40 results about "Localization system" patented technology

Systems and methods for improving label localization are disclosed herein. An exemplary system comprises: a plurality of labels configured to transmit data in response to requests; and a gateway that queries the plurality of labels at an initial query rate. The gateway can be configured to: receive an initial request; in response to receiving the initial request, transmit a signal to the plurality of labels causing a first subset of the plurality of labels to transmit the data at a second query rate that differs from the first query rate; and receive the data from a second subset of the plurality of labels at the first query rate.

This invention relates to the field of defect detection technology, specifically to a high-voltage cable defect location system and method based on a two-dimensional ultrasonic array. The system includes a signal main peak acquisition module, a lateral deviation calculation module, an excitation timing optimization module, a main peak spatial focusing module, and a focusing area control module. This invention utilizes a multi-element spatial collaborative acquisition method of a two-dimensional ultrasonic array. It constructs a signal spatial mapping relationship through the main peak timing characteristics, combines path difference parameters to achieve fine analysis of the propagation characteristics of multi-source signals, optimizes the excitation timing and array spatial response structure by adjusting the excitation sequence, periodically determines spatial convergence indices, identifies the main peak focusing state of the defect area, and dynamically adjusts the element weight distribution to improve the signal response capability of specific spatial areas. The spatial location of the defect area is thus clearly distinguished, effectively improving the resolution and accuracy of multi-point defect location in complex cable structures.

This invention relates to the field of optical inspection technology, specifically to a micro LED wafer-level rapid defect localization system based on photoluminescence. A broadband pulse excitation module outputs pulsed laser light matching the characteristics of the material under test; a two-dimensional scanning platform carries the wafer and achieves nanometer-level precise positioning; a time-resolved acquisition module collects fluorescence signals and converts them into time-resolved photoluminescence data; a data processing and control module synchronously controls the operation of each module, receives and processes the time-resolved photoluminescence data, extracts the transient luminescence intensity and carrier lifetime of each detection point, compares the two-dimensional feature vector formed by these two parameters with a preset defect feature database, identifies the defect type of each micro LED chip, and generates a wafer-level defect fingerprint spectrum. This system can accurately distinguish different types of failure modes such as epitaxial defects, surface state defects, and poor electrode contact, significantly improving detection efficiency and defect classification accuracy.

The present application relates to the technical field of medical data processing, in particular to a kind of lung nodule preoperative virtual positioning system assisted by augmented reality glasses, including memory and processor, the processor executes the computer program stored in the memory, to realize: the construction of lung lobe tubular structure lung lobe tubular structure chart;According to the distance distribution between nodes and blood vessel attribute information, the basic attribute parameter of each edge is obtained, the current surface gripping point and lesion center point are acquired;Obtain transverse attenuation factor and axial projection factor, determine the deformation resistance weight of each edge in combination with basic attribute parameter;According to the deformation resistance weight of the edge accumulated between the nodes corresponding to the current surface gripping point and lesion center point, the deep displacement transmission degree is obtained;According to deep displacement transmission degree and the pulling direction of surgical instrument, the lesion center point position is corrected to obtain the corrected lesion position.The present application ensures that the virtual nodule rendered in AR glasses is accurately matched with the position of deep real lesion.

This invention discloses a landmark matching PDR positioning method in multi-intersection scenarios, belonging to the field of indoor positioning technology. The method enhances landmark credibility by constructing landmarks through multi-dimensional information perception. Simultaneously, by adaptively extracting landmarks with different spatial features, this method is applicable to various landmarks, such as some unconventional intersections. Furthermore, this application uses different thresholds to define the radius of influence of different landmarks, solving the localization system mismatch problem caused by traditional single-location detection of landmarks, thus improving positioning accuracy to a certain extent. This application also further improves positioning accuracy by incorporating heading weights into trajectory similarity metrics, achieving dual correction of the position and heading of moving targets.

This application discloses a cross-view instance representation learning and retrieval localization system and method, relating to the fields of computer vision, multi-view perception, and multimodal intelligent understanding. The cross-view instance representation learning and retrieval localization system includes: an input module, a target representation module, a candidate construction module, a reference building module, a relation encoding module, a semantic encoding module, a semantic fusion module, and a matching discrimination module. The cross-view instance representation learning and retrieval localization method includes the following steps: S100, data acquisition and preprocessing; S200, obtaining the target instance representation; S300, constructing a candidate instance set; S400, constructing a structural relation representation; S500, obtaining the fused semantic representation; S600, outputting the target localization result. This application outputs target localization results more accurately under complex task conditions, significantly improving the accuracy and stability of cross-view instance retrieval localization.

This invention relates to the field of UAV swarm cooperative localization technology, specifically to a UAV swarm cooperative localization method for non-cooperative radiation sources. The method includes: constructing a UAV swarm cooperative localization system model; building a semantically driven BDI clustering mechanism based on the output lightweight semantic features and semantic consistency matrix; performing message-passing neural network cooperative inference and parameter updates based on the cooperative topology; iteratively selecting the optimal cooperative node set using a semantic utility-driven long-distance meta-path progressive search strategy; and performing MPNN cooperative inference and model closed-loop updates based on the optimal cooperative node set, ultimately outputting the final position estimate of the non-cooperative radiation source target. This invention solves the problems faced by existing large-scale UAV swarms in non-cooperative radiation source localization, such as difficulties in signal aliasing disambiguation, low cooperative efficiency under non-independent and identically distributed data, and inaccurate node selection strategies.

Systems / techniques that assess quantum device quality using many-body localization are provided. In various embodiments, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. In various embodiments, the computer executable components can comprise a characterization component that can characterize qubits of a quantum device. In various aspects, characterizing qubits of the quantum device can comprise executing, on the quantum device, quantum circuits with many-body localization (MBL) in parallel to cover a topology of the quantum device.

This invention provides a vehicle 3D localization method, device, vehicle, and storage medium based on monocular vision. It acquires images in real-time from a monocular camera, processes them using a multi-task recognition model to obtain first target information, acquires parameter information corresponding to the monocular camera, and calculates second target information of the target vehicle based on the first target data. Finally, it tracks the target vehicle based on the second target information. Even in environments with limited texture, it can obtain camera poses with high accuracy, thereby achieving high-accuracy vehicle poses. This reduces the impact of environmental texture variations on vehicle localization, significantly improving the robustness of the vehicle localization system. By using the same scale feature layer for vehicle sideline detection and vehicle detection, each feature point corresponds to a set of detection results, eliminating the need for subsequent matching and improving target tracking efficiency.

This application provides a method and apparatus for identifying HPV integration into newly formed chromatin loops, relating to the field of bioinformatics. The method includes: acquiring interaction sequencing read data and determining HPV reference sequences and host reference sequences; identifying HPV integration breakpoints based on chimeric read characteristics, split read characteristics, and abnormal pairing end characteristics; constructing fusion contigs based on breakpoint directions to obtain a breakpoint-aware extended reference set; comparing the interaction sequencing read data with the breakpoint-aware extended reference set, and obtaining high-confidence cross-genomic anchor pairs based on breakpoint-aware alignment constraints; clustering the anchor pairs and screening target HPV-loops; calculating the newborn score of the target HPV-loop and outputting the chromatin loop identification result. This application solves the problem of low accuracy and identification bias that often occurs in traditional interaction localization systems during the identification of newly formed chromatin loops.

This invention provides a target localization system and a target localization method, relating to the field of image processing. According to an embodiment of the invention, an image of a target area is acquired using at least one image acquisition device; the image coordinates of a target object in the image are obtained using an image processing module, and the image coordinates are transformed to obtain the spatial coordinates of the target object; the spatial coordinates of the target object are displayed on a map corresponding to the target area using a result display module. By displaying the spatial coordinates of the target object on the map corresponding to the target area, the distribution of the target object within the target area can be seen intuitively and accurately.

Airborne contaminant detection and localization systems include an HVAC system having a duct, a first vent connected to a first indoor space, and a second vent fluidly connected to a second indoor space, with the second vent being downstream from the first vent in a flow direction along the duct. A monitoring system includes a first and second sensor elements arranged proximate the first and second vents, respectively, the sensor elements configured to detect one or more airborne contaminants. A central unit receives sensor data from the sensor elements. The central unit includes information regarding a location of each of the sensor elements within the duct. The central unit determines the presence and intensity of an airborne contaminant in the duct from the sensor data and establishes a detection zone that includes a portion of the vent having a highest detected intensity of the airborne contaminant.

The application discloses an image feature matching localization system and method. After processing a plurality of input images (having a local image with an unknown location and a plurality of global images with known locations) through feature analysis and feature matching, the localization result of the local image are outputted. This localization result indicates the corresponding partial contour region of the local image and the matching partial contour region of the global image.

The application discloses a kind of localization system Web browser plug-in cross-browser window adaptation and tailoring method, belong to security video playing technical field.The purpose is to solve the problem of unstable plug-in cross-browser embedding and dynamic display out of bounds under localization system.The method first binds through multidimensional browser environment identification and dynamic parent window, to ensure that plug-in is accurately attributed in a variety of browsers;Then, based on the visual area boundary parameters dynamically issued by the browser, the main window of the plug-in and the floating layer window on it are executed in a dependent manner: first, the out-of-bound main window is first cut, and then the floating layer window is secondly constrained and cut according to the cutting result.The application realizes the stable embedding of plug-in in multi-browser environment and accurate display control under dynamic interaction, effectively eliminates visual error and interface occlusion.

The application relates to the technical field of aviation communication, and discloses a fault evaluation and positioning system for aviation communication, which comprises a communication link data acquisition module, an anomaly detection and fault classification module, a multi-source data fusion fault positioning module, a fault risk prediction and hierarchical early warning module and a fault repair and network optimization module. Through real-time data acquisition, anomaly detection and multi-source data fusion, the application can quickly identify and accurately position aviation communication link faults, utilize time difference positioning and Kalman filter optimization results, combine fault risk prediction and hierarchical early warning, provide accurate repair suggestions and network optimization schemes, and improve the stability and operation and maintenance efficiency of the communication link.

This invention discloses a broadband scattering source cooperative localization system based on an underwater sensor network, belonging to the field of underwater sensor network localization technology. It includes: a distributed underwater sensor node group deployed in the underwater monitoring area to collaboratively acquire underwater acoustic signals from broadband scattering sources; a parameter initialization and configuration module; a spatial-frequency domain joint signal modeling module; a collaborative substrate reconstruction module; a sampled signal preprocessing module; a low-rank constraint optimization solution module; and a scattering source parameter calculation module, which calculates the localization parameters of the broadband scattering sources based on the solved spatial-frequency joint distribution density matrix. This system effectively corrects the attenuation differences of broadband signals, improves signal quality, and thus improves localization accuracy. Through dynamic node position calibration and dynamic adjustment of the calibration period according to ocean current velocity, it can effectively track node movement, ensuring real-time node position and avoiding localization errors caused by node movement.

The present invention relates to a method and device for controlling a vehicle (100) embedded in a localization system. The localization system (100) is configured to determine a first position of the vehicle (10) via a first geolocation system and a second position of the vehicle via a second geolocation system different from the first geolocation system. The method and device make it possible to verify a robustness objective for the localization system (100) quantified in terms of the maximum acceptable occurrence of a positioning error beyond a predetermined threshold. Figure 1

The presently disclosed subject matter includes a magnetic-based self-localization system, method, and computer-readable memory device for determining the position of a platform or navigator using a magnetic field source. Unlike conventional magnetic navigation methods that require direct measurement of the magnetic gradient tensor (G), the disclosed approach eliminates this dependency by utilizing the relationship between linear velocity and the measured magnetic field. The technique enables real-time computation of relative position r from measured magnetic field, angular velocity, and linear velocity data.

This application relates to target tracking and provides a multi-target tracking method. It acquires measurement data of the target to be tracked using at least two sensors to obtain a first set of measurement data pairs. Then, based on preset constraints, related measurement data pairs in this first set are eliminated to obtain the true target. Next, the starting point of the true target's trajectory is determined using an FCM algorithm and the measurement data pairs of the true target. Then, the true target is correlated using the FCM algorithm and the real-time measurement data of the true target to obtain a stable trajectory. Finally, the true target is tracked based on the starting point and the stable trajectory. This application eliminates false targets using preset constraints and obtains the starting point of the trajectory based on the FCM algorithm in the trajectory initiation part, and uses FCM to determine the stable trajectory of the true target in the trajectory correlation part, thereby achieving the tracking of the true target with short processing time and fast tracking speed.

This invention relates to the field of image processing technology, and more particularly to an on-orbit target velocity localization system and method based on integral images and a single-scale sliding window. A data downsampling unit downsamples a high-resolution on-orbit image; a binarization unit binarizes the downsampled image to obtain a low-resolution binarized image; an integral image generation unit scans the binarized image and performs an integration operation to obtain an integral image matching the binarized image; a sliding window search and decision module traverses the integral image using a window, calculates the total number of pixels within the window, and outputs the optimal position coordinates of the target in the on-orbit image within the integral image; a coordinate transformation module converts the optimal position coordinates in the integral image into coordinates in the high-resolution on-orbit image, obtaining the actual positioning coordinates of the target in the on-orbit image. This invention decouples the computational cost of two-dimensional region statistics from the window size, and combined with dimensionality reduction preprocessing, achieves a significant improvement in computational efficiency and a reduction in memory usage.

This application provides an intelligent parathyroid gland identification and localization system based on ultrasound imaging, comprising: an image recognition module configured to acquire real-time ultrasound image sequences and output at least one suspicious target region and its corresponding preliminary identification result; a knowledge base module storing a parathyroid gland identification rule base constructed based on medical prior knowledge; an interaction module receiving the suspicious target region and its corresponding preliminary identification result; extracting image context features of the suspicious target region and matching them with verification rules in the knowledge base module; when a target verification rule conflicting with the preliminary identification result is matched, generating an interactive verification task to guide the user to confirm specific image features; receiving user feedback information on the interactive verification task through a user interface; and a result correction and output module connected to the interaction module for dynamically correcting the identification result of the suspicious target region.

This application primarily relates to the field of UAV detection and positioning technology at docks, specifically to a UAV detection and positioning system and method. The UAV detection and positioning system provided in this application includes: a satellite positioning module for acquiring the UAV's original global positioning coordinates; a structure perception module integrated on the UAV for collecting data on the steel structure to be inspected; a data fusion module communicatively connected to both the satellite positioning module and the structure perception module for generating corrected positioning coordinates; and a flight control module for generating flight control commands based on the corrected positioning coordinates to guide the UAV in inspecting the steel structure. Ultimately, this achieves stable, high-precision absolute positioning of the UAV in complex environments.

A localization system can be validated by: obtaining log data descriptive of a plurality of environmental and operational conditions associated with operation of the autonomous vehicle in an environment; augmenting the log data with one or more simulated anomalies; simulating operation of the localization system using the augmented data as input; obtaining simulation result data descriptive of a state of the localization system subsequent simulating the operation of the localization system; and determining a metric associated with the localization system based on the simulation result data.

This invention relates to the field of endoscopic image analysis technology, specifically to an intelligent recognition and lesion localization system for digestive endoscopy images. The system includes an endoscope posture analysis module, an image posture matching module, a mucosal texture displacement module, an image rotation correction module, and a lesion coordinate localization module. Based on an electronic endoscope, it analyzes the corresponding sampling times recorded by the voltage of the angle detector of the endoscope's steering control unit and compares the continuity of preceding and following sampling segments. This invention constructs a sequence of lens posture changes by analyzing the voltage trend of the angle detector, pairs the posture records with the acquisition sequence to form an association identifier, and combines this with the tracking of the mucosal texture displacement vector to evaluate the lens steering relationship. Using this as a reference, it calculates the viewing angle offset compensation amount and corrects the cavity wall center position. Furthermore, it adjusts the contour connection relationship of adjacent frames within the chromatic transition region, effectively overcoming the field of view variations and tissue spatial misalignment defects caused by endoscope movement, and ensuring the baseline stability of boundary mapping in continuous images.

This invention relates to the fields of computer vision, deep learning, and medical image processing technology, specifically to a rapid multi-target detection and localization system for foot medical images based on an improved YOLO architecture. The system comprises four main modules: processing, inference, verification, and output. The processing module performs image compliance matching and sharpness assessment; the inference module loads an optimized YOLOv11 pre-trained model and adapts it to scene parameters; the verification module constructs a complete process system of "confidence screening – anatomical compliance verification – repeatability verification"; and the output module accurately outputs standardized results or anomaly alerts. This invention achieves precise and stable localization of key anatomical points in the foot, with traceable and reusable localization data, meeting the stringent requirements of forensic medicine and judicial identification scenarios for core data in foot arch injury assessment.

Systems and methods described herein include implementation of road surface-based localization techniques for advanced vehicle features and control methods including confidence-based consumption, air suspension control systems and methods, end of travel management, road profile creation techniques, and others.

Various aspects of visual servoing based on use of a generative diffusion model are described. One technique includes obtaining a current view image from a robot camera that captures a portion of an environment of the robot, and obtaining a spherical image from a previous view that depicts a surrounding area of the environment of the robot. The current view image is combined with the previous spherical image to produce a modified spherical image, and inpainting is performed in a mask area of the modified spherical image with a generative diffusion model. The inpainting blends the current view image with the previous spherical image, providing a view of the entire environment of the robot that can be used for visual servoing. The robot can perform path planning and visual servoing of an end effector based on the modified spherical image, independent of any use of an external positioning or localization system.

This invention discloses a vulnerability cause localization method based on an intelligent debugging agent. The aim is to use a debugging agent to debug programs based on crash samples, mine dynamic information during the debugging process, and provide further debugging instructions to accurately locate the vulnerability and output its cause. First, a vulnerability cause localization system based on an intelligent debugging agent is constructed. The system's debugging strategy guidance module selects breakpoint debugging, debugging information analysis, or vulnerability location confirmation strategies as debugging strategies through a round-robin mechanism. The debugging experience memory module introduces experience activity, enabling the large language model to continuously learn and evolve its knowledge, significantly improving the accuracy of locating and causing new vulnerabilities. This reduces the traditional "vulnerability discovery → manual debugging → location report" cycle of several days to minutes, effectively solving the efficiency problem between automated vulnerability discovery and manual debugging. This invention enables fully automated and accurate vulnerability cause localization.

The invention relates to an indoor localization system for a wireless communication network. The system comprises: one or more anchor devices, a central entity, and one or more tag devices. Transmission of signals by the one or more tag devices is controlled so that one signal is transmitted at a time on given radio resource, wherein the tag device transmitting said one signal is the tag device being localized. At least one anchor device is configured to: receive, the signal transmitted by the tag device being localized; determine an estimate of a direction of arrival (DOA) based on the received signal by applying a first power method-based algorithm and a second power method-based algorithm respectively and send the estimated DOA together with DOA metadata to the central entity. The invention relates also to indoor localization methods, an anchor device, a computer program, and a computer readable medium.

This invention belongs to the field of robot localization and multi-sensor fusion technology, specifically relating to a localization method for adsorption-type mobile robots in sparse feature environments suitable for large and complex curved surface operations. It employs a 360° surround-view perception system and simultaneously constructs multiple sets of binocular visual inertial odometry front-ends, obtaining accurate and stable relative positioning information for the robot without relying on external sensors. By constructing a redundant and complementary visual observation system through a multi-view surround-view system, it overcomes the problem that existing single or binocular visual inertial odometry systems struggle to achieve stable and continuous feature point acquisition and visual pose estimation in such scenarios. The localization system of this invention has a low overall cost, good compatibility with the main structure of adsorption-type mobile robots, and is suitable for applications of adsorption-type mobile robots in the manufacturing and maintenance of large curved surface components such as aircraft and wind turbine blades, providing the robot with real-time, accurate, and stable relative pose information.