1253 results about "Location determination" patented technology

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 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.

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.

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.

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.

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.

The invention discloses a method and device for determining distance information of flight equipment and a storage medium, and relates to the technical field of microwave landing system measurement. The method comprises the following steps: acquiring initial distance information of target flight equipment; predicting a target position of the target flight equipment at the next moment based on the initial distance information; based on the target position, determining updated distance information of the target flight device, the updated distance information being used for indicating information from the target flight device to the ground when the target flight device is located at the target position; based on the updated distance information, pulse time difference information of the target flight equipment is determined, and the pulse time difference information is used for indicating time difference information of a pulse signal sent by the target flight equipment to the ground beacon station and a corresponding response pulse signal; and determining target distance information of the target flight equipment relative to the ground beacon station based on the pulse time difference information. According to the invention, the precision of distance measurement of the flight equipment is improved.

The subject technology is related to autonomous vehicles (AV) and, in particular, to calibrating multiple sensors of an AV in an undefined training area. An example method includes instructing the AV to pilot itself in an undefined training area subject to at least one constraint, wherein the AV is instructed to pilot itself along a path until the AV has overlapped at least a portion of the path, and at a location at which the AV has overlapped at least the portion of the path, determining that first returns from a previous LIDAR scan overlaps with second returns from a subsequent LIDAR scan taken when the AV has overlapped at least the portion of the path. Initially, the AV does not include a location reference to identify locations of objects in the undefined training area and a plurality of sensors of the AV are uncalibrated with respect to each other.

This paper constructs a remote sensing sea ice dataset and, based on the characteristics of sea ice images, improves the YOLOv5 model by adding the SE attention mechanism, improving the SPP pooling pyramid structure, and replacing the SiLU activation function with the FReLU. The model's confidence is verified using evaluation metrics such as accuracy, recall, F1-score, and mean average precision, ultimately resulting in an optimal sea ice target detection model. The test set is input into the target detection model to obtain recognition results, extracting information such as the location and size of the sea ice. Based on this extracted information, a grid map is created. The starting and ending points are determined based on the ship's own position, and a path is planned using the Theta* algorithm. The generated path is evaluated using metrics such as route distance, average offset distance, number of ship turns, and number of sea ice avoidances. This paper implements sea ice recognition at a remote sensing scale, constructs simulated navigation scenarios, and plans the optimal navigation path. This paper can improve the safety of ships sailing in ice areas and provide technical support for collision avoidance and navigation decision-making assistance in ice areas.

Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle flight operations near physical structures or objects. In particular, a point cloud of the physical structure is generated using aerial images of the structure. The point cloud is then referenced to determine a flight path for the UAV to follow around the physical structure, determine whether a planned flight path to desired locations around the structure is possible, determine the fastest route to return home and land from a given position around the physical structure, determine possibility of inflight collision to surface represented in point cloud, or determine an orientation of a fixed or gimballed camera given a position of the UAV relative the point cloud.

A parking space location determination method and apparatus, a device, a medium, and a product. The method comprises: acquiring a target parking lot image collected by a target camera in a parking lot (S110); inputting the target parking lot image into a target parking space detection model to obtain a parking space center image coordinate corresponding to a parking space in an idle state (S120); and determining geographic location information of the parking space in the idle state on the basis of geographic location information of the target camera and the parking space center image coordinate corresponding to the parking space in the idle state (S130).

The invention provides a conveyor line article dynamic positioning method and system based on multi-mode distance measurement, and the method comprises the steps: responding to the start of a conveyor line, and detecting to-be-conveyed articles on the conveyor line based on a multi-source detection unit, so as to obtain various to-be-conveyed article data; performing multi-source fusion processing on the data of the to-be-conveyed articles according to a preset weight to obtain position fusion data of the to-be-conveyed articles; based on the position fusion data of the to-be-conveyed article and a preset positioning position, the positioning direction of the to-be-conveyed article is determined; and according to the positioning direction of the to-be-conveyed article, a power adjusting unit is driven to push the to-be-conveyed article to the preset positioning position. The positioning error can be improved; the misjudgment rate is reduced, and compatible recognition of to-be-conveyed objects of multiple specifications and multiple materials is achieved; the positioning success rate is improved; the detection precision is improved; and a redundancy mechanism is formed through multi-sensing fusion, so that the practicability of the system is greatly improved.

The invention provides a point cloud data processing method, a robot and a storage medium, the method is applied to the field of robots, and the method comprises the following steps: obtaining respective matching scores of a plurality of initial point cloud data, and taking a candidate initial attitude corresponding to the initial point cloud data with the highest matching score as a target initial attitude; controlling the robot to rotate to a target initial attitude and acquiring target point cloud data under the target initial attitude; dividing the target map into a plurality of sub-maps; obtaining matching scores of the sub-maps according to the candidate initial positions and the target point cloud data in the sub-maps, and taking the sub-map with the highest matching score as a target sub-map; when an iteration termination condition is satisfied, determining the candidate initial position in the target sub-map as a target initial position; and obtaining an initial reference pose according to the target initial position and the target initial pose. According to the method, the repositioning success rate and efficiency of the robot away from the original point can be improved.

In some implementations, a device may obtain, from a user device, a document image that depicts location information associated with an owner of the document. The device may obtain location information associated with the user device. The device may perform optical character recognition using the document image to obtain a location, or may scan a machine-readable code depicted in the document image to obtain the location. The device may determine a device location based on the location information. The device may determine a confidence score based on the location and the device location. The device may determine whether the confidence score satisfies a threshold. The device may perform an action based on determining whether the confidence score satisfies the threshold.

Systems, methods, and computer readable media for location determination for battery-constrained devices, where the methods performed on a system include determining a location source of a plurality of location sources to query for location data, where the determination is based on a current location, conditions of the system, and a plurality location requests from one or more applications. The methods may further include querying the determined location source, accessing location data from the determined location source, fusing the location data with the current location to generate a new current location, and storing the new current location data in a memory accessible to the one or more applications.

The invention discloses a touch detection method, a control unit, electronic equipment and a storage medium. The method comprises the steps that N actually-measured pressures collected by a pressure detection module are obtained, the pressure detection module comprises N pressure sensors which are not located on the same straight line, and each pressure sensor collects one actually-measured pressure; effectiveness analysis is carried out based on the N actually-measured pressures, and N effective pressures are determined; pressing positioning is carried out based on the N effective pressures, a target pressing position corresponding to a finger pressing point is determined, and the target pressing position is determined based on the effective pressures corresponding to any three pressure sensors which are not in the same straight line and the sensor positions; and performing finger navigation operation based on the target pressing position. The method can ensure that the positioning precision of the target pressing position determined by pressing positioning is relatively high, so that the control precision of finger navigation operation is ensured.

The invention discloses a test task execution method and device, electronic equipment and a storage medium, and relates to the technical field of server tests.The test task execution method comprises the steps that when an emergency identification parameter of a first task read from a task queue is a target value, task priority weight calculation is conducted firstly; determining a priority weight according to the position of a test object corresponding to the task, and determining path optimization cost values respectively corresponding to the first task and the currently executed second task based on the priority weight and the path cost of the intelligent mobile device from the current position to the test object corresponding to the task; when the first path optimization cost value corresponding to the first task is smaller than the second path optimization cost value of the second task, the second task is interrupted, and the first task is executed, so that the emergency task can be executed preferentially when the path optimization cost value of the emergency task is smaller without waiting for the completion of the execution of the currently executed task. The response timeliness of the emergency task is improved, and the technical problem that the path redundancy is large when the intelligent mobile device moves is solved.

A method of determining a position of a vehicle in which a reference map is provided. The reference map comprises segmentations of a reference image with landmarks. A measurement image of a vehicle environment is captured and segmentations of the measurement image and neighborhood graphs are determined to obtain a measurement map, wherein a segmentation is represented by a vertex and where a neighborhood graph comprises the vertex and edges containing information to identify neighboring vertices of the vertex. Segmentations of the reference image are compared with the segmentations represented by the vertices of the measurement image and the neighborhood graphs, and segmentations contained in the reference image and in measurement image are determined. The vehicle's position is estimated with reference to the reference map during its movement along a road based on a result of the comparison.

The invention relates to a robot real-time obstacle avoidance planning method and device, electronic equipment and a storage medium, and is applied to the technical field of robot control, and the method comprises the steps: constructing a real occupation grid map according to the position coordinates of an obstacle, and constructing an expansion occupation grid map according to the real occupation grid map. And according to the real-time position of the robot, sampling in the global trajectory according to a preset planning distance to obtain a local target position, and determining an obstacle avoidance-free guide trajectory according to the real-time position and the local target position. Determining an obstacle avoidance track to be evaluated according to the obstacle avoidance-free guide track, the obstacle avoidance parameters, the real occupation grid map and the expansion occupation grid map; and performing collision detection on the to-be-evaluated obstacle avoidance trajectory by using the expansion occupation grid map, and if no collision occurs, or if the collision occurs and the collision time is greater than or equal to the safe duration, executing a current local trajectory updating process. And if the collision occurs and the collision time is less than the safe duration, re-determining the to-be-evaluated obstacle avoidance trajectory. And the obstacle avoidance stability can be improved.

The invention discloses a multi-modal heterogeneous data management method and system, and the method comprises the steps: carrying out the preprocessing of multi-modal heterogeneous data, obtaining the preprocessing data, extracting the data information of the preprocessing data, carrying out the analysis, and determining the key data features of all data; evaluating the importance of each data based on the key data features to obtain an initial importance evaluation value; determining an association relationship among data in the preprocessed data from the data information, and constructing a knowledge graph of each data based on the association relationship; determining the position of each piece of data in the preprocessed data in the knowledge graph, and determining an evaluation value adjustment coefficient based on the position; and adjusting the importance initial evaluation value of each piece of data based on the evaluation value adjustment coefficient to obtain an importance evaluation value, and determining the storage position of each piece of data based on the importance evaluation value. According to the method, the final storage position is determined by carrying out importance evaluation on the data features of the multi-modal heterogeneous data, the data analysis and processing flow is optimized, and the efficiency and safety of data storage management are improved.

Methods, systems, and storage media for performing multi-user gaze tracking in a vehicle space using multi-surface optical reflections are disclosed. Implementations may: acquire face and eye region image data of a plurality of occupants within a field of view of at least one camera associated with a vehicle; evaluate reflected image quality thresholds; locate and match occupants within the vehicle space; and perform eye tracking for multiple occupants independently via reflected multi-view images provided to a deep learning model.

The invention provides a scenic spot navigation method, system and device based on location services and a medium, and belongs to the technical field of scenic spot navigation, the method comprises the following steps: developing a scenic spot navigation light application based on a host application, and presetting location data of each scenic spot and a dynamic distance trigger threshold configuration rule for judging the location of a user; starting a scenic spot navigation light application, and obtaining a user position and a current positioning precision parameter through a real-time position interface of a host application; executing a dynamic distance trigger threshold configuration rule, and dynamically calculating a distance trigger threshold of each scenic spot according to the scenic spot distribution density and the current positioning precision parameter; when the distance between the position of the user and a certain scenic spot is smaller than the corresponding distance triggering threshold value, staying timing is started, and corresponding voice explanation is triggered after the duration condition is met. The intelligent level and the user experience of the scenic area guide system are improved by dynamically adjusting the trigger threshold value and comprehensively considering the judgment of multi-dimensional factors such as the positioning precision, the scenic spot distribution density and the residence time.