1221 results about "Visual system" patented technology

A dynamic vision system includes a variable focus liquid lens optical assembly. The dynamic vision system includes a variable lighting assembly. The dynamic vision system includes a control system configured to adjust one or more optical parameters and data collected from the variable focus liquid lens optical assembly in real time. The dynamic vision system includes a control system configured to adjust the variable lighting assembly. The dynamic vision system includes a processing system that dynamically learns on a training set of outcomes, parameters, and data collected from the variable focus liquid lens optical assembly to train a set of machine learning models to control the variable focus liquid lens optical assembly to optimize collection of data for processing by the set of machine learning models.

The invention discloses a full-automatic grinding method and system for steering knuckle flash based on 3D vision, and relates to the technical field of casting post-processing automation. A trimming-free direct polishing process is innovatively provided, a casting is scanned in real time through a high-precision 3D visual system, a flash space molded line is accurately captured, and one-key calibration of a camera, automatic generation and dynamic simulation of a flash path, multi-tool intelligent switching and self-adaptive adjustment of residual height are achieved in combination with self-developed off-line programming software. According to the system, a robot is adopted for grabbing workpieces to cooperate with a fixed type multi-cutter work station, a disordered feeding technology is integrated for 2D / 3D visual guiding grabbing, workpiece deformation and die difference are effectively dealt with, and flash residues are thoroughly eliminated. The method is characterized in that visual scanning, path planning and execution control are seamlessly fused, the dependence of traditional automatic grinding on the trimming process is broken through, the yield and efficiency are remarkably improved, and the industrial problem of full-process automation of casting flash is solved.

The invention belongs to the technical field of artificial intelligence and computer vision, particularly relates to a visual processing edge adaptive decision-making method for resource and task perception, and aims to solve the problem of scheduling mismatch caused by resource dynamic change and task demand diversity in visual task processing in an edge computing environment. The method comprises the following steps: collecting multi-dimensional resource state data of edge nodes in real time to form a resource state vector with high time resolution; analyzing the visual task request, and constructing a quantifiable task feature vector; and establishing a resource-task association mapping model based on a dynamic weight distribution mechanism. The method also supports cross-edge domain collaborative decision, and processes a pipeline dynamic reconstruction and security isolation mechanism. According to the technical scheme, the fluctuation of the resource utilization rate is reduced to 15% or below, the average task processing delay is reduced to 60%, the scheduling satisfaction degree is improved by 40% or above, and the self-adaptability and the service quality guarantee capability of the edge vision system are remarkably enhanced.

The invention discloses an interferometer error calibration method and device and a computer readable storage medium, and belongs to the technical field of measurement equipment.The method comprises the steps that measurement data collected when an interferometer moves on the x / y axis of a motion table is obtained, and x / y axis compensation amount is generated through calculation processing; meanwhile, a coordinate system transformation matrix is established and optimized by using data of a marking plate arranged on a motion table, and x-axis and y-axis non-orthogonal parameters are obtained. And then the compensation amount and the non-orthogonal parameters are input into a preset kinematic model, and the accurate position of the motion platform under the global coordinate system is calculated in real time. And when a preset updating condition is met, dynamically updating the error compensation value of the interferometer through the deviation between the actual position detected by the visual system and the calculated position. Reflector surface type error compensation and non-orthogonal parameter correction are fused, and high-precision error compensation calibration of the interferometer is achieved.

The invention, which relates to the technical field of engineering automation, discloses a BIM-based cable bridge routing autonomous optimization visualization system comprising a heterogeneous professional semantic modeling module, a path identification module, a path generation module, a path conflict evolution module, a path reconstruction module and an output module. The system identifies a cable thermosensitive area by constructing a cross-professional semantic map, constructs a multi-target path evaluation function and generates a high-quality candidate path by adopting a variable weight genetic algorithm; introducing a construction stage dynamic compression prediction mechanism to improve the path robustness; visual expression of the whole process of path design is realized through versioned path reconstruction and a three-dimensional animation evolution function; and finally outputting structured path data and an obstacle avoidance strategy which can be used for construction guidance. According to the invention, the intelligent level of cable bridge path planning, the engineering implementability and the system integration efficiency are significantly improved.

The invention provides an intelligent dancing garment generation method and system based on multi-modal action analysis. Dance movement biomechanical data are collected through an inertial sensor array and a multi-view visual system, features are extracted through a space-time diagram convolutional network, style semantics are analyzed in combination with a CLIP model, and a design drawing is generated through a diffusion model and fused into physical constraint optimization. And binding the 3D model with the virtual digital human to simulate a dynamic effect, and outputting a production instruction containing the fabric, the model and the process parameters. The system comprises a data acquisition module, an action analysis module and the like, and the whole-process intelligentization is realized. According to the method, traditional limitation is broken through, by fusing biomechanical data and artistic style semantics, the tear strength and style matching accuracy of the clothes are improved, the design period is shortened, automatic design and production of the dancing clothes are achieved, the dynamic adaptability and artistic expressive force of the clothes are improved, and an efficient scheme is provided for customization of the dancing clothes.

The invention discloses a compliance control method for a massage robot with a rigidity self-adaption function. The massage robot is composed of a six-degree-of-freedom mechanical arm, an end effector, a six-dimensional force sensor, a control host and other modules. The six-dimensional force sensor is installed at the tail end, the contact force of the robot and the surface of the human body can be collected in real time, tail end motion data obtained through the pose sensor is combined, the system executes a compliant control closed loop, and self-adaptive and safe massage operation is achieved. According to the method part, a force control closed loop can be constructed in real time, accurate, safe and smooth massage operation can be achieved through a force sensor installed at the tail end of the robot in combination with a smooth control algorithm based on displacement errors without depending on a visual system, meanwhile, massage area rigidity detection and self-adaptive control are achieved, and the user experience is effectively improved.

A computer-vision system or engine that (a) generates from a pixel stream a digital representation of a person and (b) determines attributes or characteristics of the person from that digital representation and (c) based on those attributes or characteristics, outputs data to a cloud-based analytics system that enables that analytics system to identify and also to authenticate the person. The attributes or characteristics of the person include their pose, and the system or engine analyses that pose to extract a facial image from a video stream that is the best facial image for use by the cloud-based analytics system to identify and authenticate the person. The computer-vision system or engine outputs the facial image to the cloud-based analytics system, but does not output the full-frame real-time video to the cloud-based analytics system.

The invention relates to the technical field of unmanned aerial vehicle vision, and discloses a vision system of an unmanned aerial vehicle and the unmanned aerial vehicle. The system comprises a visual data acquisition module, a dynamic feature extraction module, an environment modeling module and a decision control module. The visual data acquisition module captures a synchronous frame sequence containing infrared wave bands, visible light wave bands and depth information in a target area through a multispectral sensor array; the dynamic feature extraction module performs cross-modal fusion processing on the original visual data stream to generate a space-time correlation feature tensor containing a target contour geometric invariance descriptor and a motion trail differential topological structure; the environment modeling module constructs a three-dimensional semantic grid map according to the feature tensor, wherein each voxel unit codes the material reflectivity, the dynamic obstacle occurrence frequency and the illumination attenuation coefficient; the decision control module generates a flight path control instruction containing a pitch angle adjustment amount, a yaw angle compensation value and a speed change gradient based on the map, and assists the unmanned aerial vehicle to better cope with a complex environment.

The invention belongs to the technical field of robot positioning and three-dimensional mapping, and discloses a high-precision map reconstruction method and system based on monocular vision, a medium and equipment. Scene image data are acquired through a monocular image acquisition module, after feature extraction and matching are performed on each frame of image, attitude information acquired by an inertial measurement unit is fused, and pose calculation of a robot is completed through a sparse vision SLAM system; meanwhile, an image dense depth map is generated by a monocular depth estimation model based on an attention mechanism, and the image dense depth map is converted into a single-frame color dense point cloud in combination with image RGB color information. According to the invention, a loose coupling fusion strategy is adopted to carry out spatial registration on a single-frame colored dense point cloud and a robot pose at a corresponding moment, multi-frame data fusion is completed through point cloud splicing and optimization, and a globally consistent three-dimensional dense point cloud map is constructed to realize scene modeling. The method has the characteristics of high robustness and high reconstruction precision, and can be effectively applied to three-dimensional map construction in an outdoor complex environment.

The invention relates to the technical field of task scheduling, in particular to an intelligent multi-unmanned aerial vehicle cooperative task execution scheduling system and method. The method comprises the following steps: periodically scanning a space in front of a low-altitude flight path of an urban building dense area through a visual SLAM system, and processing visual information in real time by using an airborne edge calculation unit to obtain near-earth space point cloud data of a continuous time sequence; projecting obstacle height information in the near-earth space point cloud data to predefined flight grid units to obtain grid obstacle height data of each grid unit at different time points; and comparing the variation values of the grid obstacle height data in the same grid unit in adjacent time periods, and calculating the obstacle height change frequency in unit time. According to the method, the dynamic change characteristics of the obstacles in the environment can be quantitatively analyzed, the high-risk area is identified, and the challenge brought to multi-unmanned aerial vehicle cooperative task execution scheduling by the complex environment of the urban building dense area is overcome.

A multi-modal stereo vision system includes one or more stereo vision units. Each stereo vision unit includes a plurality of stereo camera pairs. Each image pair includes a first image and a second image. The plurality of stereo camera pairs can capture multi-modal image data.

The invention discloses a precise mark-free positioning system applied to an oral cavity. A camera array composed of a plurality of cameras which are annularly or specifically arranged is arranged on a mobile phone; an infrared imaging assembly for solving the problem of cooling water interference in the operation is designed on at least one camera; the processor is configured to integrate the acquired data including preoperative CBCT (cone beam computed tomography), oral scanning data and digital data of occlusal relationship to construct a complete preoperative oral three-dimensional model; establishing a spatial relationship between a visual system formed by registration of the turbine handpiece and the camera array and a preoperative oral cavity three-dimensional model, and obtaining adaptive relative poses among the parts; after the body position of a patient is fixed during an operation, a complete oral environment point cloud is formed for each frame of input data currently collected by the visual system, and the complete oral environment point cloud is fitted with a patient oral model obtained through oral scanning and CT scanning in advance, so that the oral position of the patient is positioned in real time.

The embodiment of the invention discloses a relative pose calibration method and device of a binocular camera, equipment and a medium, and relates to the technical field of vision measurement, and the method comprises the steps: determining an affine corresponding relation between two lenses in the binocular camera, and respectively determining Pluecker straight lines at different positions; according to the original rotation matrix and the original translation vector of the binocular camera, combining an affine corresponding relation and a Pluecker straight line to construct a generalized camera epipolar constraint model; respectively obtaining attitude information at different positions through an inertial measurement unit, aligning a Y axis of a binocular camera coordinate system to obtain an alignment rotation matrix and an alignment translation vector, and adjusting a generalized camera polar constraint model; and performing polynomial eigenvalue solution to obtain a relative pose. Through geometric model optimization, efficient and robust calibration of the relative pose of the binocular camera under the unknown focal length condition is realized, a plug-and-play calibration solution is provided for a visual system of a dynamic platform, and the technical blank in the field is filled.

An autonomous guided vehicle includes a frame, a drive section, a payload handler, a sensor system, and a supplemental sensor system. The sensor system has electro-magnetic sensors, each responsive to interaction or interface of a sensor emitted or generated electro-magnetic beam or field with a physical characteristic, the electro-magnetic beam or field being disturbed by interaction or interface with the physical characteristic, and which disturbance is detected by and effects sensing of the physical characteristic. The sensor system generates sensor data embodying at least one of a vehicle navigation pose or location information and payload pose or location information. The supplemental sensor system supplements the sensor system, and is, at least in part, a vision system with cameras disposed to capture image data informing the at least one of a vehicle navigation pose or location and payload pose or location supplement to the information of the sensor system.

In a dynamic environment, a visual SLAM (Simultaneous Localization and Mapping) system often causes the problems of large positioning error and inaccurate map construction due to dynamic target interference. In order to improve the robustness and precision of the system, the invention provides a dynamic scene SLAM optimization method based on improved YOLOv11 and geometric consistency constraint. Firstly, ORB features in a scene are extracted, and meanwhile a prior dynamic object and feature points on the prior dynamic object are removed through a YOLOv11 semantic segmentation model; secondly, eliminating feature points on the potential dynamic object by utilizing geometric consistency constraint, and recovering a background shielded by the dynamic object through a semantic perception Gaussian filter; and finally, selecting a high-quality key frame and applying the key frame to loopback detection and global optimization, constructing a basic Gaussian graph through a group of determined poses and point clouds, and finally fusing repair frame information to realize new view rendering and three-dimensional scene optimization.

The invention discloses an external visual system for forklift operation, and relates to the technical field of forklifts. Comprising an acquisition module, a processing module and an output module. The acquisition module stores a warehouse information data set, a cargo information data set, a forklift information data set, an equipment information data set and a problem information data set. According to the invention, through multi-factor decision fusion of a plurality of data sets stored in the acquisition module, a dynamic environment map of the processing module and an analysis model, collaborative optimization of cargo transportation safety and path planning robustness in a storage scene is realized; according to the system, historical accident data, dynamic obstacle contours and warehouse static structures can be fused in real time, high-risk areas are actively avoided, collision accidents and cargo damage risks are remarkably reduced, the problem of path failure caused by dynamic environment changes is effectively solved, and full-process intelligent safety guarantee is provided for high-density storage scenes.

The invention discloses a million-frame-level industrial vision system and method based on event driving and compressed sensing, and the system is characterized in that an event camera imaging module in the system captures the brightness change of each pixel in a field of view of the event camera imaging module in an asynchronous manner, and generates an event containing a pixel coordinate, a timestamp and change polarity for each change; a compressed sensing coding module constructs sparse image vectors for events in a time window, and the sparse image vectors are projected to low-dimensional observation vectors through an observation matrix phi; the sparse image reconstruction module is used for optimizing an objective function through sparse constraint and total variation regularization; a dynamic ROI compression module controls a compression mask function according to the event density and a gradient threshold. The method can break through the limitation of the traditional frame rate, has the advantages of high precision, high efficiency, low power consumption, strong robustness and the like, and has a wide industrial application prospect.

A surface evaluation system that includes one or more vision systems that generate target surface data during evaluation of a surface, the one or more vision systems comprising two or more of: at least one light, a camera, a structured light camera, a laser scanner and a 3D scanner.

The invention discloses a robot finger tactile perception method and system based on artificial intelligence, and the method comprises the following steps: S1, obtaining visual data and tactile perception initial parameters of a to-be-interacted object of a robot finger, carrying out the preprocessing of the visual data, and extracting the appearance features of the object, performing initial configuration on the touch sensing initial parameters; and S2, object recognition is conducted on the preprocessed visual data through a machine learning model, and the material category, morphological characteristics and surface attributes of an object are determined. According to the robot finger tactile perception method and system based on artificial intelligence, by combining a visual system and tactile sensor data and utilizing a convolutional neural network and Transform fusion architecture to extract local textures and global morphological features of an object, high-precision recognition of material categories, morphological features and surface attributes of the object is realized.

The invention discloses a PIN wire steel plate lifting mechanism and a control method, and relates to a PIN wire steel plate lifting mechanism which comprises a lifting module, a grabbing and sucking module and a fixing frame. The lifting module is in linkage with a lifting driving assembly through a ball screw, and high-precision lifting is achieved. The grabbing and sucking module comprises array type vacuum suction cups, a pressure regulating valve set and an air cylinder, the stability is enhanced through a cross-shaped transverse beam frame and a cross-shaped longitudinal beam frame, and 360-degree posture adjustment is achieved by carrying a hollow platform rotating assembly. The fixing frame is connected with the sliding base, so that the mechanism moves along the linear track, and the steel plates are conveyed. The control module integrates a visual system and a laser displacement sensor, positions the position of the steel plate and a hole site in real time, scans a three-dimensional contour, detects whether the steel plate deforms on line based on a hole site and aperture comparison method, automatically triggers a sorting alarm when a detection result exceeds a threshold value, and adopts a graded pressure relief technology in a release process to ensure soft landing of the steel plate. According to the scheme, the stability of the lifting process of the PIN wire steel plate is improved, the comprehensive efficiency of a full-process automatic production line is improved, and the reject ratio of products is reduced.

The invention relates to the technical field of numerical control machining, in particular to a five-axis drilling numerical control machine tool based on visual positioning and a machining method, and the five-axis drilling numerical control machine tool comprises a machine tool body, a numerical control system, a contact type measuring head, a visual system and a calculation control unit. Coordinates of at least three non-collinear reference features on a workpiece in a machine tool coordinate system are automatically collected through a contact type measuring head, the deviation between the workpiece coordinate system and the machine tool coordinate system is automatically calculated through a coordinate system transformation algorithm, and after the workpiece coordinate system is established, a visual system is moved to the position above each programming hole site to shoot actual marks, and the workpiece coordinate system is calculated. According to the method, actual hole center coordinates are extracted through image recognition and compared with theoretical coordinates, and finally, deviation calculation and machining decision are carried out by integrating measuring head data, visual images, numerical control programs and tolerance parameters, so that through the automatic process integrating measurement, recognition, comparison and decision making, the machining precision is improved, and the machining precision is improved. The technical problems of manual errors and lack of verification before processing are effectively solved.

The invention discloses a visual analysis method and equipment for the trafficability of a grain transport vehicle tractor track and a storage medium. According to the method, images are collected through a vehicle-mounted binocular vision system, and multi-dimensional geometric attributes of the terrain and obstacles are automatically extracted through semantic segmentation, three-dimensional reconstruction and voxel modeling. And on the basis of the extracted multi-dimensional attributes, constructing a hierarchical evaluation system containing terrain and obstacle criteria. A local weight of each attribute index is determined by adopting an analytic hierarchy process, and a fuzzy membership degree vector of each index on different passage evaluation grades is constructed according to dynamic judgment parameters adaptively set with the current grain transport vehicle model number and the terrain, so that a membership degree matrix is formed. And finally, through hierarchical fuzzy comprehensive evaluation, calculating to obtain a comprehensive trafficability score. The accuracy, reliability and automation level of tractor track trafficability evaluation are improved.

The invention discloses a bionic visual positioning system and method based on multispectral perception and a storage medium, and the system comprises a front-end multidimensional optical perception module, a mesopic vision preprocessing module and a rear-end fusion perception and target positioning module, the front-end multi-dimensional optical sensing module is used for performing optical imaging, spectral decomposition and polarization imaging; the mesopic vision preprocessing module is used for carrying out image preprocessing and optical flow estimation; and the rear-end fusion perception and target positioning module is used for feature fusion and target identification and positioning. According to the bionic visual positioning mechanism, through a bionic compound eye structure + multispectral + polarization + optical flow fusion perception strategy, the perception bottleneck of a traditional visual system in a high-dynamic and complex illumination environment is effectively solved, and the bionic visual positioning mechanism has the advantages of high robustness, low delay, wide field of view, multiple modes and the like; the method is especially suitable for application scenes such as automatic driving, unmanned aerial vehicles, robots and the like with extremely high requirements on real-time performance and reliability.

According to the robot vision calibration device and method, through collaborative design of the industrial personal computer, the vision system, the robot, the calibration jig and the calibration plate, the problems caused by complex structure, low calibration precision and poor adaptability in the prior art are solved. A floating mechanism of the calibration jig is combined with a displacement sensor to realize multi-degree-of-freedom dynamic displacement compensation, so that mechanical positioning errors are remarkably reduced; the conical surface guide structure and the reference hole layout of the calibration plate optimize the stability of the positioning reference, and ensure the accurate embedding of the calibration needle. The flexible installation of the visual system adapts to different scene requirements. According to the calibration method, the generation of a high-precision visual calibration matrix is realized through the processes of multi-reference hole coordinate recording, calibration ring coordinate calculation and visual image acquisition and matching. According to the whole scheme, through a dynamic compensation mechanism and intelligent process design, the calibration precision, efficiency and robustness are improved, meanwhile, the operation complexity is reduced, and reliable technical support is provided for an industrial automation scene.

The invention discloses a robot vision system construction and control method, and the method comprises the following steps: collecting environment image data and robot motion state data, carrying out the real-time preprocessing of the environment image data, generating standardized image data, and carrying out the real-time monitoring of the environment through setting a dynamic environment sensing module. When real-time grabbing operation guided by robot vision is carried out, an environment light interference real-time judgment mechanism is established, differential compensation strategies are set for different working condition scenes, the stability of visual data collection under the complex illumination condition is guaranteed, and meanwhile compensated light parameters are synchronized to an image processing unit; the problem of feature recognition distortion caused by abnormal environmental reflection can be reduced in real time, the accuracy of robot target positioning is ensured, the track error of visual guidance is reduced, and the completeness of a high-precision assembly task is ensured when it is detected that the in-place posture offset exceeds a safety threshold value.

The invention relates to a digital twinning-based adhesive tape production line full-process collaborative state monitoring method, which comprises the following steps of S1, starting from process monitoring demand carding, deploying an Internet of Things sensor and a visual system, constructing an adhesive tape production line full-process sensing network, collecting data through an industrial gateway, and performing primary processing; s2, equipment modeling is carried out based on the processed multi-dimensional data, a production process twin model is established in combination with a Petri network, and simulation driven by technological parameters and linkage with an MES system are achieved; s3, constructing an AI analysis unit to perform state analysis based on the processed multi-dimensional data, wherein the state analysis comprises equipment health prediction and workshop section risk detection analysis; and S4, fusing the AI analysis result with the twinborn body to generate a multi-angle state risk view. According to the invention, the efficiency and reliability of adhesive tape production line risk collaborative monitoring are effectively improved.

The invention discloses a few-sample-oriented welding defect identification method and platform, and relates to the technical field of welding defect identification, and the method comprises the following steps: collecting and marking an original welding image, collecting a molten pool gray scale image with an optical filter in real time through a visual system in a welding process, and adjusting and generating various defect images in combination with process parameters; the actual welding defect is used as a label; the welding original image is preprocessed, wherein welding pool area cutting, data enhancement operation and standardized data division are included; performing staged training on a welding defect identification model, extracting spatial features through a backbone network, performing cross fusion on horizontal and vertical features through a multi-dimensional feature fusion module to enhance molten pool positioning, and generating high-order statistical features through a Brownian distance covariance matrix module; the method comprises the following steps: identifying defects in an actual welding process, constructing a prototype welding network space based on a meta-learning strategy, generating class prototype vectors of various defects, realizing classification of query images through similarity measurement, and dynamically adjusting process parameters.

The invention discloses an optical fiber laser cutting machine with an automatic feeding and discharging mechanism, and relates to the technical field of laser processing equipment. Comprising a laser cutting main machine, an automatic feeding and discharging mechanism and a central control unit. The automatic feeding and discharging mechanism comprises an intelligent storage module, a transfer robot module, a self-adaptive anti-deviation and accurate positioning mechanism, a visual scanning system and an intelligent discharging automatic collection module. The visual scanning system is innovatively integrated on the combined type vacuum adsorption end effector, so that the combined type vacuum adsorption end effector assists an anti-deviation mechanism in accurate positioning in the feeding process, finished products, waste materials and micro connection are recognized in the discharging process, and function reuse of the visual system is achieved. All the modules are coordinated to work cooperatively through the central control unit, and full-process automatic production of materials from automatic feeding, accurate positioning, laser cutting to intelligent sorting is achieved. The problems that traditional equipment is low in positioning precision, insufficient in automation degree, low in sorting efficiency and the like are effectively solved, and the production efficiency and the machining quality are remarkably improved.

The invention discloses a robot visual guiding and grabbing system for photovoltaic glass stacking, and the system comprises a multi-mode visual data collection module which is used for synchronously obtaining two-dimensional image data and three-dimensional depth data of photovoltaic glass; and the environment adaptive sensing module is used for preprocessing the two-dimensional image data and the three-dimensional depth data to eliminate or weaken the influence of illumination variation, surface reflection and noise on the image quality, and outputting enhanced image data and calibration depth data. According to the robot vision guiding and grabbing system for photovoltaic glass stacking, by introducing the multi-mode vision data acquisition module, two-dimensional image data and three-dimensional depth data of photovoltaic glass are synchronously obtained, and the original data are subjected to reflection removal, denoising and enhancement processing in combination with the environment self-adaptive sensing module; the problem that the image acquisition quality of a traditional visual system is unstable in a high-reflection and complex illumination environment is effectively solved.