902 results about "Visually guided" patented technology

The invention belongs to the technical field of mechanical arm automatic grabbing, and particularly relates to a 3D visual guidance mechanical arm grabbing method for irregular objects. Comprising the following steps that (1) a 3D visual guidance mechanical arm grabbing system is built, specifically, a 3D camera based on line structured light is adopted to guide a mechanical arm, the mechanical arm is a visual flexible six-axis mechanical arm, and after the mechanical arm completes accurate grabbing of all objects and carries out placement according to requirements, it is regarded that the grabbing task is successfully completed; and the camera in the 3D camera is calibrated, and the calibration of the camera is realized by calling a CalibrateCamera function in the OpenCV library. Through mutual cooperation of the 3D camera and the mechanical arm, intelligent grabbing of irregular objects such as industrial parts is achieved, more accurate grabbing operation is carried out according to the actual application situation, and the robot does not depend on training of three-dimensional point cloud samples. And the 3D camera can accurately obtain external information, and the grabbing requirement of the mechanical arm is met.

The invention discloses a grabbing control system for robot visual guidance, and belongs to the technical field of grabbing control systems.The grabbing control system comprises a visual perception module used for collecting workpiece images, extracting workpiece feature information and calculating accurate coordinates of workpieces in space; the robot main body module is used for receiving a system instruction to drive a carrier to move to a target position; the grabbing execution module is used for being in contact with the workpiece, grabbing the workpiece stably and transferring the workpiece to a designated position to be placed without damage; the system integration module is used for guaranteeing the safety, operability and stability of the feeding and discharging process; according to the system, workpiece information can be accurately collected, the posture of the grabbing execution end is analyzed based on the workpiece position, the grabbing posture is corrected in real time according to the grabbing dynamic state, and the workpiece grabbing precision and stability are improved.

The invention discloses a printed circuit board defect detection method and system based on cross-modal prompt learning and visual guidance, and the method comprises the following steps: obtaining a defect-free PCB image sample, and obtaining a training data set; constructing an initial printed circuit board detection model; training the initial printed circuit board detection model by using the training data set to obtain a printed circuit board detection model; and completing the defect detection of the printed circuit board by using the printed circuit board detection model. According to the method, a synthetic anomaly generation strategy based on a PCB structure and physical prior is provided, a two-channel storage library mechanism is introduced, and a synthetic anomaly sample most valuable for model training is screened out through a difficult case mining strategy, so that visual anomaly mode guidance is provided. According to the method, a double-constraint alignment optimization strategy combining comparison loss and triple loss is adopted, the mapping relation between vision and text features is adjusted, and cross-modal alignment and clear normal / abnormal boundaries are achieved. According to the method provided by the invention, the accuracy, the robustness and the generalization capability of PCB defect detection under the data sparse condition can be remarkably improved.

The invention discloses a sow vaccine injection method based on deep learning and machine vision. The sow vaccine injection method comprises the following steps that 1, an AGV chassis is controlled to arrive at a work station according to an instruction; 2, visually recognizing the posture of the sow to be injected, and if the recognition result is that the sow to be injected is in a non-standing posture, driving up the sow to be injected with manual assistance; if the recognition result is a standing posture, visually guiding the mechanical arm to move to a photographing position; 3, the RGBD camera shoots in real time to obtain the injection position and distance of the sow to be injected, and the mechanical arm moves to position the injection clamp to the pre-injection position; 4, injection is completed, and an injection result is recorded; the invention further discloses a sow vaccine injection system based on deep learning and machine vision. Manual operation is replaced by mechanical operation, automation of the vaccine injection process is achieved, direct contact between personnel and sows is reduced, and the risk of infectious disease transmission is reduced.

Systems and methods are provided for facilitating an interactive artificial-reality activity. A method includes, after a user of a head-wearable device has opted-in to using an artificial-reality application to facilitate connecting with other participating users, determining, based on user-specific suggestion criteria, that a suggested user is located in an approved common space with the user and has opted-in to use the artificial-reality application. The method includes causing the head-wearable device to present an user interface (UI) element for linking the suggested user and the user. Upon the user selecting the UI element for linking the suggested user with the user, the method includes automatically causing the head-wearable device to provide visual-guidance UI elements to navigate the user to an interactive-activity location where the user and the suggested user will perform an artificial-reality activity while also displaying information about the artificial-reality activity to be performed.

The invention relates to a tunnel illumination control method considering visual adaptability of a driver, and belongs to the technical field of tunnel illumination control, and the method comprises the following steps: S1, employing a volume scattering point location method to obtain visual adaptability parameters of visual adaptation states of all segments in a tunnel; s2, dynamically constructing a predictive visual adaptation model of the driver group based on the visual adaptation parameters, and outputting expected visual states of the drivers according to the predictive visual adaptation model; s3, according to the expected visual state, a parameter control mechanism is adopted to control target illumination parameters of all the sections of the tunnel; s4, according to the target lighting parameters, the working state of lighting equipment in a corresponding section in the tunnel is regulated and controlled, so that the light environment in the tunnel is matched with the dynamic visual adaptability of a driver, and safe visual guidance is achieved; the method has the beneficial effects that the target illumination parameters of all the sections of the tunnel are controlled by adopting a parameter control mechanism according to the expected visual state according to the target illumination parameters.

The invention provides a movable flexible docking platform, method and equipment based on visual guidance and a storage medium, and relates to the field of automatic auxiliary assembly. The docking platform comprises an AGV trolley, a six-degree-of-freedom platform erected in the middle of the upper portion of the AGV trolley, and a binocular vision system erected on the rear side of the upper portion of the AGV trolley. The binocular vision system provides real-time vision guidance in the advancing process of the AGV; a butt joint workpiece A is placed on a six-degree-of-freedom platform, and a butt joint workpiece B which has an assembly relation with the butt joint workpiece A is placed on a working table at a target position; and the AGV transports the butt joint workpiece A to the target position, and butt joint of the butt joint workpiece A and the butt joint workpiece B is completed. According to the invention, the six-degree-of-freedom parallel platform is arranged on the AGV trolley, so that the pose fine adjustment of the assembled workpiece is realized, the pose of the workpiece can be continuously adjusted in the transportation process to keep balance, and the workpiece transportation and high-precision butt joint can be realized.

The invention belongs to the technical field of medical image three-dimensional reconstruction, and discloses an abdominal cavity reconstruction and focus positioning method based on a binocular endoscope, which comprises the following steps of: calibrating and correcting internal reference of the binocular endoscope; inputting the trained depth estimation network to obtain a disparity map and processing the disparity map into a picture according to frames; the luminosity error is minimized through a coarse-to-fine pyramid optimization method, and a transformation matrix of the endoscope pose between two continuous frames is calculated through nonlinear iterative optimization; light beam adjustment optimization is carried out on the motion trail of the endoscope, a depth map is superposed, outliers are removed, and three-dimensional reconstruction of the abdominal cavity tissue is achieved; recognizing a focus, extracting three-dimensional information according to the disparity map, and visually guiding the operation arm to move to a focus point in combination with a calibrated hand-eye matrix so as to realize positioning. According to the method, rapid and dense three-dimensional reconstruction of the peritoneal environment before the operation and accurate focus positioning based on visual guidance during the operation are realized, the accuracy of motion track estimation of the endoscope is improved, and autonomous development of the surgical robot is expected to be promoted.

The invention relates to the technical field of image analysis, in particular to an automatic marking robot calibration method based on visual guidance, which comprises the following steps of: establishing an image set comprising different resolution levels based on operation site image data acquired by a marking robot, and performing corner detection and straight line segment detection on each level image in parallel. According to the method, through a parallel detection mechanism of a multi-resolution hierarchical image set, angular point and straight line segment features under different scales are synchronously extracted, and a multi-scale feature point set with high robustness is constructed in combination with cross-hierarchical coordinate stability measurement and response intensity quantification. And performing dynamic screening and grouping association on the feature points based on a preset geometric constraint condition, eliminating noise interference and false detection features, and generating a candidate calibration structure set with spatial consistency. Weighted contribution value fitting is adopted, cross-scale stability and detection confidence of feature points are integrated, and geometric accuracy and anti-interference capability of calibration reference point coordinates are improved.

The invention discloses a robust visual constraint control method and system for a mechanical arm and computer equipment, and the method comprises the steps: building an overall dynamic model of a visual servo system through combining a mechanical arm dynamic model, a visual servo kinematics model and a hand-eye calibration relation between a camera and the mechanical arm; in combination with a visual servo kinematic model, by designing a time-varying asymmetric control barrier function, a constraint satisfaction condition for constraining a visual servo characteristic error within a preset range is obtained, and an optimal visual servo speed controller is designed, and in combination with a robot dynamical model, an optimal visual servo speed controller is designed. A constraint satisfaction condition for constraining joint angular velocity within a preset range is obtained through a time-varying asymmetric control obstacle function, an optimal torque controller is designed in combination with a visual servo characteristic error constraint satisfaction condition, a torque control signal meeting performance constraint is obtained in combination with quadratic programming, and the robot is driven to reach an expected characteristic position. The success rate of a visual servo task is improved, and high-precision visual guide assembly work of the mechanical arm is achieved.

The invention relates to the technical field of electromyographic signal monitoring, and discloses a guided monitoring method and system based on a wireless surface electromyographic analysis feedback instrument. The method comprises the following steps: acquiring electromyographic signal time sequence data and limb movement track space coordinate information when a target muscle group moves through a multi-channel wireless surface electromyographic sensor; muscle activation intensity and fatigue change features are extracted, a joint activity angle change sequence is calculated, and a muscle-joint collaborative activity feature matrix is generated through space-time alignment fusion; analyzing signal transduction delay and amplitude matching degree in the matrix, and evaluating the nerve driving coordination level; according to the deviation from the preset standard mode, generating a real-time biological feedback signal containing an action correction instruction and a muscle activation intensity adjustment parameter; and converting into a tactile vibration mode and a visual guidance mark to be output. According to the method, synchronous acquisition and fusion analysis of multi-dimensional motion information are realized, and visual guidance is provided through multi-modal feedback.

Devices and methods for performing an interventional vascular procedure with visual guidance using one or more optical head mounted displays are disclosed. Devices and methods for compensating the display of an optical head mounted display for cardiac and / or respiratory motion are disclosed.

The invention belongs to the technical field of ablation puncture navigation, and particularly relates to an ablation puncture surgery navigation system under AI visual guidance. Through cooperative work of the phase monitoring module, the channel construction module, the needle moving control module, the displacement prediction module and the feedback control module, an intelligent surgical navigation system is constructed, breathing phase information and multi-modal medical image data of a patient can be obtained in real time, and therefore a safe and optimized needle moving path is accurately planned, and the operation accuracy is improved. Meanwhile, through real-time monitoring and quantitative evaluation of parameters such as tissue deformation and pressure distribution in the needle moving process, potential operation risks can be found and corrected in time, smooth operation is ensured, in addition, the system can dynamically adjust the needle moving path and the puncture angle according to the real-time breathing state of a patient, and the operation safety is improved. The accuracy and the safety of the operation are further improved, so that intelligent management and personalized treatment in the ablation puncture operation process are realized.

The invention belongs to the technical field of steel structure damage repair. The invention provides a large steel structure corrosion damage integrated repairing robot and a control method. The robot comprises a robot body, and a force control servo motor, an automatic polishing module, a damage identification camera, an air compression pump, a paint storage box, a control terminal, a magnetic adsorption module, a pipeline climbing module, a paint film thickness measuring module and an automatic paint spraying module which are arranged on the robot body. A robot compliance control strategy integrating force feedback, visual guidance and other modes is provided, dynamic parameter adjustment is combined, efficient and compliance control over the rust removal and spraying process of the repairing robot is achieved, the high efficiency and stability of the corrosion damage repairing process are ensured, and the corrosion damage repairing efficiency is improved. And flexible movement and efficient operation of the integrated repairing robot in a complex space structure are achieved.

The invention belongs to the technical field of machine vision positioning and guiding, and discloses a nanocrystalline magnetism isolating sheet vision guiding laser deburring device and application thereof, and the nanocrystalline magnetism isolating sheet vision guiding laser deburring device comprises an image acquisition module, an image preprocessing module, a central control module, a laser module, a positioning module, a collection module, a data analysis module and a display module; according to the visual guidance technology, an advanced visual recognition system is introduced, the burr position is accurately positioned by monitoring the surface state of a workpiece in real time, and therefore the more intelligent laser deburring process is achieved. And laser parameter optimization: parameters such as wavelength, power and pulse frequency of laser are optimized according to different materials and burr types, so that the optimal deburring effect is achieved, and meanwhile, the completeness of the workpiece is ensured. And in the laser deburring process, environment-friendly materials and technologies are adopted, the influence on the environment is reduced, and the safety in the operation process is enhanced.

The invention discloses a tomato stem picking point attitude estimation method, and relates to a computer vision processing technology. The method comprises the following steps: detecting a long-range directional frame target, acquiring a color flow by a depth camera, and detecting position information and shielding conditions of fruits and fruit stems through a directional frame; visual guidance: matching fruit stems based on tomato growth constraint conditions, and visually guiding the mobile platform and the mechanical arm to move in a coupling manner until the fruit stems are observed when the fruit stems are not matched; detecting close-range key points, regulating and controlling a mechanical arm to a close-range observation position, identifying two points of a main stem and three points of a fruit stem through a key point detection model, and extracting point clouds; performing point cloud data processing, removing point cloud noise through point cloud filtering, and performing adaptive compensation on key points with depth anomaly by using a neighborhood mean value; calculating picking poses, and establishing the picking poses of the fruit stem shear points according to the three-dimensional information of the five key points; according to the method, the problem of tomato shielding in a greenhouse complex scene can be effectively solved, and the fruit stem shearing point pose is obtained.

The invention relates to a text knowledge enhanced scene graph generation method, and belongs to the field of computational vision. The method comprises the following steps: extracting text features of text information; extracting visual features and entity labels of the scene image, and combining the extracted visual features into paired entity pair features; introducing entity pair feature guidance to generate visual guidance text feature representation, so that the extracted text features are associated with visual entities; obtaining refined entity enhancement features and entity-to-visual predicate features based on the visual features and the entity tags; performing cross-modal alignment on the visual guidance text features and the entity pair visual predicate features to obtain graphical multi-modal feature representation; and inputting the multi-modal feature representation and the entity enhancement feature into a multi-layer perceptron for prediction to obtain prediction output of the entity pair and the entity pair relationship. According to the invention, the accuracy of entity object prediction and entity relationship prediction in the scene graph generation process can be improved.

The invention discloses a modular visual guidance robot feeding and discharging device, and relates to the technical field of robot-assisted feeding and discharging equipment, and the modular visual guidance robot feeding and discharging device comprises a visual module which is installed on a production line and is used for identifying the position of a workpiece and outputting coordinate information; the manipulator module is mounted on the production line, and a clamp connecting mechanism and an end effector are arranged at the tail end of the manipulator module; the clamp module is installed at the tail end of the mechanical arm module through a clamp connecting mechanism, and the clamp module is electrically connected with the tail end executor and used for grabbing a workpiece; and the control system module is electrically connected with the vision module, the manipulator module and the end effector and is used for controlling the manipulator module to act according to the coordinate information output by the vision module and controlling the clamp module to act through the end effector. The production requirements of diversified products on different production lines can be met, and the universality and adaptability of equipment are improved.

The invention relates to the technical field of home appliance maintenance, in particular to a cross-brand home appliance maintenance knowledge sharing system and method based on federated learning, a multi-mode fault data collection and intelligent maintenance system integrates image, text, fault phenomena and multi-mode instruction data collection, and after pre-processing, the multi-mode fault data collection and intelligent maintenance system is established. A feature decoupling model is established through a maintenance knowledge analysis module, a cross-brand maintenance knowledge base stores general and specific fault information and assists knowledge migration, a federal learning training module adopts differential privacy homomorphic encryption, data privacy is protected, gradient aggregation cooperative training is achieved, a reality maintenance guidance terminal is augmented to visually guide maintenance, the efficiency is improved, and the maintenance efficiency is improved. The preventive maintenance module calculates the equipment maintenance cycle, generates a prevention scheme, and reduces the failure rate and cost. The system significantly improves the maintenance accuracy, rapidly fuses into a new brand, realizes knowledge sharing and utilization, and brings revolutionary revolutions to the household appliance maintenance industry.

The invention discloses an apple recognition positioning and obstacle avoidance method based on zero samples and visual guidance. An improved YOLOV8 model is used for recognizing unknown category objects in a picking scene; semantic embedding of apples and branches is constructed by combining an external knowledge base Word2Vec, and unknown category objects in a picking scene are identified by using a zero sample learning method; constructing three-dimensional point cloud data of a fruit tree where an identification result is located, carrying out iterative convergence point cloud denoising by adopting a convex set constrained by an alpha norm, and updating point cloud coordinates; performing point cloud segmentation by using a potential energy function segmentation model; obtaining three-dimensional information of the apple and the obstacle through three-dimensional reconstruction of the point cloud feature information; extracting three-dimensional space position data of the branches at different time points to form a time sequence data set, and predicting the motion trail of the branches by using LSTM (Long Short Term Memory); through branch coordinate data of the point cloud and the LSTM, predicting a motion track of the branch, and utilizing a geometric collision detection method to evaluate and predict a collision risk between a robot end effector and the branch; and planning an optimal obstacle avoidance path by using an A * algorithm.

The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly generating modified digital images utilizing a guided inpainting approach that implements a patch match model informed by a deep visual guide. In particular, the disclosed systems can utilize a visual guide algorithm to automatically generate guidance maps to help identify replacement pixels for inpainting regions of digital images utilizing a patch match model. For example, the disclosed systems can generate guidance maps in the form of structure maps, depth maps, or segmentation maps that respectively indicate the structure, depth, or segmentation of different portions of digital images. Additionally, the disclosed systems can implement a patch match model to identify replacement pixels for filling regions of digital images according to the structure, depth, and / or segmentation of the digital images.

The invention relates to the technical field of artificial intelligence, and discloses a vision-guided automatic sorting and deviation rectifying method and system.The vision-guided automatic sorting and deviation rectifying system comprises a vision parameter processing module, a sorting strategy decision module and a deviation rectifying execution control module, a real-time judgment mechanism of dynamic and static resolution differences is established by setting a resolution collaborative correction end, and the deviation rectifying execution control module is established; a self-adaptive interpolation algorithm is adopted to adjust visual feature data, so that the system can eliminate imaging resolution deviation caused by ambient light and transmission vibration, the acquisition accuracy of material surface texture features is ensured, sorting identification errors caused by projection chromatic aberration are avoided, the environmental adaptability of the visual guidance system is improved, and the visual guidance system is more accurate in image quality. The position and posture coupling analysis end is arranged, the dynamic matching degree of the position and posture offset of the materials and the motion trail of the mechanical arm is monitored in real time, the grabbing angle offset is automatically corrected through a space coordinate compensation mechanism, and it is guaranteed that the relative space position of an end effector and the materials is in the optimal grabbing state all the time.

The invention discloses a visual guidance positioning system and method in the machine tool flexible shaft assembling process, and relates to the technical field of flexible shaft assembling, a visual system obtains three-dimensional pose data of the tail end of a flexible shaft and a target connector, a six-dimensional force sensor is combined to monitor contact force / torque in real time, the limitation of a single sensor is broken through, and the blind area of the single sensor is solved; visual and force sense coordinate systems are aligned in real time, and coordinate drifting caused by movement of the mechanical arm is eliminated; generating an approximation path based on the pose difference, introducing a compensation amount formula, inhibiting oscillation in combination with an attenuation coefficient, and improving the path smoothness; when the contact force exceeds the dynamic threshold value or the pose difference converges, path correction is automatically triggered, overload damage is avoided, and the assembly damage rate is effectively reduced. The method breaks through the limitation of traditional static path planning, has high precision, high reliability and complex working condition adaptability, and is especially suitable for precise instrument and heavy load machinery assembly scenes.

The invention discloses a control method and system based on a self-positioning helicopter field navigation aid lamp and a medium, and relates to the technical field of aircraft landing auxiliary devices.The method comprises the steps that environment information, unmanned aerial vehicle state information and navigation aid lamp layout information are obtained, and initial guiding parameters are determined; calculating a visual guidance signal parameter based on the position condition of the unmanned aerial vehicle relative to each navigation aid lamp and the initial guidance parameter; determining a navigation aid lamp control scheme according to the visual guidance signal parameters and the initial guidance parameters, and sending a lighting starting instruction to a plurality of corresponding navigation aid lamps; acquiring environment feedback information from each navigation aid lamp area, and calculating an environment difference value; if the environment difference value exceeds a preset environment change threshold range, triggering an environment adaptability adjustment instruction; and calculating corresponding navigation-aid lamp adjusting parameters and sending an illumination adjusting instruction to the corresponding navigation-aid lamp area. According to the invention, the safety and reliability of the unmanned aerial vehicle under a complex or emergency landing condition are improved.

Aspects of the disclosure provide methods and apparatuses for mesh processing. In some examples, a method for mesh processing includes receiving an input mesh that is bounded in a bounding box. The input mesh is formed of a first plurality of vertices and a first plurality of faces that connects the first plurality of vertices. The method further includes calculating at least a first visual measure for one or more faces in the first plurality of faces. At least the first visual measure for a face is calculated according to a number of valid rays respectively at a plurality of sampling positions of the face, a valid ray at a sampling position is a ray that is traced from the sampling position to the bounding box. The method also includes performing adjustments to the input mesh to generate a repaired mesh according to at least the first visual measure.

The invention provides a visual optimization method, medium and system for a welding robot for a floating ship plate of an oil storage tank, and belongs to the technical field of electric digital data processing.The method comprises the steps that key information of the welding process is comprehensively obtained and deeply analyzed through a multi-dimensional and multi-scale data collection and decomposition strategy, and the welding process is optimized; comprising complex data such as welding seam images, robot poses, current, voltage, oil mist concentration and floating ship plate vibration frequency. By constructing an image interference compensation model and a pose compensation model based on multivariate decomposition, accurate enhancement of weld image quality and dynamic correction of robot poses are achieved, and interference factors and system errors in the welding process are effectively eliminated. Finally, the optimized high-quality image data and accurate pose data serve as input of a machine vision module, the vision guiding precision of the oil storage tank floating ship plate welding robot is remarkably improved, and the technical problem that the detection reliability is seriously reduced due to the fact that a vision system of the welding robot is often affected by many interference factors is solved.

The invention provides a laser shock thermal imaging composite coating spraying method and device based on visual guidance, and the method comprises the steps: generating a transient thermal response on the surface of a coating through laser shock, and collecting the temperature field distribution of the surface of the coating in real time through a high-speed thermal infrared imager; the crack position is identified according to the temperature field distribution of the coating surface, thermal response characteristics of a crack area on the coating surface are obtained, and the thermal response characteristics comprise real-time temperature and temperature gradient data of the crack area; establishing a nonlinear mapping model between the crack thermal response characteristics and the crack size, training by adopting a deep neural network, inputting the thermal response characteristics subjected to data preprocessing into the trained deep neural network, and predicting the size and the spatial position of the crack in real time; and target spraying parameters are set based on predicted crack size information, spraying process parameters are adjusted in real time through a self-feedback PID control system, the material ratio is dynamically adjusted through a multi-channel powder feeding system, and the gradient composite coating is formed.

The invention provides a gear forging control method based on visual guidance, relates to the field of image processing, and is applied to gear forging quality control in the aviation field. The control method specifically comprises the following steps: shooting a gear panoramic image by using a camera; performing image analysis on the panoramic image to obtain a multi-region spliced image; respectively inputting the multi-region spliced image into a region quality detection model to obtain a multi-region quality result; the gear quality report is generated according to the multi-region quality result, the forging equipment is controlled to reprocess, and each region of the gear is independently detected and analyzed, so that refined quality control can be performed on each part of the gear, the overall quality of the gear is enhanced, and the performance and reliability of the gear in an extreme environment are improved.

The invention discloses a welding robot system based on visual guidance, which comprises an artificial potential field welding robot path planning algorithm, the artificial potential field welding robot path planning algorithm is combined with an ant colony algorithm, and the artificial potential field welding robot path planning algorithm and the ant colony algorithm comprise artificial potential field function simulation, ant colony algorithm simulation and path search, pruning strategy and path optimization mechanism. And the step operation system (GBOS) comprises three-dimensional model importing and welding seam positioning. According to the method, the welding path planning technology of the ant colony algorithm of the artificial potential field function is fused, the welding robot is guided to avoid obstacles by simulating attraction force and repulsive force, the optimal path can be accurately recognized, the coverage rate of the searched path to the environment can reach 74.63%, a good convergence curve can be obtained, and after the pruning strategy is introduced, the optimal path can be obtained. According to the method, the path can be optimized, redundant broken lines or path sections are removed, and optimization of the path length and complexity is achieved, so that the welding time and cost are reduced, and the welding efficiency is improved.

The invention relates to the technical field of image processing, in particular to a vacuum printed PCB precise feeding method and system guided by machine vision, and the method comprises the steps: obtaining the feature points of a to-be-positioned PCB image and the feature points of a real PCB image; calculating the credibility of each feature point of the real PCB image, screening out a target feature point according to the credibility, and matching the target feature point with the feature points of the to-be-positioned PCB image to complete positioning and feeding of the real PCB image; wherein the calculation of the credibility of the feature points comprises the step of clustering the feature points of the real PCB image to obtain a plurality of clusters. According to the invention, by screening the feature points of the real PCB image, it is ensured that the feature points are more accurate and stable, mismatching is reduced, and the accuracy of image matching is improved; and some redundant or unimportant feature points can be removed, so that the workload of subsequent matching and calculation is reduced.