62 results about "Trajectory database" patented technology

The invention relates to the technical field of RFID smart tags, and discloses an RFID smart tag positioning and tracking printing method and system, and the method comprises the steps: inputting an RFID tag radio frequency signal into a conditional variation automatic encoder for convolution processing and attention weighting, and obtaining an RFID tag global feature vector; establishing a layered sensor node network to perform multi-dimensional acquisition on environmental parameters to obtain an environmental spatio-temporal data set; inputting the global feature vector of the RFID tag and the environment spatio-temporal data set into a deep fusion network for feature fusion to obtain a multi-modal fusion feature; performing sequence modeling based on the multi-modal fusion features to obtain an article trajectory prediction model; the object track prediction model is applied to a target area grid coordinate system for density distribution calculation, a real-time object positioning heat map and a track database are obtained, an efficient object positioning heat map generation and track data management mechanism is established, and real-time position visualization and historical track query are facilitated for the system.

The invention provides a positioning and tracking early-warning method and system for a Bluetooth signal, and relates to the technical field of positioning and tracking, and the method comprises the steps: receiving a Bluetooth signal of a target Bluetooth device through a Bluetooth receiver, correcting a signal feature parameter through a signal attenuation compensation model, and combining the position coordinate of the Bluetooth receiver, the real-time position of the target equipment is calculated through a positioning algorithm, and the real-time position and the corrected signal characteristic parameters are stored in a track database; based on historical trajectory data, a space-time diagram convolutional neural network model is constructed and trained to predict a target trajectory, and an electronic fence is dynamically generated in combination with target activity rule parameters; and generating fence early warning information by comparing the prediction track and the electronic fence boundary, extracting a target behavior feature vector, identifying an abnormal behavior by using a behavior identification model, and generating comprehensive early warning information in combination with the fence early warning information.

The invention relates to a ship trajectory data mining and macro-micro fusion route prediction method and system, and the method comprises the steps: S1, extracting ship trajectory data near an inland waterway from the data of an automatic ship recognition system, and carrying out the cleaning, filtering, sorting and preliminary analysis; s2, performing clustering analysis by using the features of the ship trajectory data, preliminarily mining trajectory features in combination with manual annotation, and establishing a ship trajectory database; s3, on the basis of historical data, constructing a deep learning model aiming at the inland river driving key path nodes of the ship from a macroscopic level; s4, training a deep learning model combining a convolutional neural network and a long-short-term memory network based on historical data, and predicting a ship position track from a micro level; and S5, performing macro-micro fusion prediction on the new ship data to obtain a ship navigation path and trajectory prediction coupling result. According to the method, coupling of macro and micro prediction means is adopted, and a certain guarantee is provided for the precision of ship trajectory prediction.

The invention relates to the technical field of industrial robot control, and discloses an industrial robot trajectory optimization control method based on an intelligent algorithm. The method comprises the steps that joint position information, tool center point coordinates and a motion time sequence when a robot executes multiple tasks are collected and stored in a track database; after cleaning and screening data, extracting a feature set containing a path point sequence, speed distribution and an acceleration contour; constructing an intelligent optimization algorithm model of a neural network structure, and training by using the feature set to learn a trajectory optimization strategy; analyzing a target position coordinate and a motion constraint condition of the current task to obtain an initial track parameter; and inputting the initial parameters into the trained model, outputting an optimized track sequence containing a path point list and a speed curve, and generating a control instruction to drive the robot to move. The method can adapt to different tasks, improves track rationality and motion stability, and fits industrial production practice.

The invention relates to the technical field of logistics tracking, in particular to a shipping logistics tracking method. Comprising the following steps: detecting a signal interruption time point and duration to obtain a signal interruption interval; according to the signal interruption interval, the navigation speed, direction and position which are finally recorded before interruption of the ship are extracted from a historical navigation trajectory database, and an initial state vector is generated; predicting a future transportation path of the ship through the corrected position sequence, and generating a predicted path set; according to the prediction path set, constructing a ship motion track in the three-dimensional virtual scene, and generating a visual track model; obtaining a decision support view by combining the confidence coefficient of the reckoning position sequence; and updating a port scheduling plan in real time through a decision support view, and generating an optimized loading and unloading time sequence. According to the method, the problem that the calculation precision of the position of the ship is not high in a complex scene of signal interruption is solved, and the ship position precision and the prediction precision of a future transportation path are improved.

The invention provides a signal coverage enhancement method and system for a terrestrial digital television broadcasting transmitter, and the method comprises the steps: obtaining the position data of a train, collecting the latitude and longitude information of the train in a high-speed moving scene in real time, matching the latitude and longitude information with a preset moving track database, and determining the coordinate data of the current position of the train; according to the train position coordinate data, transmitter array distribution parameters of the corresponding section are extracted from a pre-established signal coverage database, and initial beam forming parameters of each transmitter in the corresponding section are obtained; according to the change trend of the signal coverage range, acquiring coverage blind area feedback data, determining a section with insufficient signal power density in the tunnel cutting area, and generating a coverage blind area distribution map; and according to the coverage blind area distribution diagram, adjusting parameters for executing beam forming on the transmitter array in real time, obtaining optimized signal power density distribution data, and forming a mobile coverage corridor framework.

The invention relates to a mechanical arm trajectory planning method and device and a mechanical arm, the mechanical arm comprises a base, a plurality of joints and an end effector which are connected in sequence, the method comprises the steps that a mechanical arm trajectory database is established based on a simulation environment, and the mechanical arm trajectory database comprises multiple pieces of trajectory data, the trajectory data comprises positions of a plurality of attitude points on a motion trajectory of the mechanical arm and angle data of each joint corresponding to each attitude point; obtaining a trajectory planning task, matching corresponding trajectory planning parameters with the multiple pieces of trajectory data, and obtaining at least one piece of candidate trajectory data based on a matching result; and combining the trajectory planning parameter with the at least one piece of candidate trajectory data to obtain final trajectory data, so that the problem that the motion trajectory of the tail end of the mechanical arm is not smooth is solved.

The invention discloses a photovoltaic off-grid hydrogen production system operation mode switching instant DC bus voltage stability control method, which comprises the steps of collecting a DC bus voltage signal, and reconstructing a high-dimensional phase space trajectory; calculating real geometric features such as phase space curvature and torsion of the trajectory; searching a historical similar trajectory segment in a historical trajectory database, and generating a final prediction trajectory at a future moment according to a known evolution path of the historical similar trajectory segment; and generating a feedforward control signal according to the deviation between the final prediction track and the reference voltage, and combining the feedforward control signal with traditional feedback control to form a final control instruction. The method does not depend on an accurate system mathematical model, and realizes rapid, smooth and stable control of voltage under mode switching by deeply excavating dynamic geometric information of voltage signals.

The invention discloses an intelligent debugging method and system for an LC filter, and relates to the technical field of automatic control, and the method comprises the steps: generating an initialization parameter set suitable for a debugging task of the LC filter based on a meta-learning framework; constructing a quantization particle swarm hybrid optimization debugging model; and constructing a parameter change trajectory database by combining the concept of the psychological field and a knowledge distillation technology, performing time sequence modeling on the parameter change trajectory database through an LSTM network, and predicting an optimal initial guess. The LC filter does not need to depend on a large amount of historical initial data at the beginning of regulation and control, the complex program of manual debugging is deleted, the time for carrying out initialization operation on the LC filter is greatly shortened, the difficulty of local solutions in the intelligent debugging process is solved, the convergence speed is high, the debugging time is shortened, and the debugging efficiency is improved. In the debugging process, result data is quickly and efficiently obtained on the basis of combining a small amount of historical data, and the automatic intelligent debugging process of LC can be continuously optimized.

The invention belongs to the technical field of image recognition, and provides an airport intelligent bird repelling system radar detection recognition method based on a bird flight trajectory, which comprises the following steps: obtaining sequential flight trajectory data of birds based on bird situation data of an airport area obtained by a bird detection radar in real time; based on an LSTM classifier and a recurrent neural network, classifying the time sequence flight trajectory data to obtain a bird flight trajectory recognition result; and carrying out feature value similarity matching on the bird flight trajectory recognition result and bird flight standard trajectory data in a set bird flight standard trajectory database to obtain a bird type recognition result. According to the invention, through the learning ability of the LSTM classifier and the recurrent neural network, the fine features of the flight trajectory of the birds can be accurately captured, high-precision trajectory classification is realized, and the intelligent level of an airport bird repelling system is improved.

The invention discloses a perception data processing and tracking method suitable for a low-altitude economic unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles, and the method comprises the following steps: receiving measurement data from various sensors and local state data; establishing a track for each detection target of each sensor and linking tracks of the same target from different sensors; managing tracks in the track database and finding out an optimal sensor track; according to the method, data of ADS-B, ATAR, Camera and GBSS multi-source sensors are integrated, coordinate conversion and a track association algorithm are combined, accurate recognition and tracking of cooperative and non-cooperative intrusion targets are achieved, compared with a single sensor or a simple weighted fusion method, the method has the advantages that the method is simple, and the method is easy to implement. According to the method, the missing detection rate and the false detection rate are effectively reduced, and the accuracy and the environmental adaptability of sensing data in a complex low-altitude environment are remarkably improved.

The invention relates to the technical field of data management and tracking, in particular to a file trajectory tracking method and system based on a knowledge graph, and the system comprises four modules: a data collection module is responsible for collecting detailed information of a file, a user and a PC; the knowledge graph construction module creates a knowledge graph comprising user nodes, file nodes and PC nodes according to the collected data, establishes relationship edges among the nodes according to file operation behaviors, marks operation types, time and PC information, and optimizes node feature representation by using spectrogram convolution operation; the track recording module is responsible for recording and storing newly generated operation behavior information to the track database; after receiving a tracking request, the trajectory tracking module preprocesses the knowledge graph through a spatial graph convolution operation, aggregates related operation information to update node representation, and further accurately backtracks a motion trajectory of a file in the knowledge graph; the technology provides powerful support for the fields of file management, security audit and the like, and has a wide application prospect and an important practical value.

The invention discloses a medical instrument equipment position dynamic trajectory tracking intelligent management system, and relates to the technical field of medical equipment management.The medical instrument equipment to be managed is tagged and labeled through a trajectory data mining unit, and a trajectory database is mined based on equipment position features; the multi-element management construction unit is used for constructing an intelligent management block by combining the track database according to multi-element management dimensions; an equipment tracking and state analysis unit receives equipment updating information, performs equipment tracking and state analysis in combination with the intelligent management block, and generates an equipment data stream; and the equipment position management unit reversely acts the equipment data flow on a plurality of functional modules to perform equipment position management. According to the method and the device, the technical problems that the position and the real-time state of the equipment cannot be obtained in time due to low management efficiency and poor real-time performance of the medical instrument in the prior art, and the use and the maintenance of the equipment are influenced are solved, and the real-time performance, the accuracy and the management efficiency of the medical instrument management are improved.

The present disclosure provides a trajectory data processing method, device and equipment of a road network map, belonging to the technical field of computer information processing, solving the problem that the trajectory data of the road network map is prone to appear stuttering phenomenon when displayed in a three-dimensional scene, resulting in poor visualization effect. The method comprises: determining a spatial road network model according to a source file in the road network map; generating a trajectory database according to trajectory data in the road network map; correcting trajectory points in the trajectory database according to the spatial road network model to obtain corrected trajectory point data. The technical scheme of the present disclosure can make the trajectory data of the road network map more clear and smooth when displayed in a three-dimensional scene.

The invention discloses a method for calculating the motion trajectory and speed of a battery by using a three-axis gyroscope, comprising the following steps: step one, establishing an initial operation library; step two, updating the operation library data; step three, establishing an initial trajectory; step four, optimizing the trajectory path; step five, establishing a speed model; step six, refining the model nodes; and step seven, calculating the speed at a time point. The invention collects the running angular velocity of the battery by using a three-axis gyroscope, and then restores the running trajectory of the battery by calculating the attitude angle, thereby ensuring the accuracy of the established motion trajectory, and obtaining the battery speed direction at a corresponding time node by performing curvature optimization on the established running trajectory, thereby improving the practicability of the calculation method, and refining the nodes on the battery running trajectory and establishing a trajectory database, and then using the speed point data adjacent to a specific time point to calculate the instantaneous speed at a specific time, thereby meeting complex actual detection requirements.

The invention discloses a forest region disaster risk assessment method based on machine learning, and relates to the technical field of forest region disaster risk assessment, and the method comprises the steps: S1, building a forest region disaster evolution trajectory database, carrying out the modeling of historical disaster events according to a time sequence, analyzing the similarity between the current forest region environment characteristics and historical disaster trajectories, and obtaining a forest region disaster evolution trajectory database; deducing disaster types and focus points of attention, and clustering disaster features to form a risk category set; according to the forest disaster risk assessment method based on machine learning, the disaster risk condition can be displayed with higher information density and a clearer structure, so that the risk identification speed is improved, the understanding burden caused by information overload is reduced, and the accuracy, interpretability and response efficiency of forest disaster risk assessment are remarkably enhanced on the whole.

The present invention relates to a phased array tracking method based on four-dimensional joint weighted dynamic pre-switching, and belongs to the field of phased array communication technology. The present invention includes: updating the spatiotemporal correlation parameters to the target historical motion trajectory database, generating the target state prediction value based on the UKF prediction method; starting the four-dimensional joint gradual weighting program, performing linear phase interpolation in the time delay dimension, and generating a phase-continuous control signal; solving the mutual coupling matrix, establishing a cross-array phase mapping model based on cubic spline interpolation, and compensating for the residual phase error; dynamically adjusting the number of effective array elements participating in beam synthesis according to the real-time radar scattering cross section, generating the final beam pointing signal, and completing the stable relay tracking of the current cycle. The present invention solves the problems of phase jump and signal attenuation during multi-array switching, and is suitable for continuous tracking of UAVs in high-speed moving scenarios.

The invention relates to the technical field of building thermal environment regulation and control, and discloses a building ventilation thermal load regulation and control method and system based on thermal plume prediction, and the method comprises the steps: constructing a curtain wall surface three-dimensional coordinate system and a thermal state temperature map, and obtaining a current thermal plume trajectory; similar trajectory matching is carried out in combination with a historical thermal plume trajectory database, and a thermal plume development path is predicted; based on a prediction result, establishing a compensation relationship between a floor load grading sequence and an adjacent floor feed-forward temperature, implementing time sequence dislocation dimming through spiral progressive control, and after time sequence dislocation dimming, performing thermal-optical coupling feedback correction; hot air can be effectively prevented from flowing backwards, the high-rise room temperature and the air conditioner load are reduced, indoor natural lighting is guaranteed, the building thermal environment is optimized, and building ventilation thermal load efficient regulation and control are achieved.

The invention relates to a method and system for machining small holes in a transparent hard and brittle material and an intelligent terminal, and relates to the technical field of laser machining. Searching a corresponding concentric circumference scanning track from a preset track database based on the punching diameter; acquiring laser parameters and galvanometer parameters; searching a corresponding period distribution diagram from a preset parameter database based on the galvanometer parameters; calculating pulse interval time based on the pulse repetition frequency; determining jump time based on the pulse interval time and the period distribution diagram; adjusting the laser parameter based on the jump time to obtain an actual laser parameter; and performing a vector dotting process on the perforated material. The laser drilling device has the advantages that the jumping time is set, so that each pulse falls within the moving stable period of the galvanometer, and the laser drilling stability is improved.

The application discloses an indoor and outdoor seamless connection positioning switching method and system based on trajectory prediction and fingerprint verification, and the method comprises the following steps: S1, a virtual simulation environment is established at the building entrance, random trajectories and reward guide trajectories are generated, and a trajectory database is established; a fingerprint database is established; S2, feature extraction is carried out based on the trajectory database, and a support vector machine (SVM) model is used for binary classification training; S3, a sliding window is set, real-time pedestrian trajectory data is input into the SVM model for sliding prediction, and it is judged whether the SVM is continuously triggered in the window; S4, multi-modal fingerprint matching is started, and it is judged whether the fingerprint matching is successful; and S5, switching from a GNSS positioning mode to an indoor positioning mode is executed, and indoor and outdoor seamless connection positioning switching is realized.

The present disclosure relates to a flight trajectory prediction method of an aircraft, and relates to the technical field of hypersonic aircrafts, and the method comprises the following steps: determining a raw trajectory database of a hypersonic aircraft under different initial states and different flight control laws based on a motion equation; training a network model to be trained based on the raw trajectory database to obtain a current trajectory prediction model; determining a trajectory prediction model to be migrated from the current trajectory prediction model according to a target flight trajectory of an aircraft to be predicted and a raw flight trajectory in the raw trajectory database, and migrating model parameters in the trajectory prediction model to be migrated to a trajectory prediction model to be corrected; performing parameter correction on the trajectory prediction model to be corrected based on the target flight trajectory to obtain a target trajectory prediction model, and predicting a flight trajectory of the aircraft to be predicted based on the target trajectory prediction model. The present disclosure improves the accuracy of the predicted flight estimation.

This invention discloses a multi-target flight trajectory recognition device based on dual-channel pre-training, comprising a flight trajectory database, an aircraft radiation source receiver, and a host computer connected to each other. The database stores flight trajectory signals of different types of aircraft. The host computer includes three modules: self-supervised pre-training, supervised training, and flight trajectory recognition. The data in the database is used to perform self-supervised pre-training and supervised training on the flight trajectory recognition model, and the trained model is stored in the flight trajectory recognition module. The receiver receives external flight trajectory signals and transmits them to the flight trajectory recognition module of the host computer for recognition. This invention innovatively introduces a self-supervised pre-training stage to pre-train the flight trajectory recognition model to fully explore its inherent features and enhance its anti-interference capability. Simultaneously, it analyzes the flight trajectory signal from both the time and frequency domains to maximize the extraction of multi-domain and multi-dimensional information from the signal, significantly improving the accuracy of flight trajectory recognition.

The invention provides a method for determining lane information, and relates to the technical field of artificial intelligence, in particular to the technical fields of map navigation, automatic driving, intelligent traffic and the like. The method comprises the following steps: determining current map lane information corresponding to the current position of a vehicle from a high-precision map; determining current visual lane information corresponding to the current position from a visual image acquired by the vehicle; in response to determining that the current visual lane information is inconsistent with the current map lane information, correcting the current visual lane information according to lane information in a pre-constructed track database to obtain corrected current visual lane information; and in response to determining that the corrected current visual lane information is consistent with the current map lane information, generating target lane information corresponding to the current position. The method improves the accuracy of the lane information.

An embodiment of the present invention discloses a method and system for visual management of bus travel combined with positioning technology. The method includes: obtaining real-time vehicle positioning data of a target vehicle, extracting task execution information associated with the real-time vehicle positioning data, performing dynamic trajectory fitting processing on the real-time vehicle positioning data, generating a driving trajectory map that matches the task execution information, performing multi-dimensional analysis on the driving trajectory map based on preset task rules, and determining driving state characteristics and task completion indicators of the target vehicle; performing spatiotemporal correlation mapping on the driving state characteristics, task completion indicators, and the driving trajectory map to generate a visual dynamic management interface; in the running state of the visual dynamic management interface, in response to a tracing instruction triggered by a management terminal, calling a historical trajectory database to perform backtracking optimization processing on the driving trajectory map, and outputting management feedback data including abnormal event annotations and path comparison results.

This invention discloses a safety monitoring method for operating equipment, applied to an automated warehouse system, which includes a Warehouse Management System (WMS), Automated Guided Vehicles (AGVs), and a guidance and positioning device. The method includes: collecting data on AGV operating status, warehouse environment, WMS tasks, and the mechanical status of the guidance and positioning device; constructing a standard path model based on a historical trajectory database and calculating real-time trajectory deviation; constructing a multi-dimensional risk assessment model to comprehensively calculate the risks of the AGV itself, the environment, the task, and the guidance and positioning device; classifying risk levels according to the comprehensive risk value, implementing differentiated early warning and response measures, and dynamically adjusting AGV task allocation in conjunction with the WMS system. This invention also integrates an automatic monitoring function for near-expiry goods, enabling near-expiry identification, AGV dispatching, and automatic sorting and disposal. This invention achieves comprehensive, three-dimensional monitoring from equipment safety to cargo safety, improving the safety and intelligence level of warehouse operations.

This invention provides a vehicle trajectory extraction method based on the complementarity of LiDAR and video technologies, comprising: constructing an integrated radar device; identifying key targets based on video acquisition data collected by a high-definition video device, and constructing a basic image information database through image optimization and data filtering; converting radar data into readable road and vehicle information based on the LiDAR acquisition device, and constructing an object and behavior database for target identification; fusing the object and behavior database and the basic image information database, and constructing a driving behavior detection dataset to achieve road element calibration, vehicle element calibration, and behavior parameter calibration; identifying and tracking the calibrated objects, thereby outputting a trajectory database. This invention can provide a data foundation for road traffic operation and risk identification, and provide a scientific basis for traffic management departments to evaluate and manage road traffic.

The application discloses a trajectory database creation method and device, a query method, a vehicle, a medium and equipment, and belongs to the field of data processing. The method comprises the following steps: constructing an index based on a spatial position for each road center point in a base map, obtaining first related field information about each road center point, and generating a map database; constructing an index based on a spatial position for each trajectory point, and obtaining second related field information; binding each trajectory point in each trajectory with a road center point in the base map, and filling the second related field information of each trajectory point based on the map database; and generating a trajectory database by using the second related field information of each trajectory point and the first related field information in the map database. According to the application, the content in the trajectory database can be changed according to specified conditions, without the need to read into memory or regenerate the database, so that time is saved, the result can be reused, and the features of roads or trajectories can be quickly extracted according to positions.

The invention belongs to the technical field of fractal knowledge display, and relates to a fractal display method and system based on user behavior analysis, and the method comprises the steps: obtaining the initial distance information of a user relative to a display region, the initial reflection signal frequency of a radar induction device, and the frequency of a transmitter through the radar induction device; the somatosensory camera obtains initial action posture information of the user; constructing a user action and track database; obtaining initial user action and trajectory parameters; initial user action and track parameters are taken as reference, subsequent distance information of the user, reflected signal frequency of the radar sensing device and transmitter frequency are acquired based on a timestamp, initial action posture information of the user is acquired by the somatosensory camera, and a data set is formed; the method has the advantages that the action and track parameters and the action posture information of the user are automatically obtained, and corresponding music and explanation are played for the user to attract the user to watch parting display.

The application discloses a trajectory similarity analysis method based on trajectory compression and clustering. Firstly, N reference trajectories are compressed, and some trajectory data is removed within a certain error range, so as to facilitate subsequent processing and analysis. Secondly, the range of trajectory segments participating in calculation is reduced by intercepting common trajectories and angle pre-judgment, and the reference trajectory data is clustered offline. When calculating the similarity matrix, the similarity of each two trajectories only needs to be calculated once within the error range to reduce the complexity. Finally, the representative trajectory of each cluster is found, the similarity of the to-be-matched trajectory and the representative trajectory of each cluster is calculated, and whether the to-be-matched trajectory exists in the reference trajectory database is judged. If the to-be-matched trajectory exists in the reference trajectory database, the trajectory similarity of the to-be-matched trajectory and each reference trajectory of the corresponding cluster is calculated, so that it is determined that the actual trajectory is similar to which reference trajectory, and a similarity result is obtained.

The invention relates to a mechanical arm trajectory planning method and device based on reinforcement learning, equipment and a medium. The method comprises the following steps: acquiring a real-time pose parameter, a target pose parameter and a state transition parameter of the mechanical arm; on the basis of the real-time pose parameter, the state transition parameter and the target pose parameter, transferable trajectory information is identified from a historical trajectory database; environment obstacle distribution label information of the mechanical arm is obtained, and a trajectory planning reinforcement learning model of the mechanical arm is selected based on the environment obstacle distribution label information; and the transferable trajectory information is input into a trajectory planning reinforcement learning model matched with the environment obstacle distribution label information, and real-time trajectory information of the mechanical arm is generated. By the adoption of the method, the defects of traditional trajectory planning in dynamic environment adaptability, calculation efficiency and generalization ability can be overcome by fusing real-time sensing, historical data migration and dynamic model matching, and efficient and safe operation of the mechanical arm in an unstructured scene can be achieved.