22 results about "Dynamic localization" patented technology

The invention relates to a defect positioning method based on fusion of weld defect features and trajectory tracking data, and belongs to the technical field of weld defect detection and positioning. The method comprises the following steps: capturing welding seam track dynamic data and defect feature data, constructing a dynamic coordinate system based on a welding seam initial feature point, and establishing double-data-set reference mapping; performing multi-physics field interference decoupling correction on the trajectory data, and performing cross-modal feature purification and core feature consistency verification on the defect data; converting the preprocessed data into a feature form adaptive to fusion, and constructing a welding process-defect formation mechanism association network to regulate and control fusion weight; and finally, reconstructing a three-dimensional dynamic contour of the welding seam, calling dynamic positioning logic to position the defect, and outputting a result carrying the process-defect causal confidence coefficient. The positioning precision is improved through multi-dimensional data fusion and mechanism association, and technical support is provided for welding quality management and control.

The invention discloses a dynamic positioning precision optimization system based on a self-learning fusion model, and relates to the technical field of wireless positioning. Comprising the steps that an acquisition and synchronization module synchronously acquires AOA, RSSI and TOA signals from a plurality of anchor points and generates a synchronous multi-source signal flow; the discrimination module extracts multi-dimensional instability characteristics such as fluctuation entropy, angle jitter and delay abrupt change rate of the signal flow, and classifies the current channel environment into predefined modes such as high occlusion, non-line-of-sight error or stable line-of-sight; the mapping module calls a corresponding weight distribution strategy according to the modal identifier to generate a real-time fusion weight vector; the adaptive positioning module couples the weight vector to an unscented Kalman filter observation model, dynamically adjusts the weight of each signal source in state updating, and outputs an estimated position and a positioning confidence coefficient; the optimization module monitors the positioning confidence and iteratively optimizes the weight strategy online based on the deviation of the positioning confidence from the target value. The method effectively improves the positioning precision and robustness in a complex dynamic scene.

The invention relates to the technical field of industrial automation, in particular to an inspection path generation method and device, a storage medium and computer equipment, when an inspection path is generated, time-space synchronization can be carried out on data collected by different sensors, geometric and physical consistency of a motion track is ensured, the dynamic positioning precision is further improved, and the accuracy of the inspection path is improved. Moreover, when part of the sensors fail, the robustness of the system can be effectively enhanced through a synchronized redundant data maintenance function, and the data processing delay can be reduced through time-space synchronization, so that the real-time control requirement of a dynamic scene is met, and a map can be updated in real time according to the current environment to improve the accuracy of navigation and positioning. The method adapts to complex environments; in addition, the current positioning error can be corrected according to the target point cloud data and the target image data so as to further improve the positioning accuracy, and the relatively accurate inspection path and control instruction can be generated based on the corrected positioning result and the target map.

The invention discloses an error real-time compensation method for GNSS (Global Navigation Satellite System) dynamic positioning, which relates to the field of GNSS dynamic positioning and comprises the following steps of: obtaining a to-be-corrected track fragment with a continuous motion trend; calling the digital map data of the corresponding area from a local storage and / or a cloud server; determining one or more candidate matching roads according to the matching degree of the track course change features and the road curvature features; performing short-time dead reckoning to obtain a predicted position at the current moment; based on the road traffic direction constraint and the connectivity constraint, the projection points are verified; and taking the final corrected positioning result as a reference point of dead reckoning at the next moment, and continuously and progressively correcting the GNSS dynamic positioning error. The method has the advantages that through short-time dead reckoning prediction, dynamic positioning errors and inertia accumulation drifting are restrained, a positioning result is forced to be reasonably attached to a real road network all the time, and high-reliability, low-cost, continuous and stable dynamic positioning is achieved.

The invention relates to the technical field of industrial automation, in particular to an automatic inspection method and device in a complex environment, a storage medium and related equipment, data acquired by different sensors can be subjected to space-time synchronization to improve dynamic positioning precision, and when part of the sensors fail, a function can still be maintained through synchronized redundant data, so that the reliability of the system is improved. The robustness of the system is effectively enhanced, and the data processing delay can be reduced through space-time synchronization, so that the real-time control requirement of a dynamic scene is met; locally updating the newly acquired global map according to the static characteristics and the target attitude data, thereby reducing the calculation amount, improving the accuracy of navigation positioning, and adapting to a complex environment; the current positioning error is corrected according to the target point cloud data and the target image data, so that the positioning accuracy is further improved, and the inspection path and the control instruction are generated based on the corrected positioning result and the target map, so that the operation risk is effectively reduced while automatic inspection is realized.

The invention discloses a three-dimensional positioning method and system for a bimodal target, and relates to the technical field of indoor positioning, and the method comprises the steps: collecting the phase ranging data of a connected state base station and the received signal strength indication data of a broadcast state base station, and forming a bimodal perception data set; selecting a static positioning model or a dynamic positioning model according to the motion state of a to-be-positioned point, and converting a positioning problem into a nonlinear optimization problem based on the bimodal perception data set; and solving the nonlinear optimization problem by adopting a CBS algorithm to obtain the position estimation of the point to be positioned in the three-dimensional space. According to the method, three-dimensional positioning of a static target and smooth track positioning of a dynamic target are realized at the same time, the optimization range is effectively constrained, the system deployment complexity and the calculation load are reduced, the precision and robustness of indoor three-dimensional positioning are effectively improved, and the method is suitable for application scenes with strict requirements for quick response and low-cost deployment.

The application provides a conveying line article dynamic positioning method and system based on multi-modal ranging, comprising: in response to the start of the conveying line, detecting the to-be-conveyed articles on the conveying line based on a multi-source detection unit to obtain multiple to-be-conveyed article data; performing multi-source fusion processing on the multiple to-be-conveyed article data according to a preset weight to obtain to-be-conveyed article position fusion data; determining a to-be-conveyed article positioning direction based on the to-be-conveyed article position fusion data and a preset positioning position; and driving a power adjustment unit to push the to-be-conveyed article to the preset positioning position according to the to-be-conveyed article positioning direction. The application can improve positioning error, reduce misjudgment rate, realize compatible recognition of multiple specifications and multiple material to-be-conveyed articles, improve positioning success rate, improve detection accuracy, and form a redundancy mechanism through multi-sensing fusion, thereby greatly improving system practicability.

This invention relates to the field of data processing technology, specifically to a method for dynamic positioning of page elements based on an adaptive waiting strategy. The method involves extracting latency jitter data and combining it with the historical loading characteristics of the target page to obtain a waiting time limit. Within this limit, the method monitors the internal mounting state, visual visibility state, and layout stability state of the target node. When the internal mounting state of the target node is ready, but the visual visibility state and layout stability state assessments fail, the geometric size feature weights of the target node are stripped, and node data of the internal mounting state is extracted. An undirected graph data structure is constructed to downgrade and anchor the target node. When the target node is downgraded and its local node block is already mounted to the page node tree, the nearest ancestor node container that has completed layout rendering is backtracked as a reference to construct a safe interaction boundary. Before the overall webpage resources are fully loaded, interactive operations are performed on target nodes that have not escaped the safe interaction boundary.

This invention belongs to the field of text localization, and particularly relates to a dynamic localization method and system based on dot matrix coordinate calibration. The method involves: acquiring the dot matrix space of a target page; scanning the target page and extracting its dot matrix feature space, including dot matrix intervals, arrangement rules, preset relative coordinate relationships of points, and dot matrix intrinsic entropy; fusing the dot matrix intrinsic entropy, arrangement rules, and target dot matrix space to determine the target text information; combining text logic, character structure, preset coordinate system, dot matrix intervals, and preset relative coordinate relationships of points to calculate the target path and standard character position distribution; executing the target path and capturing the real-time position of the target characters; and using a pre-trained lightweight generative adversarial model to perform real-time pre-correction of subsequent target paths based on the deviation between the real-time position and the standard position under a preset path length, until the text target is completed. This invention effectively improves the accuracy of target text position and reduces errors through precise dot matrix coordinate calibration and dynamic path correction.

The invention discloses an intelligent cooperative reasoning character interaction detection method based on CLIP in the technical field of computer vision and character interaction. The method comprises the following steps: S1, constructing a high-quality multi-mode character interaction image data set; s2, an intelligent collaborative reasoning framework; s3, training and optimizing the model; s4, model reasoning and result output; s5, performing model evaluation and iterative optimization; according to the method, the advantages of openness and robustness of a CLIP model are deeply fused, TDA adopts a double fusion method, interactive text information and visual context are alternately integrated, and a man-machine object combination with a correct interactive relationship is dynamically positioned; the SEC is combined with three text cues to realize cross-modal alignment of vision and language; the DQM module independently extracts character features and object features from global context features through a multi-head self-attention and cross attention mechanism, and reduces the dependence of subsequent modules on redundant features through decoupling feature extraction.

The application discloses an ECU upgrade package processing method and system, comprising the following steps: downloading an ECU upgrade package from a cloud server to a local database, performing block encryption on the ECU upgrade package downloaded to the local database, obtaining a plurality of data blocks and encryption information corresponding to each data block, entering an ECU flashing task, dynamically positioning the corresponding data block according to an offset requested by the ECU, decrypting the data block based on the encryption information, sending the decrypted data block to the ECU, and sending all the data blocks to the ECU. When the ECU upgrade package is flashed, the application can support encrypted storage of the ECU upgrade package, prevent the ECU upgrade package from being stored in the local database of a diagnostic instrument in a plaintext form, and dynamically decrypt the ECU upgrade package, so that the memory occupation of decryption is low, and the memory pressure of the ECU flashing is small.

This invention discloses an autonomous driving localization method and system based on LSTM deep reinforcement learning. The method includes: performing normalization preprocessing on the complex environment of autonomous driving based on partially observable Markov decisions to obtain real-time dynamic localization results; inputting the real-time dynamic localization results into an LSTM-based deep reinforcement learning model for correction processing to obtain a position correction action evaluation value; and correcting the position of the autonomous vehicle based on the position correction action evaluation value. The system includes a prediction module, a correction module, and an application module. By using this invention, more accurate satellite positioning can be generated by considering the high dynamics, temporal sequence, and complexity of autonomous driving in complex environments. This invention, as an autonomous driving localization method and system based on LSTM deep reinforcement learning, can be widely applied in the field of autonomous driving satellite positioning technology.

A system and method are provided for determining a location of a portable device relative to an object. The system and method may include operating in two modes: 1) a first mode in which an antenna output, such as a received signal strength indicator, satisfies a mode transition criterion that is dynamic, and 2) a second mode in which, with the mode transition criterion being satisfied, the location of the portable device is determined.

The invention provides a web page testing method, device and equipment. The method comprises the steps that page information of different modes of a web page to be tested is acquired; performing feature extraction on the page information of the different modes through a multi-mode decision model, identifying at least one target element according to extracted first feature vectors of the different modes, and deciding a target dynamic positioning strategy correspondingly adopted by the target element from pre-defined dynamic positioning strategies corresponding to the different modes; determining at least one test path based on the target element, and generating a test script for the webpage to be tested based on the test path and a target dynamic positioning strategy corresponding to the target element in the test path; and based on the test script, testing the webpage to be tested, and outputting a test report. Through the method provided by the invention, the self-adaptive test script can be generated based on the dynamic positioning strategy, the elements are accurately positioned, and the test efficiency is improved.

Database systems and methods are provided for dynamic localizations of an application provided at a client device. In response to receiving an indication of a desired localization, an exemplary method retrieves metadata associated with the desired localization for one or more fields of an object associated with an application platform at a database system, retrieves one of more field values for the one or more fields of a data record corresponding to an instance of an object from the database system, and generates a GUI display associated with the application that includes a graphical representation of the data record at the database system utilizing the metadata associated with the desired localization retrieved from the database system and one or more field values for the one or more fields of the data record.

This invention proposes a trajectory generation method and voice navigation system for precise positioning in smart helmets. It belongs to the interdisciplinary technical fields of smart wearable devices, high-precision positioning, and mobile geographic information systems (GIS). The method includes: collecting raw positioning signal data, inertial measurement data, and environmental perception data during cycling using a multimodal sensor array built into the smart helmet; performing multi-source fusion preprocessing on the raw positioning signal data to generate hybrid positioning source data; constructing a dynamic positioning weight model based on the hybrid positioning source data to generate adaptive positioning source allocation results; this method improves positioning accuracy to within 2 meters in complex scenarios such as urban canyons, effectively solving the trajectory drift problem caused by traditional GNSS single-source reliance. The dynamic weight allocation mechanism can switch the optimal positioning source in real time according to the environment, significantly reducing positioning errors in scenarios with tall buildings obstructing the view or in tunnels.

Exemplary embodiments involve centimeter-accurate localization using asymmetric antennas. A pair of mobile devices can establish a wireless communication link, with one device serving as a base station and the other as a rover for real-time kinematic positioning (RTK positioning). If the mobile devices have similar asymmetric antennas for receiving Global Navigation Satellite System (GNSS) signals, the errors caused by the asymmetric antennas can be compensated for by combining the measurements of both devices. The rover's mobile device can display instructions for the user to adjust its orientation to match that of the base station's mobile device.The rover's mobile device can then receive measurement or correction data from the base station and use it to determine its position relative to the rover's mobile device. Such techniques can be performed with complementary model devices that can be used to map areas with a high degree of precision (e.g., at the centimeter level), including elevation data.

The application discloses an AR positioning system and method for engineering construction period. The application discretely collects construction site fixed feature environment nodes (the distance is not more than 10 meters) through a device with a Lidar system; the collected data grid is reconstructed and introduced into a game engine to build a space reference array which retains original coordinate information; a virtual information position is set in the array; two algorithms of grid dynamic positioning and video flow dynamic positioning are innovatively written and associated, and the starting priority of the former is set to be higher than that of the latter; when there is an environment node in the visual field, grid matching is preferentially adopted to perform accurate pose calculation and correction; when there is no node in the visual field, video flow positioning is enabled, and the grid data of adjacent nodes are used to suppress accumulated errors in time. The application effectively reduces data cost and performance consumption, and especially for complex environment in the engineering construction period, high-precision and anti-drift dynamic positioning in large-scale roaming is realized.

The invention discloses a UI element dynamic positioning method and system based on deep learning, and the method comprises the steps: collecting a screenshot, an element type and position coordinate data of a UI interface, and carrying out the rotation, zooming and noise injection enhancement of the data, thereby obtaining standard UI interface data; extracting global features of the UI image by adopting a pre-trained CNN model, strengthening feature weights of a button and an input box, outputting bounding box coordinates of a target element through a full connection layer, and establishing a deep learning model; optimizing hyper-parameters of the deep learning model by using a PSO particle swarm algorithm to obtain a target deep learning model; and inputting the standard UI interface data into the target deep learning model for prediction, and outputting the bounding box coordinates of the UI elements, so that the accuracy of UI element positioning is remarkably improved.

The invention belongs to the technical field of surveying and mapping geographic information, and relates to a field surveying and mapping collaborative operation method fusing RTK and mobile communication, which comprises the following steps of: generating a dynamic view reflecting global operation capability according to a local area network established by terminal equipment in a team; electing a crutch holder bearing responsibility of distribution of the high-precision positioning data source in the whole micro-domain; packaging and fusing into a micro-domain correction data stream with a dynamic positioning reference, and broadcasting the micro-domain correction data stream to all the crutch receivers; forming a dynamic operation situation map covering the whole staff; the designated member terminal is switched to a temporary reference station role and generates temporary local reference correction data through autonomous calculation so as to replace the micro-domain correction data flow for broadcasting; forming data time capsules arranged according to a time sequence and storing the data time capsules locally; and generating a centimeter-level precision track of the lost terminal during the lost period. According to the invention, the problem that any member becomes individual combat once entering a signal blind area due to too strong network dependence is solved.

The invention improves Global Navigation Satellite System (GNSS) accuracy using a novel hybrid approach combining Real-Time Kinematic (RTK) and Precise Point Positioning (PPP) techniques with advanced multipath mitigation. The system receives positioning data from multiple GNSS devices and uses a server-based location correction engine to process this information. It generates estimated position values and ambiguity measurements, which are then used in both RTK and PPP algorithms. The system also applies a mean-field carrier multipath mitigation technique, leveraging an ensemble solver to compute multipath-free position estimates. This approach addresses both device-specific and environmental errors, particularly benefiting consumer-grade GNSS devices. By iteratively refining position estimates and correcting for multipath effects, the system achieves high-precision positioning without relying on fixed base stations, offering centimeter-level accuracy for a wide range of applications.

The application discloses a kind of based on machine dog carries GPS dynamic mode's Gobi beach original ground re-measurement method, including step one, according to re-measurement area topography, select the elevation measurement scheme of adaptation, and carry out including GPS module, laser ranging module, leg posture perception module installation and calibration on machine dog;Step two, GPS reference station is laid out;Step three, machine dog walks along the preset walking route, carries out on-site re-measurement, and the data of corresponding module in walking process is collected in real time according to the selection elevation measurement scheme;When walking to two elevation measurement scheme switching nodes, switching measurement scheme;Step four, according to the data collected, plane coordinate and elevation data are calculated, and complete re-measurement data are formed.The application is through the high topographic adaptability of machine dog and the innovative fusion of GPS dynamic positioning, two-scheme elevation measurement technology, completely solve the safety, efficiency, accuracy pain point of Gobi beach original ground re-measurement.