80 results about "Location map" patented technology

The invention relates to the technical field of agricultural automation, and discloses a seed leakage real-time detection method and system for an automatic sugarcane planter, and the method comprises the steps: collecting the distance measurement data and position signals of each seed metering channel in real time through a multi-channel sensor, and obtaining an initial distance measurement data set; calculating the relative distance difference between the channels based on the initial ranging data set, and determining the zero drift distance; when the zero drift distance exceeds a preset threshold value, datum point correction is carried out on the target calibration channel, and calibrated ranging data are obtained by fusing adjacent channel data; performing cross validation on the calibrated data, and judging an accumulative error level; channel cooperation parameters are adjusted according to the accumulative error level, distance measurement values passing verification are integrated through a data fusion method, and an optimized relative distance matrix is obtained; and mapping seed leakage point coordinates through the matrix, generating a position map, extracting reseeding target points, and determining a final seed leakage positioning result. The accuracy of seed leakage detection is improved.

A self-organizing mesh network system is disclosed, comprising: at least one master node generating a timing reference signal; a plurality of regular nodes deriving time synchronization from the timing reference signal; and a wireless medium for communicating location and timestamp information among the plurality of regular nodes, The plurality of regular nodes may be configured to each use communicated location and timestamp information of nearby nodes to independently generate a location map of the nearby nodes. The plurality of regular nodes may be configured to accept an additional regular node. The plurality of regular nodes may be configured to allow a node of the plurality of regular nodes to exit the plurality of regular nodes. The plurality of regular nodes may each use communicated location and timestamp information of the plurality of regular nodes to independently generate a location map of each of the plurality of regular nodes.

Methods and systems for determining a signal-to-noise metric for locations of interest on a specimen are provided. One or more statistics of non-defect signals from background patch images in a test image that are similar to a patch image of a location of interest in the test image are determined. The background patch images are found by searching a reference image for patch images that are similar to the location of interest patch image and finding the corresponding patch images in the test image. The signal of the location of interest in the test image and the one or more statistics are used to determine a signal-to-noise metric for the location of interest. The signal-to-noise metric can be used in applications such as defect annotation, deep learning (DL) model tunability, DL model repeatability, and novel defect detection.

The invention discloses a VR image generation method, which comprises the following steps of dividing VR image data into model data and map texture data, respectively storing the model data and the map texture data in a database, and establishing an index table of the model data and the map texture data; extracting an initial position of the VR equipment, retrieving corresponding model data and mapping texture data in the index table according to the initial position, and combining the corresponding model data and mapping texture data to obtain a VR image of the initial position; the method comprises the following steps: performing model data pre-loading on an image area adjacent to a VR image at an initial position, then tracking a moving process of VR equipment, performing multi-stage mapping processing on model data which is not subjected to mapping processing in a real-time VR image, and performing model data pre-loading on an image area adjacent to the real-time VR image at the same time. The defects in the prior art can be overcome, and the generation speed of the VR image is increased.

An autonomous warehouse monitoring robot 100 comprises a propulsion system 106, 108, 110, a processing unit 112 and a scanner array 114 that includes an RFID scanner arranged in a moveable tower, wherein the scanner arrangement is arranged to scan RFID data from at least one package that includes multiple articles. The processing unit is configured to receive RFID scanner data from the scanner array wherein the scanned RFID data relates a horizontal location (P1, P2, fig 1B) for the article in the warehouse, a vertical location (L1, L2, Fig 1B) for the article in the warehouse, and environmental data such as temperature and humidity (148, fig 1C) scanned at the horizontal location and the vertical location for the article. A storage system and method is also disclosed.

This application relates to an arbitrary resolution fusion method for hyperspectral images based on a state-space model, belonging to the field of image processing technology. Addressing the problems of poor multi-scale adaptability and fusion accuracy in existing super-resolution image fusion and reconstruction methods, this application provides an arbitrary resolution fusion method for hyperspectral images based on a state-space model. This method uses a global spatial-spectral fusion module and a bilateral adaptive upsampling module to fuse a low-resolution hyperspectral image with a panchromatic image to obtain fusion features. Based on the fusion features and the location map, an arbitrary-scale super-resolution image is obtained. This invention significantly improves the fusion imaging performance of low-resolution hyperspectral images and panchromatic images, achieving high-precision fusion reconstruction of high-resolution hyperspectral images of arbitrary resolution, effectively solving the bottleneck problems of multi-scale adaptability and fusion accuracy in traditional methods.

The application provides a building crack detection method based on a neural network, comprising the following steps: S100, acquiring a building crack image and performing illumination compensation on the image; S200, extracting multi-scale features of different resolutions of the building crack in the image after the illumination compensation and fusing the features; S300, determining a crack position by obtaining a crack thermal map through the fused features, focusing on a crack region by using a spatial attention mechanism based on a crack position map and the fused feature map, and detecting a crack width, a crack length and a crack direction.

The invention discloses an underwater vehicle rudderstock position map design method based on CFD numerical simulation, and the method comprises the steps: dividing the chord length of a tail rudder into a plurality of equidistant rudderstock position points, and achieving the systematic expression of rudderstock arrangement through the combination of a balance ratio; on the basis of a CFD (computational fluid dynamics) method, an overlapping grid technology is adopted, a simulation environment under the rudder angle change is constructed, and key performance indexes under different rudder stock position and rudder angle combinations are calculated; extracting feature data through a plurality of groups of simulation results, and drawing a map relationship among the rudderstock position, the rudder angle and the hydrodynamic response; and determining an optimal rudderstock position by using the map. By coupling CFD simulation and structural modeling, parameterization, quantification and visualization of rudder system design are achieved, and the design decision efficiency under multiple working conditions and multiple parameters is improved.

1. The name of the design product: graphical user interface for displaying vehicle transportation status on computer. 2. The use of the design product: for running software and programs. 3. The design points of the design product: the design of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The computer is commonly designed, and other views are omitted, including perspective view, rear view, left view, right view, top view, and bottom view. 6. The use of the graphical user interface: for displaying vehicle transportation status. 7. The human-computer interaction mode of the graphical user interface: the front view is the initial interface, clicking the "location icon" enters the change state diagram 1, clicking the "node icon" button enters the change state diagram 2, clicking the "node information" in the right "shipping details" list enters the change state diagram 3, and the map background is only for display and does not belong to the design for which protection is sought.

Surgical guidance systems and methods visually mark a structure of interest (SOI) of an organ on intraoperative images captured by a localizable imaging device. The location of the SOI relative to a body structure (e.g., a passageway system) associated with the organ is determined in preoperative images captured by a medical diagnostic imaging (MDI) system. The location of the SOI relative to the body structure in the preoperative images is then mapped onto a reconstructed version of the body structure based on location information provided by localization sensors distributed on the body structure. Intraoperative images taken by the localizable imaging device are aligned with the reconstructed version of the body structure, and an image object representing the SOI is superimposed on the intraoperative images at a location mapped from the reconstructed version of the body structure.

A multi-beam system includes a light source configured to emit light; a fiber bundle connected to the light source; and a camera configured to capture an image set including images corresponding to each fiber connected to the light source. The fiber bundle includes a central fiber having one end connected to the light source, and N layers of fibers surrounding the central fiber. The first layer of fibers includes M fibers, each having one end connected to the light source, and the Nth layer of fibers includes more than M fibers, but only M fibers in the Nth layer of fibers have one end connected the light source. A processor is configured to determine a centroid of each image in the image set to produce a centroid map and generate a fiber location map comprising fiber locations of all fibers in the fiber bundle based on the centroid map.

This invention discloses an adaptive edge detection and automated trimming system for die-cast hardware parts. By combining a crack detection module with temperature imaging technology, this invention achieves accurate detection and visual positioning of cracks in die-cast hardware parts. A constant-temperature heating liquid and heat-absorbing particles are injected into the crack under high pressure. Due to their significant temperature difference, the heat-absorbing particles penetrating the cracks appear as high-temperature signals in the temperature imager, thus generating a precise location map of the crack distribution. This effectively solves the problem of poor adaptability to complex geometries in traditional detection methods and avoids subsequent trimming damage caused by missed crack detection. Furthermore, a surface cleaning device ensures the cleanliness of the liquid and particles during the detection process. Through the linkage of the crack detection module and the adaptive edge detection module, the system can perform real-time correction and avoidance of crack areas, ultimately achieving efficient, safe, and accurate trimming.

A system includes a plurality of location indicators for arrangement throughout a store that includes a plurality of stocked items. Each of the location indicators defines a different area of the store. The system includes a computing system configured to generate a location map that defines a plurality of sections in the store. Each section includes a plurality of areas of the store defined by different location indicators. The location map defines how the sections and the areas are arranged. The system includes a mobile scanning device that is configured to wirelessly receive an electronic customer order including a plurality of ordered items. The mobile scanning device determines a location value associated with a location indicator and arranges at least some of the plurality of ordered items on the display based on the determined location value and the location map.

The application provides a charging pile information determination method and system based on artificial intelligence, and relates to the technical field of charging piles.The method comprises the following steps: acquiring monitoring videos of a current parking lot in a preset time period; determining parking vehicle sequence data of the parking lot, an installation quantity range of charging piles and a parking lot location map based on the monitoring videos of the current parking lot in the preset time period by using a parking lot data processing model; determining a plurality of charging pile simulation installation scheme information and scheme similarity of different charging pile simulation installation schemes based on the parking vehicle sequence data of the parking lot, the installation quantity range of the charging piles and the parking lot location map by using a variational autoencoder; and determining a charging pile target installation scheme based on the plurality of charging pile simulation installation scheme information.The method can accurately determine the arrangement quantity of charging piles.

1. Name of the product in this design: Setting area of ​​the graphical user interface for generating vehicle trajectory of electronic device. 2. Purpose of this design: An electronic device. 3. The key design features of this product are the graphical user interface in the electronic device for which protection is sought. 4. The image or photograph that best illustrates the key design points: Design 1 Change State Diagram 5. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: The graphical user interface is used for vehicle trajectory generation. The graphical user interface requests protection for a specific area used to set the target parking space and the parking spaces along the driving trajectory. 7. Human-computer interaction method of the graphical user interface: In response to the user touching or clicking the "Target Parking Space" button in the main view of Design 1, the graphical user interface changes from the main view of Design 1 to Design 1 Change State Figure 1 to display the target parking space icon and its operation prompts; in response to the user moving the target parking space icon to the target location, the graphical user interface changes from Design 1 Change State Figure 1 to Design 1 Change State Figure 2 to display relevant operation prompts and the generated preview trajectory; in response to the user touching or clicking the "Passing Parking Space" button in Design 1 Change State Figure 2 after completing the addition of the target parking space, the graphical user interface changes from Design 1 Change State Figure 2 to Design 1 Change State Diagram 3 displays the passing parking space icons and their operation prompts; in response to the user moving the passing parking space icon to the target location, the graphical user interface changes from Design 1 Change State Diagram 3 to Design 1 Change State Diagram 4 to display the relevant operation prompts; in response to the user completing the addition of the passing parking space, the graphical user interface changes from Design 1 Change State Diagram 4 to Design 1 Change State Diagram 5 to display the parking space addition result; in response to the user touching or clicking the "Submit Point" button in Design 1 Change State Diagram 5, the graphical user interface changes from Design 1 Change State Diagram 5 to Design 1 Change State Diagram 6 to display the generated driving trajectory result. In response to a user touching or clicking the "Target Parking Space" button in the main view of Design 2 and moving the target parking space icon to the target location, the graphical user interface changes from the main view of Design 2 to Design 2 Change State Figure 1 to display relevant operation prompts and the generated preview trajectory. In response to a user adding a target parking space and then touching or clicking the "Passing Parking Space" button in Design 2 Change State Figure 1 and moving the passing parking space icon to the target location, the graphical user interface changes from Design 2 Change State Figure 1 to Design 2 Change State Figure 2 to display relevant operation prompts. In response to a user adding a passing parking space, the graphical user interface changes from Design 2 Change State Figure 2 to Design 2 Change State Figure 3 to display the parking space addition result. In response to a user touching or clicking the "Submit Point" button in Design 2 Change State Figure 3, the graphical user interface changes from Design 2 Change State Figure 3 to Design 2 Change State Figure 4 to display the generated driving trajectory. In response to a user touching or clicking the "Target Parking Space" button in the main view of Design 3 and moving the target parking space icon to the target location, the graphical user interface changes from the main view of Design 3 to Design 3 Change State Diagram 1 to display relevant operation prompts and the generated preview trajectory; in response to a user completing the addition of a target parking space and touching or clicking the "Passing Parking Spaces" button in Design 3 Change State Diagram 1 to complete the addition of passing parking spaces, the graphical user interface changes from Design 3 Change State Diagram 1 to Design 3 Change State Diagram 2 to display the parking space addition result; in response to a user touching or clicking the "Submit Point" button in Design 3 Change State Diagram 2, the graphical user interface changes from Design 3 Change State Diagram 2 to Design 3 Change State Diagram 3 to display the generated driving trajectory result. In response to the user touching or clicking the "Target Parking Space" and "Passing Parking Space" buttons in the Design 4 main view and completing the addition of the target parking space and passing parking space, the graphical user interface changes from the Design 4 main view to Design 4 Change State Figure 1 to display the parking space addition result and the generated preview trajectory; in response to the user touching or clicking the "Submit Point" button in Design 4 Change State Figure 1, the graphical user interface changes from Design 4 Change State Figure 1 to Design 4 Change State Figure 2 to display the generated driving trajectory result. In response to a user touching or clicking the "Target Parking Space" and "Passing Parking Space" buttons in the Design 5 main view and completing the addition of the target parking space and passing parking space, the graphical user interface changes from the Design 5 main view to the Design 5 change state diagram to display the parking space addition result and the generated preview trajectory. In response to a user touching or clicking the "Target Parking Space" and "Passing Parking Space" buttons in the main view of Design 6 and completing the addition of the target parking space and passing parking space, the graphical user interface changes from the main view of Design 6 to Design 6 Change State Figure 1 to display the parking space addition result and the generated preview trajectory; in response to a user hovering the cursor over the target parking space icon in Design 6 Change State Figure 1, the graphical user interface changes from Design 6 Change State Figure 1 to Design 6 Change State Figure 2 to display relevant operation prompts and operation buttons; in response to a user dragging the target parking space icon in Design 6 Change State Figure 2 to the target location, the graphical user interface changes from Design 6 Change State Figure 2 to Design 6 Change State Figure 3 to display the parking space dragging result and relevant prompts. In response to a user touching or clicking the "Target Parking Space" and "Passing Parking Space" buttons in the Design 7 main view and completing the addition of the target parking space and passing parking space, the graphical user interface changes from the Design 7 main view to Design 7 Change State Figure 1 to display the parking space addition result and the generated preview trajectory; in response to a user hovering the cursor over the passing parking space icon in Design 7 Change State Figure 1, the graphical user interface changes from Design 7 Change State Figure 1 to Design 7 Change State Figure 2 to display relevant operation prompts and operation buttons; in response to a user dragging the passing parking space icon in Design 7 Change State Figure 2 to the target location, the graphical user interface changes from Design 7 Change State Figure 2 to Design 7 Change State Figure 3 to display the parking space dragging result and relevant prompts. In response to a user touching or clicking the "Target Parking Space" and "Passing Parking Space" buttons in the main view of Design 8 and completing the addition of the target parking space and passing parking space, the graphical user interface changes from the main view of Design 8 to Design 8 Change State Diagram 1 to display the parking space addition result and the generated preview trajectory; in response to a user hovering the cursor over the target parking space icon in Design 8 Change State Diagram 1, the graphical user interface changes from Design 8 Change State Diagram 1 to Design 8 Change State Diagram 2 to display the relevant operation buttons; in response to a user rotating the parking space icon to the target angle using the rotation button in Design 8 Change State Diagram 2, the graphical user interface changes from Design 8 Change State Diagram 2 to Design 8 Change State Diagram 3 to display the parking space rotation result and related prompts. In response to a user touching or clicking the "Target Parking Space" and "Passing Parking Space" buttons in the main view of Design 9 and completing the addition of the target parking space and passing parking space, the graphical user interface changes from the main view of Design 9 to Design 9 Change State Diagram 1 to display the parking space addition result and the generated preview trajectory; in response to a user hovering the cursor over the passing parking space icon in Design 9 Change State Diagram 1, the graphical user interface changes from Design 9 Change State Diagram 1 to Design 9 Change State Diagram 2 to display the relevant operation buttons; in response to a user rotating the parking space icon to the target angle using the rotation button in Design 9 Change State Diagram 2, the graphical user interface changes from Design 9 Change State Diagram 2 to Design 9 Change State Diagram 3 to display the parking space rotation result and related prompts. In response to a user touching or clicking the "Target Parking Space" and "Passing Parking Space" buttons in the main view of Design 10 and completing the addition of the target parking space and passing parking space, the graphical user interface changes from the main view of Design 10 to Design 10 Change State Figure 1 to display the parking space addition result and the generated preview trajectory; in response to a user hovering the cursor over the target parking space icon in Design 10 Change State Figure 1, the graphical user interface changes from Design 10 Change State Figure 1 to Design 10 Change State Figure 2 to display relevant operation prompts and operation buttons. 8. Other situations requiring explanation: The portion of the graphical user interface shown by the yellow dashed lines in the views of Design 1 to Design 10 does not constitute the part that is protected by this design. The pattern formed by the white dashed lines in the views of Designs 1 to 10 is part of the design patent that is to be protected. This design does not require color protection.

The application relates to a cargo placement control method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a warehouse location map by acquiring image collection of a warehouse location; the warehouse location objects in the warehouse location map are at least one; the warehouse location represented by the warehouse location objects is used for storing cargos; the warehouse location objects in the warehouse location map are positioned and detected; the cargo placement state of the warehouse location objects is recognized, and the cargo placement state of the warehouse location represented by the warehouse location objects is obtained; the cargo placement state is used for indicating whether there is a cargo on the warehouse location represented by the warehouse location objects; and the cargo placement control processing of the carrying equipment is performed according to the cargo placement state. The cargo placement state of the warehouse location objects in the warehouse location map can be recognized, and whether there is a cargo on the warehouse location represented by the warehouse location objects can be automatically judged through programming, so that the carrying equipment can timely place the cargos, and the efficiency of the cargo placement is improved.

This invention discloses a positioning map construction method for HPA (Hyperparking Approach) and a vehicle parking method based on HPA. The method identifies parking spaces and vehicles parked in target parking areas, and constructs a positioning map based on the parking space and vehicle identification results. During HPA path playback, based on the positioning map, the method obtains the vehicle's first position information according to detected parking space or vehicle identifiers. The vehicle's self-positioning information is then corrected based on the first position information to obtain the vehicle's second position information. When preset mode switching conditions are met, the vehicle's current second position information is used as the mode switching point, controlling the vehicle to switch to parking mode and complete automatic parking. This invention improves positioning accuracy during vehicle parking by constructing a positioning map and using it to assist vehicle positioning, and also rationally arranges the vehicle's mode switching points.

Methods and systems for determining a signal-to-noise metric for locations of interest on a specimen are provided. One or more statistics of non-defect signals from background patch images in a test image that are similar to a patch image of a location of interest in the test image are determined. The background patch images are found by searching a reference image for patch images that are similar to the location of interest patch image and finding the corresponding patch images in the test image. The signal of the location of interest in the test image and the one or more statistics are used to determine a signal-to-noise metric for the location of interest. The signal-to-noise metric can be used in applications such as defect annotation, deep learning (DL) model tunability, DL model repeatability, and novel defect detection.

The invention provides a natural ecosystem investigation method. The natural ecosystem investigation method comprises the following steps: S1, acquiring a high-resolution remote sensing image and DEM data, and dividing ecosystem types; s2, typical ecological problems of the ecological system are determined, sample plot design and sample plot dynamic arrangement are carried out, investigation points are arranged in a sample plot, and sampling analysis is carried out; and S3, performing data analysis according to the plaque partition map, the sample plot location map and the remote sensing image map. According to the dynamic survey method combining quadrat / transect and sampling point actual ground survey, the mutual verification of ground, remote sensing and model data is realized by combining a satellite remote sensing and model simulation technology with multiple data sources, typical / important ecological problem partitions in a watershed ecosystem range are found out and verified, and a watershed ecological system is established. Support is provided for design and implementation of the ecological engineering project, and a data index basis is provided for acceptance of the ecological engineering project.

The invention is entitled "Identifying cardioversion while building a position map." The invention describes a method comprising: computing a position of an intrabody probe within a heart of a subject based on an inductive signal received from an electromagnetic sensor, the intrabody probe comprising one or more electrodes and the electromagnetic sensor; determining a set of attributes of a signal transmitted between the electrode and a plurality of reference electrodes located at respective reference positions based on a set of attributes; responsive to a distance between the computed position and an estimated position being greater than a predetermined threshold, deriving an estimated position of the probe from a position map that maps the sets of attributes to respective estimated positions; determining whether an electrocardiogram signal from the subject is saturated; and responsive to the electrocardiogram signal not being saturated, updating the position map so as to map the set of attributes to the computed position. Other embodiments are described.

The invention provides a hand-object interaction reconstruction method based on contact perception UV graph representation, which is used for reconstructing an interactive hand and an interactive object from an input single-view color image and ensuring that a reconstructed hand-object interaction result has a smaller die penetrating volume and a more reasonable interaction posture. The method specifically comprises the following steps: 1, constructing a contact perception UV graph from a public hand-object interaction data set; 2, preprocessing an input image to enable the size of the image input into the model to be as follows; 3, designing and building a hand and object feature extraction network, and sending the processed single-view image data to the feature extraction network, 4, building a diffusion model of a UNet structure, and iteratively estimating a contact perception UV image of a target from Gaussian noise; 5, directly recovering the vertex coordinates of the hand and the contact condition of each vertex from the contact perception UV graph; and 6, in order to adjust an inaccurate hand posture, an interaction optimization model is introduced, and the model optimizes the hand posture reconstructed in the UV position map, so that a final hand-object interaction result is reconstructed and obtained.

The objective is to obtain an information processing device and information processing program that can more easily convert point cloud data acquired as relative coordinate values ​​into absolute coordinate data compared to conventional technologies. [Solution] The information processing device 10 includes an acquisition unit 11A that acquires point cloud data obtained by 3D imaging an area in which a position image showing the absolute coordinate position of a predetermined corresponding point on a corresponding center line is arranged such that the predetermined reference point of the position image is at a position corresponding to the center line or the offset line of the center line, and a recording unit 11B that records the acquired point cloud data.

The invention provides a positioning method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of image processing, in particular to the technical fields of image positioning, artificial intelligence and the like. According to the specific implementation scheme, an image to be positioned is obtained, image feature extraction is conducted on the image to be positioned, positioning image features corresponding to the image to be positioned are obtained, and positioning image feature vectors comprise low-dimensional image features and high-dimensional image features; matching the low-dimensional image features with a plurality of index features of an image position library to obtain at least one candidate index feature matched with the low-dimensional image features; the image position library stores position image features corresponding to a plurality of position images, index features constructed according to the position image features, and geographical position information associated with the position images; and in response to the condition that the candidate index feature does not meet a preset condition, matching the high-dimensional image feature with a position image feature corresponding to the candidate index feature, and determining geographical position information of the to-be-positioned image.

1. Name of the product in this design: Electronic device with a graphical user interface for robot cleaning details. 2. Purpose of this design: This design is used for display and interaction, for users to process information on the robot cleaning details device on the display screen panel. 3. The key design features of this product are: the graphical user interface content on the display screen panel, which can display relevant information about the robot cleaning device. 4. The image or photograph that best illustrates the design's key features: the front view. 5. The display screen panel adopts the conventional design, omitting the rear view, left view, right view, top view, and bottom view. 6. Purpose of the graphical user interface: Robotic cleaning details. 7. Human-computer interaction method of graphical user interface: The main view is the home page. When the user clicks on the main view, the page contains map information, floor, cleaning area, and time-consuming module information. Click on the main view interface; the cleaning status is marked as cleaning in progress. The upper part of the image is a map, which allows you to view the robot's location. The "Cancel Task" section at the bottom of the map displays cleaning status information (Status: Cleaning in Progress). Below the "Cancel Task" section, the floor number, cleaning area, and cleaning duration are displayed. Below the "Floor" section, the robot's specific location and cleaning progress are displayed; gray indicates no cleaning, and green indicates cleaning. The "Task Information" section displays task information. Once the cleaning task is completed, a "Status Change Graph" will be displayed. Click on the task bar information in the graph to view detailed data. In the main view and all other views, the characters used are replaceable, and the number of "X"s does not limit the number of characters that can be replaced.

The invention discloses an air cooperative positioning system based on an unmanned aerial vehicle group, and the system comprises a data collection module which collects the multi-modal data of each unmanned aerial vehicle in real time through sensors on a plurality of unmanned aerial vehicles, and the multi-modal data comprise the current position, speed, attitude and surrounding environment information; the cooperative positioning module calculates the accurate position of each unmanned aerial vehicle based on the acquired multi-modal data and a data fusion algorithm; and the group positioning optimization module optimizes the collective positioning precision of the unmanned aerial vehicle group in real time based on the calculated accurate position of each unmanned aerial vehicle in combination with the relative position among the multiple unmanned aerial vehicles. According to the invention, through multi-modal data acquisition, cooperative positioning calculation and relative position map optimization, high-precision, high-robustness and consistent collective positioning of an unmanned aerial vehicle group in a complex environment is realized.

The application provides a process window prediction method based on curved surface fitting, relates to the field of lithography technology, and comprises a prediction system, wherein the prediction system comprises a control module, a measurement data processing module, a model simulation module, a process window analysis module and a visualization module. The technical scheme predicts the process window through curved surface fitting, simultaneously considers the influence of Focus / Dose parameters on CD, has smaller fitting result error, is more accurate in process window prediction, comprehensively analyzes the interactive influence of illumination dose and focusing position through a three-dimensional curved surface fitting method, overcomes the overfitting problem of single parameter fitting of a traditional Bossung graph and EL graph, generates a larger and more stable common process window, reduces the prediction error from 8% to 4.8%, increases the process window area by 12%, and significantly improves the prediction accuracy of the pattern quality of all positions of the wafer.

The present application relates to the field of indoor positioning, and particularly relates to a terminal positioning method and device, electronic equipment and storage medium, the method comprising: acquiring actual indoor scene images in a target area and first positioning feature data of a terminal to be positioned collected at corresponding collection positions; calculating second positioning feature data under each target data feature dimension according to each first positioning feature data; the second positioning feature data is used for quantifying device hardware attributes of the terminal to be positioned; inputting an image difference feature matrix between the actual indoor scene images and standard indoor scene images, each first positioning feature data and each second positioning feature data into a terminal positioning model to obtain a target position of the terminal to be positioned; the image difference feature matrix is used for representing environmental changes to correct errors in the first positioning feature data. Through the present application, device hardware attributes and environmental changes can be quantified and represented, and the accuracy of indoor terminal positioning is improved.

This invention discloses a non-destructive image recognition method and system for eggshell cracks. The method includes: first, obtaining an eggshell crack dataset; then, generating eggshell crack feature maps and crack location maps based on the eggshell crack dataset; constructing an initial eggshell crack detection model, and training the initial eggshell crack detection model based on the eggshell crack feature maps and crack location maps to obtain a trained eggshell crack detection target model; finally, acquiring view image data of the target egg with the crack to be detected, and determining the crack detection result of the target egg based on the eggshell crack detection target model. By constructing and training the eggshell crack detection target model, it can accurately identify and locate cracks on eggshells. This method not only significantly improves the accuracy of detection but also significantly enhances detection efficiency, providing strong support for egg quality inspection and food safety assurance.

The application provides a kind of tubular belt conveyor belt torsion angle identification method and device, method includes the following steps: collection conveyor belt lap position picture information;According to the outer diameter of conveyor belt, construct data scale, and specify the scale and range of data scale;Extract the characteristic pixel points of the lap position of the picture of the conveyor belt;Keep the characteristic pixel points located in the middle position as the determination pixel points;Take the average of the minimum row number and the maximum row number in all determination pixel points as the horizontal coordinate of the lap position of the conveyor belt;Project the horizontal coordinate of the lap position of the conveyor belt to the data scale, and judge the torsion angle of the conveyor belt according to the intersection of the projection and the scale on the data scale.The device includes a camera and a picture information processing unit.According to the input information of the lap position of the conveyor belt, an identification algorithm model is established, and the rotation angle of the lap position is calculated in real time, so that the maintenance and management personnel can master the accurate torsion angle of the lap point of the conveyor belt, and provide data reference for decision-making.