1654 results about "Location determination" patented technology

The invention provides a multi-source data fusion distribution processing analysis method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining heterogeneous sensor data, constructing a multi-dimensional data structure, and identifying a missing or abnormal sampling position; determining an associated neighborhood and obtaining historical observation data to construct a memory state sequence; memory type state reconstruction is executed to generate completion candidate data and confidence weight, a complete multi-dimensional data structure is generated after fusion, and the reliability of the whole completion process is quantified; and dividing the multi-dimensional data structure to different processing nodes, executing cross-node synchronization, then carrying out multi-modal conjoint analysis, and outputting a fusion analysis result and a confidence index. According to the invention, the data fusion analysis precision and efficiency are improved.

The invention discloses an automatic three-dimensional reconstruction method and system based on power transmission corridor point cloud. The method comprises the following steps: acquiring data and exporting point cloud data; noise points, outliers and ground points are removed from the acquired point cloud data of the power transmission corridor, and down-sampling is performed on the point cloud with a large data volume; performing clustering segmentation on the preprocessed point cloud of the power transmission corridor, positioning the position of a tower, determining a point cloud range of a power line, and removing point clouds of other objects on the ground; aiming at the structural characteristics of a power line and an insulator in the power transmission line, extracting point clouds of the power line, the insulator and a tower by adopting a geometric constraint principal component analysis (PCA) algorithm; performing automatic geometric model reconstruction on the tower, insulator and power line point clouds according to different reconstruction rules to generate each module grid model; and transforming the grid model of each module, restoring the grid model to the original position of the point cloud, and generating a power transmission line digital twin model conforming to the real size. According to the method, automatic segmentation, classification and real-time reconstruction can be accurately carried out on the point cloud of the power transmission corridor.

The invention discloses a document comparison traceability method and device and a computer storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: in response to a traceability request for a difference fragment, determining the range of the difference fragment in an original document according to the difference fragment and a difference position corresponding to the difference fragment, identifying the text in the range as a target text; splitting the target text into independent text segments according to separators, comparing the text segments with the difference segments, and determining the similarity between each text segment and the difference segment; and taking the text fragments with the similarity reaching or exceeding a preset threshold as candidate fragments, determining the text fragment with the highest similarity from the candidate fragments as a tracing fragment, and returning position coordinates of the tracing fragment in the original document. By receiving the traceability requests of the difference fragments and the difference positions and positioning the difference range, the traceability analysis range is effectively reduced, and the accuracy of document comparison traceability is improved.

The invention relates to a computer-implemented method for identifying at least one area of interest from a region of interest. The method comprises: obtaining a plurality of geo-information data over the region of interest for a geological time interval, the geo-information data comprising at least carbonate reference locations wherein marine carbonate sediments are observed, obtaining at least one paleo-digital elevation model of the region of interest, providing an Earth system model with a plurality of input sets of modeling parameters and obtaining output sets of paleoenvironmental parameters, determining a plurality of representative paleoenvironmental parameters for each carbonate reference location from the plurality of output sets of paleoenvironmental parameters, grouping at least a part of the carbonate reference locations into at least one group of carbonate reference locations defined as carbonate factory, and computing a susceptibility of occurrence of the carbonate factory.

The invention provides an indoor positioning method and system based on vision, geomagnetism and inertial navigation, and the method comprises the steps: obtaining inertial navigation data, and determining a local region where a target object is located in an indoor space according to the inertial navigation data; wherein the inertial navigation data is obtained by a positioning device carried by a target object; obtaining a visual image of the local area, and determining the position of the target object in a pre-constructed spatial model according to the visual image to obtain a first position; determining a target range according to the first position, and simulating an environment magnetic field around the target object under the condition that the magnetic disturbance object exists in the target range; real-time magnetic field data is obtained, the real-time magnetic field data is obtained through measurement of magnetic field measurement equipment carried by the target object, the real-time magnetic field data is matched with the environment magnetic field, the specific position of the target object in the local area is determined, and a second position is obtained. According to the invention, multiple positioning technologies are fused, and the indoor positioning accuracy can be further improved.

The invention provides a space error compensation method, device and equipment and a computer storage medium, and belongs to the technical field of precision machine manufacturing, and the space error compensation method comprises the steps: in an offline mode, based on target space error data, determining a compensation model; and in the current interpolation period of the machine tool, determining the compensated coordinate point of the current interpolation period based on the compensation model and the target position of the current interpolation period. The machining track of the machine tool can be corrected in real time in the machining process.

The invention provides a reference line generation method, an automatic driving method and device, equipment and a vehicle, and relates to the field of artificial intelligence, in particular to the field of automatic driving. According to the specific implementation scheme, for at least one obstacle located in a target area in a road, the category of the obstacle is determined according to a first motion parameter of the obstacle in a historical time period, and the category of the obstacle represents the relative relation between the obstacle and a target vehicle; under the condition that the at least one obstacle comprises the target obstacle belonging to the target category, determining any candidate node in a plurality of candidate nodes determined for the position of the target vehicle, and determining the total cost value of the candidate nodes according to the historical driving track of the target obstacle and the second motion parameter of the candidate node; determining a target region reference line according to a target node determined by using the total cost values of the plurality of candidate nodes; wherein the target area reference line is used for planning a target driving track of the target vehicle.

The invention provides a robot path planning method and system based on multi-strategy improvement and a medium, and relates to the technical field of path planning, and the method comprises the following steps: building a grid map of a ground environment based on a positioning navigation system, and correcting and supplementing the grid map in combination with environment information sensed by a robot in real time; according to the corrected and supplemented grid map, an objective function of robot path planning is established; according to the objective function, performing optimal position updating through an improved mouse group optimization algorithm, and determining an optimal mouse position; wherein the improved mouse group optimization algorithm is that a position updating formula of an original mouse group optimization algorithm is improved by introducing a position updating mechanism of a teaching and learning optimization algorithm and an education competition optimization algorithm. And determining an optimal path planning result according to the optimal mouse positions which are sequentially updated according to a preset maximum iteration number. According to the method, the problem of local optimum existing in an existing path planning method is solved, and the robot path planning effect can be effectively improved.

A position estimation unit 25 estimates, for each movement in a predetermined section, a plurality of position candidates of a position estimation target on the basis of position information and sensor information. A position determination unit 26 evaluates, for each movement in the predetermined section, on the basis of the plurality of position candidates of the position estimation target obtained by the movement in the predetermined section, whether the position information used to estimate the position candidates has an error caused by any of a position of a GPS satellite, a position of a mobile body in a real space, or the mobile body or does not have any error caused thereby. The position determination unit 26 determines a final output value of the position of the position estimation target on the basis of a result obtained by removing, from the plurality of estimated position candidates of the position estimation target in the plurality of times of the movement in the predetermined section, a position candidate of the position estimation target estimated in the movement in the predetermined section that has been evaluated to have the error.

The invention relates to the technical field of scene matching navigation, and provides a multi-mode scene matching navigation positioning method and device for a self-adaptive variable-structure unmanned aerial vehicle. According to the method, geographic coordinates corresponding to all pixel points in an aerial image are determined according to pose information in the aerial image of the unmanned aerial vehicle, and the geographic position of the unmanned aerial vehicle with errors is corrected based on difference information between the pixel coordinates of the central point of the aerial image of the unmanned aerial vehicle and the geographic position corresponding to the center of a camera. Based on the corrected geographic position of the unmanned aerial vehicle, determining a reference image pixel coordinate corresponding to the angular point pixel coordinate of the aerial image, and obtaining a simulated aerial image under the view angle of the unmanned aerial vehicle through perspective transformation so as to determine a homography transformation matrix; according to the method, the satellite reference image pixel coordinates of the interest point in the aerial image are determined based on the homography transformation matrix and the perspective transformation matrix, and finally the longitude and latitude of the interest point are determined, so that the limitation of the traditional method in view angle difference compensation, computing resource constraint and cross-modal processing is solved, and the universality, robustness and positioning accuracy of the system are improved.

A method of controlling a user terminal, performed by a computer system that is a server or the user terminal, may include determining whether the user terminal is located within a customized region of a space based on a location of the user terminal, the customized region being associated with at least one service element, and in response that the user terminal is determined to be located in the customized region, controlling the user terminal based on the service element.

When using a drone to monitor or survey an object on the water, the position of the object can be determined more accurately, or the object can be analyzed more accurately. [Solution] The present invention is an information control system comprising a group of moving bodies consisting of multiple moving bodies equipped with measurement sensors capable of acquiring measurement data measuring an object when at least a portion of it is above water, a moving body operation control unit that controls the operation of the moving bodies, a measurement data acquisition unit that acquires first measurement data measured of the object from a first position by at least one of the moving bodies in the group of moving bodies and second measurement data measured of the object from a second position by the moving body or another moving body, an object position determination unit that determines position information of the object based on the first measurement data and the second measurement data, or determines the validity of the determined position information, and an information output unit that displays or transmits to the outside the position information of the object determined by the object position determination unit.

The invention belongs to the technical field of behavior prediction, and particularly relates to a ship anomaly detection method and device based on TCN trajectory prediction. The method comprises the following steps: S1, acquiring AIS data given by a ship automatic identification system in a set time period before the current moment; s2, predicting the position of the ship at the next moment based on a pre-trained time convolutional network; s3, determining an error between the actual position and the predicted position of the ship at the next moment; s4, when the error exceeds a threshold value, determining that the position is an abnormal point; s5, continuously appearing abnormal points serve as abnormal track segments, the time length of the abnormal track segments serves as a weight calculation factor, and the abnormal scores of the abnormal track segments are calculated; and S6, determining the abnormal level of the abnormal track segment according to the abnormal score and the plurality of abnormal degree intervals. According to the invention, the detection precision of ship abnormal behaviors is improved.

The invention discloses a device structure performance condition monitoring method based on layered depth dynamic potential. The method comprises the following steps: determining a device easy-to-damage position based on discrete mechanics; obtaining key mechanical response characteristics of the vulnerable position based on structured compressed sensing; constructing a structural performance condition monitoring model based on global capture and local fusion; characteristic enhancement of real-time structure performance condition interactive monitoring poles is realized; and solving the structural performance resonance measurement of the device. Through hierarchical processing and depth potential modeling, the problems that a traditional method is insufficient in local anomaly recognition capability and limited in global prediction precision are effectively solved, and higher anomaly detection sensitivity, higher robustness and better prediction accuracy are shown in experimental comparison; the method is especially suitable for real-time structure performance condition monitoring under complex working conditions.

The invention relates to the technical field of building detection, and discloses a building retard-bonded prestress intelligent detection method based on the Internet of Things. The method comprises the steps of collecting and preprocessing real-time monitoring data of the retard-bonded prestressed structure through an Internet of Things platform, and filtering interference signals to improve data quality; classifying the preprocessed data according to a preset stress state interval, and extracting time-space domain features of each interval to generate a stress feature set; detecting the change frequency of the stress state interval, and starting a dynamic adjustment mechanism to mark an abnormal interval if the change frequency exceeds a threshold value; according to the matching degree of the historical damage mode of the structure and the current feature, a non-abnormal interval stress feature set is decomposed to generate a damage feature subset, multi-parameter collaborative correction is carried out in combination with the incidence relation of material mechanics and environmental action parameters, and finally the position of a potential damage source is reversely traced along a damage evolution path. And determining a maintenance priority and generating a maintenance instruction.

The invention relates to the technical field of unmanned aerial vehicle detection, and discloses a highway bridge hidden danger target identification and position determination method based on an unmanned aerial vehicle. The method comprises the following steps: acquiring a real-time video of a bridge by using an unmanned aerial vehicle carrying a multispectral sensor, and performing multi-scale segmentation on a current frame image to obtain a bridge surface and a suspected hidden danger target area; extracting a suspected hidden danger target area texture feature through a gray level co-occurrence matrix, morphological closed operation and spatial domain filtering, and inputting a hidden danger classification model to obtain type information; based on the bridge surface geometric structure model and the center coordinate of the suspected hidden danger target area, calculating the offset of the suspected hidden danger target area relative to the bridge datum line; and generating three-dimensional space coordinates in combination with the offset and the type information, and marking the three-dimensional space coordinates in a bridge structure chart. According to the method, multi-spectral sensing, multi-scale image processing and three-dimensional modeling technologies are fused, accurate recognition and three-dimensional positioning of bridge hidden dangers are achieved, hidden danger information can be dynamically updated, and the detection efficiency and precision are improved.

Approaches for evaluating user devices are disclosed. Devices that are physically proximate to a user device are determined. A first geolocation is determined based on the devices that are physically proximate to a user device. Data communications involving the user are evaluated. A second geolocation is determined based on an evaluation of the data communications involving the user. A proximity of the first geolocation with respect to the second geolocation is determined. The proximity of the first geolocation and the second geolocation are evaluated with respect to a threshold value to determine if the first geolocation and the second geolocation are sufficiently proximate.

The invention provides a collision avoidance learning control method applied to an unmanned system cluster, which can be applied to the technical field of artificial intelligence. The collision avoidance learning control method comprises the following steps: determining respective state vectors of a plurality of unmanned systems according to respective real-time positions of the plurality of unmanned systems in an unmanned system cluster; inputting the communication weight among the plurality of unmanned systems, the state vector of each unmanned system and the expected formation vector of each following unmanned system relative to the piloting unmanned system into an error dynamic model to obtain respective formation errors of the plurality of unmanned systems; for each unmanned system, inputting the formation error into an evaluation neural network to obtain a prediction control parameter; determining a comprehensive obstacle function value based on the respective real-time positions of the plurality of unmanned systems and the real-time position of the obstacle; and correcting the prediction control parameter based on the comprehensive obstacle function value to obtain a target control parameter so as to control the unmanned system cluster to perform formation motion by using the target control parameter.

A high-altitude platform and method for in-flight navigation, the platform comprising a ground-facing camera and a computing device including a memory and a processor, the memory storing instructions which when processed cause the computing device to perform a position determination method, comprising: acquiring one or more images from the ground-facing imaging device; retrieving, from an image dataset associated with a trained model, a plurality images associated with an area of interest; processing, using an image comparator, the acquired one or more images and the retrieved images associated with terrain of interest to derive therefrom respective acquired image feature sets; using a loss function, comparing each acquired image feature set to each retrieved image feature set to identify for each acquired image a corresponding matching retrieved image; using the matched image and the optical characteristics of the ground-facing camera, determining the position of the platform.

One or more computing devices, systems, and / or methods for low power consumption geofencing are provided. Location determination facilities used during a past number of device location lookups over a timeframe are tracked. If a geofence is actively set and movement of a device has triggered execution of location identification logic, then a determination is made as to whether a particular location determination facility was used during the past number of device location lookups over the timeframe. If the particular location determination facility was used during the past number of device location lookups over the timeframe, then an original sequence of location determination facilities attempted by the location identification logic is modified to create a modified sequence of location determination facilities used to determine a current device location of the device. Otherwise, the original sequence of location determination facilities is used to determine the current device location of the device.

The embodiment of the invention provides a substation meter identification method, device and equipment. The method comprises the following steps: acquiring a to-be-recognized image; inputting the to-be-recognized image into a pre-acquired target detection model to obtain a target type of a target meter and position information of the target meter in the to-be-recognized image; wherein the target detection model is a model which is obtained by training a lightweight YOLOv11 model based on an image in which the type and the position of the meter are calibrated in advance and is used for classifying the meter in the image and determining the position of the meter; wherein the lightweight YOLOv11 model is obtained by setting a backbone network of the YOLOv11 to be a StarNet lightweight network and setting a detection head to be BNLSCD; cutting out an area where the target meter is located from the to-be-identified image according to the position information to obtain a dial plate image; and reading the meter based on the target type and the dial plate image to obtain the reading of the target meter. The method is used for achieving the effect of reducing computing resources consumed for identifying the meter reading.

The invention provides an unmanned aerial vehicle laboratory testing method and device, and belongs to the technical field of unmanned aerial vehicle testing. The scheme comprises the following steps: determining a global reference point based on the position of a laboratory, and further determining a conversion relation between a local northeast high coordinate system and a global coordinate system and a plurality of fixed reference points; according to the fixed reference point, sequentially executing stand setting and starting of an automatic measurement tracker in a laboratory, and further obtaining real-time coordinates of the to-be-tested unmanned aerial vehicle by using the automatic measurement tracker; the GNSS signal generator generates a simulation navigation signal according to the real-time coordinates of the to-be-tested unmanned aerial vehicle and records a simulation track; the to-be-tested unmanned aerial vehicle performs indoor flight test based on the simulation navigation signal; and comparing the simulation track with a flight track recorded by a flight control system of the to-be-tested unmanned aerial vehicle so as to output a laboratory test result. The scheme does not depend on hardware modification of the unmanned aerial vehicle, the implementation difficulty is reduced, the implementation cost is saved, and controllable testing of medium and large unmanned aerial vehicles in the indoor environment is facilitated.

A system for calibrating a computing device to track basketball shots has a camera for capturing two-dimensional (2-D) images of a basketball shot toward a basketball hoop. The system identifies the basketball and basketball hoop in the 2-D images and determines distances of the basketball from the camera based on sizes of the basketball in the 2-D images. The system also determines angles of the basketball from the camera based on positions of the basketball in the 2-D images. The system calculates a parabolic trajectory of the basketball based on the determined distances and angles and then determines an orientation and a position of the camera in three-dimensional (3-D) space based on the identified basketball hoop and the calculated trajectory. The system stores, in memory, calibration data indicative of the orientation and the position of the camera in 3-D space for use in tracking basketball shots by the computing device.

There is disclosed a multirotor UAV in which electric motors are arranged to drive propellors under the control of an on-board flight controller. The UAV has a plurality of sensors and a first processor for providing sensor signals to the flight controller in normal mode of in-flight operation. The UAV has a three-dimensional depth scanner and a further data processor for processing the three-dimensional depth scanner, wherein the further data processor is selectively activated to process the three-dimensional depth scanner data in a second mode of in-flight operation when fling in close proximity to an external structure. The further data processor creates a three-dimensional map of the external structure for control of the flight of the UAV proximate thereto. The UAV can operate in a GPS-denied and / or compass-denied mode. One or more sensor can detect a profile of an external structure within a predetermined vicinity of the UAV. A depth sensor can detect a visible feature in the environment. The control system is operable to log the visible feature as reference point and to determine yaw readings for use by the flight controller relative to said reference point. The control system comprising can receive the outputs of the distance scanning sensor and the location determining system and can define a mapping boundary around a current position of the UAV. The mapping boundary is of a defined size that is smaller than the scanning range of the position scanning sensor. The data processor generates a map of any surfaces within the mapping boundary and the flight controller is arranged to output control instructions for control of the propulsive rotors based upon the map.

The invention discloses a double-target automatic tracking shooting method and an automatic tracking shooting device, and the method comprises the steps: determining two to-be-tracked targets in a real-time shooting image; obtaining respective feature vector queues of two to-be-tracked targets through a human body feature algorithm, and obtaining respective reference target frame serial numbers of the two to-be-tracked targets through a target detection algorithm; based on the feature vector queue and a reference target frame serial number, matching a target frame in each frame in a subsequent real-time shot picture; if matching succeeds or partial matching succeeds, determining the position of a tracking point according to the position of the successfully matched target frame; if matching fails, the position of the fixed tracking point is the center of the current picture; and when the matching of the continuous preset frames fails, adjusting the focal length to expand the field of view of the real-time shot picture. According to the dual-target cooperative tracking mechanism, dual-target equivalent tracking is realized through parallel feature vector queues and dynamic weight distribution.

The invention provides an internal dimension marking method and device for an architectural plane graph, electronic equipment and a storage medium. The method comprises the following steps: acquiring a to-be-labeled architectural plane graph, and identifying a to-be-labeled object in an internal space of the to-be-labeled architectural plane graph; generating a size mark of the to-be-marked object based on a preset mark generation condition, and obtaining a first architectural plane graph; the first architectural plane graph comprises at least one size mark, and each size mark in the first architectural plane graph is located at an initial position; according to the initial position of each size mark, determining the movable range of each size mark; based on the movable range of each size mark, position adaptability scoring is conducted on each size mark, the position with the highest score is determined as the target position of the corresponding size mark, and a target building plane graph is obtained. According to the invention, the readability and aesthetic property of the size marking of the internal space in the building plan can be improved.

The invention discloses a sensor optimization arrangement method and system for rapid identification of physical field parameters of a tunnel with a long construction period, and relates to the technical field of underground space sensor arrangement. Sequentially establishing a tunnel geometric model, a physical model and a grid model, and setting boundary conditions to obtain a tunnel internal CFD model; verifying and correcting the CFD model in the tunnel based on the monitoring data after actual installation, and carrying out preliminary tunnel simulation by using the corrected model; and obtaining a weighted fusion mean value of tunnel physical field parameters based on a preliminary tunnel simulation result, carrying out deviation analysis on the weighted fusion mean value and a physical field parameter mean value at different heights, selecting a height range with a minimum error, and combining with a typical installation position to determine an optimal sensor layout scheme. According to the method, more accurate sensor monitoring data can be obtained by using a small number of sensors, and the identification speed and accuracy of tunnel physical field parameters are improved, so that potential safety hazards in a tunnel can be found and prevented in time.