving original data of a current course, the original data comprising an absolute angle outputted by a course encoder, and an acceleration and an angular velocity outputted by an IMU module; the original data are converted into a unified coordinate system through a rotation matrix, and mechanical installation deviation is compensated; performing data fusion on the compensated original data through a preset fusion algorithm; and outputting the fused absolute angle to a servo mechanism of the holder, and by adopting the method, through real-time sensor data alignment, a dynamic compensation algorithm and a fusion algorithm, a course drift suppression mechanism which is resistant to dynamic interference and low in cost is constructed, and static drift lt can be realized; the dynamic tracking error is 1t, 0.01 degree / h and 1t; and the technical index is 0.05 degree.

The invention belongs to the technical field of computer vision, deep learning and time-space prediction, and discloses an end-to-end time-space prediction method based on improved three-dimensional rotation position coding, which is suitable for various time-space sequence prediction scenes such as weather, traffic flow and the like. According to the invention, through four key improvements, a position coding mechanism is optimized; three-dimensional coding proportions of time, height and width are dynamically adjusted so as to adapt to different scenes; fusing the absolute time and the relative space position, and strengthening local space-time correlation modeling; the position information directly guides attention calculation, and the fusion with an Attention module is deepened; and a rotation matrix cache mechanism is introduced to reduce redundant calculation. Meanwhile, the model is matched with a Patch embedding layer, an adaptive Transform encoder and an MLP de-wharf, a complete link of'feature embedding-position encoding-space-time fusion-prediction output 'is constructed, and the precision, generalization and reasoning efficiency of space-time prediction are effectively improved.

The invention belongs to the technical field of space remote sensing surveying and mapping, and particularly relates to a monitoring system and method for a front and rear view visual axis included angle and absolute direction of a surveying and mapping camera. The method comprises the following steps: S1, through side sway of a satellite platform, taking a time for sky imaging calibration as a reference time; s2, calculating a rotation matrix from a front and rear view ground camera measurement coordinate system to a star camera coordinate system at a reference moment; s3, calculating respective thermal deformation matrixes of the star camera coordinate system, the front-view camera measurement coordinate system and the rear-view camera measurement coordinate system; s4, obtaining a real-time rotation matrix from the measurement coordinate system of the front-view camera to the coordinate system of the star camera and a real-time rotation matrix from the measurement coordinate system of the rear-view camera to the coordinate system of the star camera at the measurement moment; and S5, carrying out arc cosine calculation on the two absolute pointing vectors to obtain a visual axis included angle between the front-view camera and the rear-view camera at the measurement moment. According to the invention, while the geometric accuracy of the surveying and mapping camera is ensured, the real-time performance of measurement and the comprehensiveness of subsystem monitoring are realized at the same time.

The invention discloses a robot hand-eye calibration method, control equipment and a robot system, and relates to the technical field of robots. The robot hand-eye calibration method comprises the following steps: uniformly correcting a plurality of pixel coordinates obtained by dynamic shooting to a reference pixel coordinate system which is consistent with a camera coordinate system at a reference position in direction; and meanwhile, the world coordinates of the end effector corresponding to each sampling position are localized relative to the world coordinates of the end effector at the reference position, so that interference caused by global coordinate offset and camera orientation difference is eliminated, and the application range of the hand-eye calibration method is expanded. Besides, a singular value decomposition algorithm is adopted to solve a mapping relation between pixel coordinates and local world coordinates under a reference pixel coordinate system, so that a solved rotation matrix can meet orthogonality constraints, the hand-eye transformation process strictly conforms to a robot motion model with translation and rotation motion, and the calibration precision is improved. The calibration process can be automatically calculated and completed, and the calibration efficiency is high.

The invention discloses a binocular structured light three-dimensional reconstruction and dynamic rotation matrix-based large rotation equipment rotor multistage stacking concentricity accurate measurement method, and belongs to the technical field of non-contact optical measurement, three-dimensional reconstruction and assembly precision measurement. The method comprises the following steps: 1, binocular structured light three-dimensional reconstruction; step 2, dynamic rotation matrix correction: correcting the space attitude of the surface of the spigot, and converting all measured point clouds to a unified coordinate system for concentricity calculation; 3, multi-stage stacking eccentricity error evaluation under the polar coordinate system is carried out, the concentricity is rapidly calculated on the basis of a three-dimensional reconstruction result, and visual distribution of eccentricity errors is formed for subsequent online compensation; and 4, constructing a feed-forward + feedback compensation closed-loop system based on the measurement and error transfer model in the step 3, and correcting the eccentric error in real time in the assembly process. The defects that existing contact measurement is low in efficiency, contact damage exists, and multi-stage assembly accumulative errors cannot be evaluated and compensated in real time are overcome.

The invention discloses a multi-view three-dimensional reconstruction driven cattle body size online measurement method, and relates to the technical field of animal husbandry three-dimensional measurement, and the method comprises the steps: extracting a ground reference plane, a segment elevation function, a guardrail reference line, a segment guardrail spacing, a periodic pitch and a hoof ground contact event, and generating a calibration opportunity score in combination with a pixel-level quality weight map; in the sliding window factor graph, jointly solving an external parameter rotation matrix, an external parameter translation vector and a global scale by taking the prior as a constraint, and outputting an uncertainty matrix; implementing hierarchical self-recovery according to the comprehensive health degree and the score, and replacing safe writing with double buffer atoms; carrying out weighted splicing under a unified measurement coordinate and carrying out profile robust measurement, forwards transmitting uncertainty to a body size layer and supporting individual multi-time column-passing convergence; the method is suitable for channel visibility interruption and structure variable scenes, and under the condition of uninterrupted release, measurement consistency is kept and auditable results are output.

The application discloses a kind of bridge tower segment attitude intelligent prediction method and system based on multi-point cooperative positioning, method includes: S100, in the two adjacent sides of the segment that has been installed, select multiple observation points, using laser reflector obtains the space coordinates of observation point, using multiple total station instruments cooperates measurement;S200, based on rigid body transformation mathematical model, the attitude change prediction of segment to be installed, using rotation matrix and translation vector calculates the optimal attitude of segment to be installed, too much point redundant information optimizes attitude estimation, controls cumulative error;S300, BIM modeling is carried out to bridge tower structure, and high-precision three-dimensional rendering is carried out, complex monitoring data is converted into intuitive graphical interface, and segment state is shown in real time;S400, according to data comparison, combined with error analysis, if the error is larger than design data, then corresponding adjustment is carried out;S500, repeat the above steps, until all bridge tower segments are accurately positioned and installed. The precision and construction efficiency of bridge tower segment erection are improved.

One or more embodiments of the invention provide a model quantification method and apparatus, a storage medium and a program product. The method comprises the steps of reconstructing a weight of at least one network layer in a to-be-quantized initial model based on an orthogonal rotation matrix; performing quantitative perception training on the reconstructed model to jointly optimize the weight of the at least one network layer and the corresponding rotation matrix; the optimized weight is quantified to generate a target model, and the weight precision of the target model is lower than that of the initial model.

The invention discloses an intelligent processing method and system for multi-source data fusion of surveying and mapping equipment, and belongs to the technical field of surveying and mapping data processing.According to the method and system, an initial LiDAR point cloud is combined with position data and attitude data for joint calculation to obtain an accurate LiDAR point cloud, the accuracy of point cloud data is optimized, and therefore the accuracy of final registration is improved, and the registration accuracy is improved. And matching the point cloud multi-scale feature point set with the image multi-scale feature point set to obtain a point cloud homonymy point set and an image homonymy point set, analyzing a rotation matrix and a translation vector through a quaternion registration algorithm, and completing registration of the target panoramic image and the precise LiDAR point cloud according to the rotation matrix and the translation vector. And high-precision space registration is realized through a quaternion registration algorithm, the registration accuracy is further improved, and the surveying and mapping precision is improved.

An image processing method, an image display apparatus, a computer program product, and an aircraft are disclosed. The image processing method includes: generating a two-dimensional output image based on input information; guiding a light beam corresponding to the output image to a display unit; capturing a three-dimensional image displayed on the display unit; obtaining a photometric error and a geometric error between the captured three-dimensional image and the output image; constructing a loss function for the photometric error and the geometric error; solving the loss function through an algorithm for solving three-dimensional to two-dimensional point pair motion to obtain a rotation matrix and a translation matrix; and correcting the output image according to the rotation matrix and the translation matrix to display the corrected output image on the display unit.

The invention relates to an intelligent ship water diversion method and system based on RTK and inertial navigation fusion, and the method comprises the steps: firstly, deploying and calibrating an RTK base station at a wharf commanding height, generating a differential correction in real time, and broadcasting the differential correction to a shipborne end; utilizing RTK surveying and mapping equipment to collect shoreline feature points, adopting a cubic spline interpolation algorithm to construct a continuous and smooth three-dimensional shoreline curve model, and fusing wharf geographic information to generate a shoreline visual map with geographic coordinates; establishing a ship coordinate system, converting inertial navigation attitude data into the coordinate system through a rotation matrix and a translation vector, fusing the inertial navigation attitude data with RTK position data, and outputting a high-precision ship pose; fusion data are transmitted through a 5G network, a shore end converts the fusion data into a local plane coordinate system and generates a real-time dynamic visual interface, the real-time dynamic visual interface is pushed to a tug terminal through an RTSP protocol, water diversion operation is assisted, high-precision perception, visual guidance and shore ship cooperation of the ship berthing process are achieved, and the water diversion safety and the intelligent level are improved.

The invention relates to a point cloud registration method and device, electronic equipment and a computer storage medium, and belongs to the technical field of point cloud registration, and the point cloud registration method comprises the steps: obtaining to-be-registered target point cloud data and source point cloud data, and constructing a rotation matrix and a translation matrix for registration of the target point cloud data and the source point cloud data; constructing an optimization function by taking parameters of the rotation matrix and the translation matrix as variables and taking the minimum Euclidean distance of corresponding points between the target point cloud data and the source point cloud data as a target; solving the optimization function by adopting a preset optimization algorithm to obtain a parameter optimal solution of the rotation matrix and the translation matrix, and constructing a target rotation matrix and a target translation matrix according to the parameter optimal solution, and registering the target point cloud data and the source point cloud data by using the target rotation matrix and the target translation matrix. According to the invention, the precision and stability of point cloud registration can be ensured.

The invention relates to a robot three-dimensional surface type measurement system and a parameter calibration method. The method comprises the following steps: defining a coordinate system of the measurement system; the three-dimensional surface type measuring head calibration sub-method comprises the following steps of: optimizing a sphere center coordinate of a calibration sphere in a three-dimensional surface type measuring head coordinate system, and translating a three-dimensional surface type measuring head to obtain a plurality of groups of point pairs between the three-dimensional surface type measuring head coordinate system and a robot base coordinate system; a multispectral confocal probe calibration sub-method: points on the surface of the sphere are converted to a robot end coordinate system through an optimized multispectral confocal probe conversion matrix and then are converted to a robot base coordinate system, so that accurate alignment of the multispectral confocal probe coordinate system and the robot base coordinate system is realized; and fusing the measurement data under the robot base coordinate system by adopting a combined probe data fusion algorithm. Compared with the prior art, the method has the advantages of eliminating system errors caused by installation of the combined measuring head, improving fusion precision and the like.

The invention discloses a novel symmetric iteration nearest point cloud registration calculation method for quality detection, and the calculation method comprises the steps: setting a point set and a point set in a three-dimensional space, carrying out the registration of a point set P and a point set Q, so as to solve a six-degree-of-freedom rigid body transformation matrix, and carrying out the registration of the point set P and the point set Q; the six-degree-of-freedom rigid body transformation matrix comprises a three-degree-of-freedom rotation matrix R and a three-degree-of-freedom translation vector t; a weighted point-surface model is constructed, and a symmetric iteration nearest point objective function based on weighted point-surface measurement and an adaptive robust loss function is constructed based on the weighted point-surface model; the calculation of the symmetric iteration nearest point objective function based on the weighted point-surface measurement and the adaptive robust loss function comprises the step of alternately executing a corresponding point updating step and a registration step until a convergence condition is met.

The invention provides an outdoor cross-modal robust positioning and navigation method for extreme severe weather, and relates to the field of online positioning and navigation of mobile robots. The method comprises the following steps: acquiring and preprocessing data; generating a path point set based on a CMR network, perfecting the path point set through local trajectory fitting and error optimization, and constructing a path point relative pose measurement-topology hybrid map; motion prior estimation is carried out based on Doppler velocity, effective matching prior estimation is generated in combination with LiDAR odometer information, cross-modal pose estimation is carried out through a CMR network, and a pure tracking strategy and PD controller path point tracking are adopted; and geometric and intensity alignment is carried out on the forward 4D millimeter wave radar point cloud and the omnidirectional 3D laser radar point cloud through a CMR network, a rotation matrix and a translation vector are output, and accurate positioning is completed. According to the invention, the sensing and positioning defects in extreme weather in the prior art are overcome, and the positioning precision and robustness are improved.

The invention relates to the technical field of SLAM, in particular to a dynamic environment robust positioning method based on improved ORB-SLAM2, and the method comprises the steps: obtaining RGB-D scene data containing an indoor moving object, and extracting ORB feature points described by FAST angular points and BRIEF descriptors; extracting feature points with unreliable heights according to geometric features of ORB feature points of adjacent frames; pixel analysis is carried out on the RGB-D scene data based on a Fast-SAM instance segmentation model, and a mask matrix containing environmental object space boundary information is generated; performing point-prompt extraction on the height unreliable feature points and the mask matrix to obtain a dynamic object mask; removing ORB feature points existing in the dynamic object mask to obtain a reliable feature point set; and calculating matching point pairs in the reliable feature point set to obtain an essential matrix and a corresponding rotation matrix and translation vector, and refining the pose based on a nonlinear optimization method.

The invention relates to the technical field of space calibration, in particular to a non-overlapping field-of-view dual-camera space calibration method based on an ArUco calibration board, and the method comprises the steps: carrying out the single-target calibration of two cameras; fixing the calibration plate at a plurality of preset postures and spatial positions, carrying out image acquisition, and obtaining an image frame of the calibration plate under the current spatial pose; extracting an ArUco marker ID and a two-dimensional angular point coordinate of the ArUco marker ID in the image frame, and recovering three-dimensional information of the calibration plate in each frame of image under a camera coordinate system; three-dimensional space points corresponding to the same marker ID in the two camera coordinate systems are recovered, and a plurality of space point pairs with the known corresponding relation are constructed; calculating a rotation matrix and a translation vector from the first camera coordinate system to the second camera coordinate system; according to the method, marker data in respective visual fields are collected under a public world coordinate system, and the unique coding characteristic of the marker data is combined, so that cross-visual-field space point pair matching and accurate transformation estimation are realized.

The invention provides a track correction method for a detection device in a pipeline based on coordinate transformation, and relates to the technical field of pipeline inertial surveying and mapping. The method comprises the following steps: firstly, acquiring uncorrected trajectory resolving data points C1, C2... CM and positioning points D1, D2... DN of a detector in a pipeline, and performing data alignment and segmentation; translating the resolving point and the positioning point, calculating a rotation angle between the resolving data in the translated correction interval and the positioning point interval, and determining a rotation matrix; and then solving and translating expansion coefficients of the positioning points and the corresponding calculation points in the correction interval, according to the sequence of the timestamps of the positioning points, until the correction of the calculation points corresponding to the DN-1 to DN sections is completed, and correcting the end point of the track to be overlapped with the actual detection end point so as to realize the correction of the full track.

The invention relates to the technical field of attitude estimation, in particular to an attitude estimation method in a magnetic interference environment, which comprises the following steps of: obtaining a conversion relation between an Euler angle and a quaternion; calculating the quaternion at the next sampling moment; respectively solving a first state transition matrix, a first process noise matrix and a first prior covariance according to the first state equation; respectively solving a second state transition matrix, a second process noise matrix and a second prior covariance according to a second state equation; elements in the nb-series rotation matrix are used as observed quantities of state variables in the parameter-series rotation matrix, a corresponding Kalman gain is calculated, and a Jacobian matrix is designed by using the observed quantities; calculating an observation noise covariance matrix by using the Jacobian matrix; updating the Kalman gain by using the observation noise covariance matrix; and updating the state equation and the posterior covariance by using the updated Kalman gain and the observed quantity. The method solves the problem of how to prevent the calculation of the roll angle and the pitch angle from being influenced by magnetic interference when the magnetic interference exists.

The invention provides a shipborne two-axis stable turntable gyro drift compensation method, which comprises the following steps: calculating a rotation matrix from a frame coordinate system to a ship deck coordinate system, calculating a rotation matrix from the ship deck coordinate system to a navigation system, calculating a rotation matrix from the frame coordinate system to the navigation system, and obtaining the orientation and pitching pointing angle of a frame in the navigation system. A platform frame pointing direction and pitching inertia drift value is stabilized, drift estimation values are sent to the input end of a rotary table direction and pitching axis angular rate control loop, reverse motion of a direction and pitching axis motor is controlled, and gyroscopic drift is corrected; and returning to the starting step until the real-time compensation of the gyroscopic drift is completed. The method can be used for correcting the gyroscopic drift in real time, keeping the pointing inertia stability of the turntable frame, improving the gyroscopic drift compensation efficiency and reducing the manual dependence. The stability precision of the rotary table is improved, and the intelligence and the operation convenience of rotary table equipment are enhanced. And the working intensity of equipment operators is reduced.

The invention relates to a line laser contourgraph data consistency evaluation method and device which are applied to the field of optical precision measurement, and the method comprises the steps: obtaining point cloud data generated when a line laser contourgraph scans a measured plane of a measured target object; determining a spatial relationship between the measured plane and an ideal horizontal plane based on the point cloud data; determining an ideal horizontal plane based on an optical axis formed by a line laser profiler; constructing a rotation matrix between the original coordinate system of the point cloud data and the coordinate system of the ideal horizontal plane according to the spatial relationship between the measured plane and the ideal horizontal plane; correcting the point coordinate of the original laser line in the point cloud data through the rotation matrix to obtain the corrected point coordinate of the laser line; and evaluating the data consistency of the line laser contourgraph based on the corrected point coordinates of the laser lines. According to the invention, the problem that the accuracy of the consistency evaluation of the overall line laser data measured by the line laser contourgraph needs to be improved is solved.

Disclosed in the present invention is a parameterized-information-based method for transferring a rebar BIM model to engineering construction. The method comprises: traversing a BIM model structure tree to acquire a rebar model, and extracting UDF data of rebars in the lowest-level child nodes; parsing the UDF data of each rebar, acquiring and traversing points in a rebar centerline C1, acquiring the coordinates of any point, and calculating the tangent vectors and convexity of the point; using a parsing result to calculate an identification code h of each rebar, marking an unmarked rebar with a hash value h appearring for the first time as Reference, and then marking unmarked rebars having the same hash value as Instance; calculating an offset matrix between the Reference rebar and the Instance rebars thereof, wherein the offset matrix comprises a rotation matrix and a calculated translation vector; and outputting, in an XML format, the obtained data of the rebars and parameters directly read from a UDF.

The invention discloses an optical satellite drift angle accurate calculation and attitude correction method and system, and relates to the technical field of satellite attitude control, and the method comprises the steps: calculating a prime unitary circle curvature radius according to a WGS84 ellipsoid parameter, and converting the geodetic coordinate of a ground target point into an ECEF rectangular coordinate; calculating Julian days based on UTC time, determining an age difference angle and a nutation angle, and converting an ECEF coordinate into a J2000 coordinate; calculating the projection of the earth rotation angular velocity in a J2000 coordinate system, and determining a relative velocity vector; determining an orthogonalized body coordinate system in combination with a unit vector from the target satellite to the ground target point; and projecting the relative velocity vector to a body coordinate system, calculating a drift angle and a double-rotation-sequence Euler angle, and correcting a real-time execution attitude by rotating a matrix around a Z axis. According to the method, high-precision image motion compensation can be realized, the imaging quality of a high-resolution optical satellite in a complex task scene is improved, and a technical foundation is laid for wide application of sub-meter remote sensing images.

The invention relates to the field of industrial automatic detection, in particular to an industrial component point cloud identification method and system. The method comprises the following steps: collecting multi-frame point cloud data, extracting a mold table region point set and fitting a reference plane; identifying an effective point set based on the reference plane, establishing a local coordinate system and calculating a sensor rotation matrix; generating a correction point cloud through the rotation matrix calibration point cloud; dividing the corrected point cloud into grids, and detecting and expanding a contour point set; performing straight line fitting on the contour point set to determine boundary lines and angular points; comparing the angular point forming region with a preset feature to eliminate anomalies; the connecting corner points form a closed contour. The method solves the problems that an existing point cloud processing technology depends on a static environment and is weak in dynamic interference resistance, contour extraction is greatly influenced by noise, and key point connection is prone to errors.

The invention discloses an equipment attitude automatic correction method and device and an optical terminal intensity instrument, the equipment attitude automatic correction method is applied to a preset monitoring terminal comprising a triaxial MEMS accelerometer and a magnetometer, and the method comprises the following steps: collecting acceleration and magnetometer data; calculating acceleration stable three-axis offset; calculating roll and pitch angles and determining a horizontal plane; positioning magnetic north and calculating a magnetic north azimuth angle; calculating a magnetic declination angle and a yaw angle by combining longitude and latitude; generating a rotation matrix and converting a coordinate system; judging angle change and updating the matrix; and completing calibration and attitude stabilization. According to the technical scheme provided by the invention, the monitoring terminal equipment can be ensured to automatically and accurately adjust and stably maintain the attitude after being installed, so that the effective operation of the earthquake monitoring and early warning system is ensured, and the earthquake disaster prevention and flooding earthquake (vibration) monitoring performance is improved.

The invention relates to the technical field of photoelectric detection and radars, in particular to a calibration method, system and device for a radar and a laser anti-collision device and a medium, and aims to track and lock the same dynamic non-cooperative target through the laser anti-collision device and the phased array radar. Synchronously acquiring spherical coordinate observation data of the dynamic targets in the public view field under respective coordinate systems; and after the spherical coordinates are converted into rectangular coordinates, calculating a point set centroid, constructing a covariance matrix and performing singular value decomposition based on a rigid body transformation model, and directly solving a rotation matrix and a translation vector from a radar coordinate system to a laser anti-equipment-free coordinate system, thereby completing calibration. No external absolute coordinate reference is needed, only relative observation data of equipment is utilized, and the method has the advantages of being rapid in deployment, high in environmental adaptability, low in cost and high in calibration speed. The problems that in the prior art, a calibration system depends on RTK or a high-precision map, the environmental adaptability is poor, and the deployment requirement is high are solved.

The invention relates to the technical field of digital supervision, in particular to a digital supervision method and system for a power construction project, and the method comprises the following steps: collecting a surface three-dimensional coordinate point clustering calculation component point cloud cluster, extracting an actual measurement central axis through employing a random sampling consistency algorithm, comparing a design axis net coordinate, calculating an axis net deviation value, and calculating the point cloud cluster. And constructing an axis network topological structure chart, traversing and comparing deviation values, analyzing and marking a primary deviation source, and performing recursive calculation to judge a deviation conduction path. According to the method, three-dimensional coordinate point clusters are collected, actual measurement central axes of components are calculated to restore geometric morphology, a space translation vector and a rotation matrix are calculated by comparing with a designed axis net, an objective deviation value is quantified, manual subjectivity is eliminated, meanwhile, an axis net topological structure diagram is constructed through component connection, and recursive calculation is carried out in combination with the deviation value, so that the precision of the axis net topological structure diagram is improved. A deviation source is effectively analyzed and marked, a deviation conduction path is judged, and closed-loop management from deviation discovery to source diagnosis is achieved.

The application discloses a kind of mobile video and real scene three-dimensional fast fusion method, comprising the following steps, key frame is selected according to predetermined frequency, and its rotation matrix is calculated based on the pose information corresponding to key frame;Determine whether the module length of angular velocity vector corresponding to non-key frame is greater than angular velocity threshold value;If not, the rotation matrix of adjacent key frame is directly selected for the non-key frame, and the position is updated according to the moving speed;If yes, the rotation compensation matrix corresponding to the non-key frame is calculated according to the angular velocity vector and integrated with the rotation matrix of adjacent key frame to obtain the rotation matrix of the non-key frame, while updating the position according to the moving speed.The application introduces non-key frame rotation matrix dynamic reuse and micro compensation mechanism, significantly reduces the average calculation complexity of system, greatly improves the response speed and frame rate of overall fusion processing, meets the demand of high real-time requirement application scene such as remote command.

The invention discloses a non-overlapping-area multi-camera attitude calibration method, and belongs to the technical field of computer vision. According to the method, a checkerboard perpendicular to the gravity direction is hung in front of each camera, and images are independently collected at different positions under the static condition; solving a rotation matrix from the camera to the checkerboard coordinate system at each position through a PnP algorithm, and projecting a gravity direction unit vector in the checkerboard coordinate system to each camera coordinate system to obtain a gravity projection coordinate; an error minimization model is constructed based on the consistency of gravity projections between the two cameras, and a relative rotation matrix between every two cameras is solved through singular value decomposition in combination with orthogonality and determinant constraints. According to the method, the gravity projection vector is extracted from the image independently acquired by each camera by utilizing the physical priori of the vertical suspension checkerboard and the gravity direction, the multi-camera relative attitude calibration method without common view, synchronization and auxiliary sensors is constructed, and rapid, low-cost and high-universality external parameter calibration is realized.

The invention discloses a field programmable gate array (FPGA) implementation method for Hermite matrix eigenvalue decomposition, which comprises the following steps of: performing real number processing on a Hermite matrix according to a corresponding relationship between the Hermite matrix and eigenvalues and eigenvectors; grouping the dimension real matrix obtained by the real number processing; calculating rotation matrixes of diagonal units and non-diagonal units; performing Jacobi rotation operation on the diagonal units and the non-diagonal units, and updating the feature vector matrix according to a rotation matrix; after a group of Jacobi rotation is completed, data exchange is carried out according to grouping of a parallel Jacobi algorithm; and multi-stage cleaning can be carried out according to actual requirements. According to the method, a parallel Jacobi algorithm is selected, a series of matrix rotation is adopted, the matrix is converted into a diagonal matrix, and therefore the eigenvalue and the eigenvector of the matrix are calculated. According to the method, the parallel computing advantages of the FPGA and the Jacobi algorithm are fully utilized, and the real-time performance of the algorithm is effectively improved.