1409 results about "Visual system" patented technology

A display system of an aircraft includes a display device defining a display area, a vision system for generating an image of an operating environment of the aircraft on the display area, data processors operatively coupled to the display device and the vision system, and non-transitory machine-readable memory operatively coupled to the one or more data processors and storing instructions executable by the one or more processors and configured to cause the one or more processors to, when a condition of the aircraft is met, cause an alteration of a display of flight information on the display area to declutter a cutout region in the image generated by the vision system, the cutout region devoid of imaging generated by the vision system and displaying an Approach Lighting System (ALS) of a runway of intended landing for the aircraft.

The invention relates to the technical field of visual automatic calibration, and discloses a joint manipulator automatic calibration method and device based on a visual system. The method comprises the following steps: carrying out multi-view image acquisition on a joint manipulator of the five-axis robot to obtain original image data; performing occlusion region extraction on the original image data to obtain a joint occlusion region set; on the basis of the joint occlusion region set, disordered image splicing and mark point feature extraction are carried out on the original image data, and joint feature image data are obtained; constructing an adaptive calibration equation based on the joint feature image data, and solving a target transformation relation between a global visual coordinate system and a local visual coordinate system; multi-joint collaborative calibration and joint chain constraint optimization of the five-axis robot are executed according to the target transformation relation, and joint error correction parameters are generated, high-precision joint error correction parameter calculation is achieved, and the positioning precision and the movement precision of a joint manipulator of the five-axis robot are greatly improved.

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 relates to the technical field of automatic control of a dispensing process, and discloses an intelligent dispensing control method based on a self-adaptive track and dynamic fault-tolerant control. The method comprises the following steps: acquiring spatial pose data of a workpiece to be dispensed through a visual system, identifying a Mark point, and generating positioning reference information; the information is fused with height measurement data, and a dispensing track and dispensing height control parameters are obtained through calculation; driving an injection mechanism to dispense glue according to the control parameters, collecting a glue dispensing image, and comparing the image template to realize real-time judgment and alarm control of the offset and blockage state of the nozzle; after dispensing is completed, coverage rate analysis is conducted on the dispensing image, and a qualification result used for workpiece circulation judgment is generated; all control parameters, image data and judgment results are uploaded to a manufacturing execution system, the time interval between dispensing and the previous process is recorded, and process tracing and time card control are achieved. According to the invention, the dispensing precision and consistency are improved, and the automatic and fault-tolerant performance is good.

The invention is suitable for the technical field of electrical equipment corrosion detection, and provides an electrical equipment corrosion detection method based on double-spectrum collaborative analysis and space-time prediction, and the method comprises the following steps: carrying out fusion analysis on a visible light image and an infrared image of acquired electrical equipment, and outputting position information and morphological category of a corrosion region; a binocular vision system and an IMU sensor are combined to calculate three-dimensional space coordinates, main direction angles and environmental parameters of the corrosion area, and pose data are generated; inputting the pose data into a preset corrosion extension path prediction model for processing, and outputting physical characteristic parameters; fusing the dual-frequency RTK GPS positioning data, the IMU attitude data and the physical characteristic parameters to construct a space-time association data set, and inputting the space-time association data set into a preset space-time diagram neural network model to analyze a space-time evolution relationship of diagram structure modeling corrosion nodes; and outputting microscopic and macroscopic prediction results. The identification accuracy of corrosion characteristics and the corrosion detection efficiency can be improved, and the labor cost and the operation risk are reduced.

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 discloses a robot vision external parameter calibration method based on blind deblurring and natural vibration measurement, and the method comprises the steps: collecting a continuous image sequence in a vibration environment through a high-frame-rate camera, extracting pixel-level motion information in combination with an advanced image deblurring deep network and an optical flow feature tracking technology, and carrying out the self-vibration measurement. And further restoring a three-dimensional displacement signal caused by natural vibration of the camera based on a pinhole imaging model, and obtaining ideal position information through frequency domain analysis to realize high-precision visual system external parameter calibration under a vibration condition.

The invention discloses a stacked workpiece disordered grabbing method and system based on a 3D visual system, and relates to the technical field of computer vision, and the method comprises the steps: obtaining an RGB image and a depth image of a stacked workpiece through a depth camera, and generating point cloud data; the improved Mask R-CNN model integrated with the MSDA module is used for performing instance segmentation on RGB and depth images, and workpiece pose estimation is realized by combining an ICP algorithm and template point cloud registration; establishing a coordinate relation between the camera and the mechanical arm through hand-eye calibration, and obtaining a 6D pose of the workpiece under a mechanical arm base coordinate system; and according to the point cloud centroid distance and the point number, the grabbing priority is calculated, the optimal target is selected for grabbing, and disordered grabbing of all the workpieces is completed circularly. According to the method, the improved Mask R-CNN model integrating the MSDA module and the ICP algorithm are combined with the 3D visual system, so that accurate instance segmentation and pose estimation of stacked workpieces are realized, and therefore, an unordered grabbing task is accurately completed.

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 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.

A control system for a drive through includes processing circuitry. The processing circuitry is configured to determine, using image data obtained from multiple cameras, a characteristic of a vehicle in a lane of the drive through. The processing circuitry can operate a point of sale unit to provide an indication of the characteristic of the vehicle. The processing circuitry can, responsive to detection of one or more of a plurality of vehicles using the image data, perform at least one of (i) initiating an alert via the point of sale unit for staff of the drive through, (ii) initiating an action to open an additional lane, or (iii) initiating a kitchen action to prepare one or more food or beverage items.

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 provides a cleaning and polishing control system and method for a track axle box, which is applied to automatic axle box cleaning and polishing equipment and comprises the following steps: generating an optimal cleaning path and an optimal polishing path according to an axle box three-dimensional model or visual scanning data; pressure and rotating speed parameters are dynamically adjusted according to sensor feedback, operation parameters and fault logs are recorded, and quality tracing and time sequence optimization of cleaning and polishing are supported; the axle box is fixed to a station through a conveying belt or a mechanical arm, and a visual system scans and positions the surface state; large-particle dirt is removed through high-pressure spraying, grease is dissolved through a chemical cleaning agent, and waste water is recycled through a filtering system; the mechanical arm preliminarily polishes the rusted and burr areas according to a preset path; the pressure and rotating speed of the grinding head are adjusted according to feedback of the sensor to realize uniform surface polishing; the cleaning efficiency is improved, the production efficiency is improved, the labor intensity is reduced, the production cost is reduced, customized solutions are adapted according to different production environments and production modes, and an automatic smart factory is built.

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 a content and distortion bilingual guidance-based no-reference image quality evaluation model construction method, which comprises the following steps of: designing two semantic description models of content text description and distortion text description by utilizing a pre-training model CLIP of visual language comparative learning, respectively extracting content features and distortion features of an image by two branches of CNN and Transformer, and constructing a non-reference image quality evaluation model based on content and distortion bilingual guidance. Carrying out cosine similarity calculation on the distortion characteristics of the image and the distortion type and quality grade text description characteristics to obtain the matching probability of the image with various distortion types and quality grades; combining the quality grade probability with a Like scale to predict a quality score; and respectively calculating a content type, a distortion type, quality score loss and weighted summation to guide model training. The semantic content sensitivity characteristics of a human visual system in quality perception are fully combined, and the semantic understanding ability and the quality evaluation accuracy of the model in a complex distortion situation are effectively enhanced.

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 belongs to the technical field of image processing, and particularly relates to a GIS early warning method based on cleaning result analysis of a cleaning robot, which comprises the following steps: acquiring original image data acquired by a camera of the cleaning robot; analyzing view angle inclination influence according to the original image data, determining a feature point offset condition, and generating distortion distribution information; performing correction processing on the original image data according to the distortion distribution information to generate corrected first image data; edge features are extracted for the first image data, and contour information related to clean area division is obtained; dividing a cleaning area according to the contour information, and determining cleaning state distribution information of each area block; and generating a GIS blind area distribution map according to the cleaning state distribution information. According to the method, the problems of image distortion, inaccurate region division and the like in a visual system of the cleaning robot are effectively solved, the cleaning efficiency and quality are improved, and a reliable basis is provided for subsequent cleaning path planning.

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.