207 results about "Ambiguity resolution" patented technology

The invention relates to the technical field of natural language processing, in particular to an intelligent customer service system based on natural language processing, which comprises a dynamic term ambiguity resolution module, a context intention chain construction module, a domain emotion vectorization module, a compliance response decision module and an aging knowledge injection module. Wherein the dynamic term ambiguity resolution module is used for receiving an original statement of a user and generating a standard term set; the context intention chain construction module is used for generating a structured intention chain; the domain emotion vectorization module is used for generating a three-dimensional emotion vector; the compliance response decision module is used for generating a to-be-verified response scheme; and the timeliness knowledge injection module is used for verifying the timeliness of legal provisions in the response scheme to be verified. According to the method, through fusion of dynamic term disambiguation, context intention chain modeling, emotion vector quantization and law and regulation aging verification, accurate semantic understanding and compliance response generation of the intelligent customer service system in multiple rounds of dialogues are realized.

A partial ambiguity resolving method suitable for a complex dynamic environment belongs to the field of high-precision dynamic satellite navigation relative positioning, and comprises the following steps: constructing a single-epoch carrier phase double-difference difference observation equation; and calculating a weight factor corresponding to each satellite through a standardized residual error and an IGG3 method, and substituting the weight factors into the double-difference factor matrix to obtain a corrected observation value. And resolving the updated observation equation through a weighted iterative least square method. And carrying out partial ambiguity fixation on the corrected ambiguity floating point solution to obtain a whole cycle ambiguity fixed solution. And carrying out Ratio-based posteriori consistency traversal detection, monitoring the number of satellites participating in calculation in a traversal search process, and if the number of the satellites is smaller than a threshold value, outputting a floating point solution. And if the number of satellites after traversal search is greater than or equal to And substituting the fixed solution of the integer ambiguity into the updated observation equation to obtain a fixed solution of a three-dimensional relative position vector and a covariance matrix of the three-dimensional relative position vector.

The invention provides a multi-language cross-culture communication assisting method and system based on a large model. The method comprises the following steps: receiving a source language audio stream during a call, calling a multi-language sound frequency harmonic modulation feature library to extract fundamental frequency harmonic intensity distribution and tone turning features, and generating a cultural acoustic fingerprint vector; based on the vector, controlling a microphone array phase difference, directionally enhancing a fundamental frequency harmonic component of a speaker and suppressing noise, and outputting a high signal-to-noise ratio spectrogram; analyzing the pronunciation rhythm and tone turning characteristics of the spectrogram, capturing the pitch jump and duration of the syllable boundary, and generating an acoustic culture label; associating the spectrogram with a target semantic library, matching harmonic distribution and a cultural context rule based on a large model, and outputting a cultural interpretation prompt containing an ambiguity resolution suggestion; and generating a calibration result according to the acoustic tag and the semantic prompt, and overlapping the dynamic floating subtitles to the face area of the speaker in the video conference picture. According to the invention, cultural tone ambiguity in multi-language communication is eliminated.

The invention discloses a method for enhancing geographical name and address translation precision by using context awareness and a geographic library, relates to the technical field of intelligent translation, and constructs a dynamic collaborative ambiguity resolution framework by fusing a context awareness mechanism and multi-dimensional attributes of a geographic knowledge base so as to break through semantic limitation of traditional geographical name and address translation. Specifically, firstly, dynamic association information implied in an address text is captured by utilizing context semantic coding of a non-geographical name text fragment, and structured feature embedding is performed on candidate entities in combination with a geographic knowledge base to extract multi-dimensional attributes of the candidate entities, so that cross-modal disambiguation decision is realized in a semantic aggregation stage; through a geographic feature cross validation mechanism guided by context semantics, the problem of translation ambiguity caused by static rule dependence and geographic attribute segmentation in the prior art is effectively solved, so that a more accurate multi-language address translation effect is achieved.

The invention relates to a multi-modal rumor detection method and system fusing multi-granularity features, and the method comprises the steps: collecting multimedia posts in social media, extracting texts, images and comments in the posts, and labeling authenticity labels of the posts, thereby constructing a training data set; a multi-modal rumor detection model fused with multi-granularity features is constructed, the multi-modal rumor detection model extracts the multi-granularity features in posts, image-text features are deeply fused, resolution of image-text ambiguity is achieved through image-text similarity weights, comment information is fully mined, comments are utilized from different angles, and the image-text ambiguity resolution is achieved. Finally, similar information of the same category of social media posts is captured through comparative learning; using the training data set to train a multi-modal rumor detection model; and inputting texts, images and comments of undetected multimedia posts into the trained multi-modal rumor detection model to obtain authenticity labels of the multimedia posts. The method and the system are beneficial to improving the rumor detection accuracy and reliability.

The invention discloses an intelligent auditing method and system based on a multi-modal large model, and relates to the field of artificial intelligence, and the method comprises the following steps: a field adaptive model is constructed by injecting financial and accounting field corpora into an LLaMA-3 architecture, accounting criteria, policies and regulations can be automatically analyzed, executable auditing rules can be generated, the system adopts a multi-channel structure, and the auditing efficiency is improved. According to the method, key entity extraction, logic relation identification and ambiguity resolution are synchronously completed, the accuracy and robustness of rules are ensured, multi-source heterogeneous data are integrated by constructing a finance and accounting knowledge graph, generated SPARQL query is executed to realize automatic auditing testing, block chain anchoring rule hash and a three-dimensional evidence matrix are innovatively introduced, and the auditing efficiency is improved. And the traceable and non-tampering decision traceability of the whole process is realized. According to the method, the auditing efficiency, the coverage and the automation level are remarkably improved, the auditing risk is effectively avoided, and a highly credible solution is provided for intelligent auditing of man-machine cooperation.

The invention relates to a work order material intelligent tracking and dynamic updating system based on multi-source data fusion. The system comprises an acquisition module, a tracking module, an updating module, a man-machine interaction module and a storage module, the acquisition module is used for acquiring work order information from a bill of material, scheduling information and inventory and supplier data, and constructing a material data model; the tracking module monitors material inventory, consumption and material shortage risks based on the model, and realizes automatic state updating and graphical path recording in combination with bar code recognition and ambiguity analysis; the updating module predicts material requirements through a machine learning algorithm, optimizes a distribution plan and outputs a dynamic report; the interaction module supports multi-format data import, unstructured field classification and interrupted operation control; the storage module ensures credible synchronization and tamper-proofing performance of data among different systems through a block chain technology; according to the invention, high-efficiency management and dynamic allocation of work order materials can be realized in an environment without an MES system, and the production transparency and the resource utilization efficiency are improved.

The invention discloses an ambiguity determination method for satellite positioning, a terminal and a medium in the field of satellite navigation and positioning, and the method comprises the steps: obtaining observation data of a base station and a mobile station, eliminating errors through employing a double-difference technology, and carrying out the cycle slip correction, and obtaining the corrected observation data; preliminarily estimating the speed and position of the mobile station; based on the corrected observation data, extracting an optimal ambiguity subset through satellite-level and ambiguity-level screening; constructing a factor graph model by using the optimal ambiguity subset, taking the preliminarily estimated speed and position of the mobile station as initial values, minimizing an error function in a factor graph, and optimizing to obtain a floating solution of ambiguity; obtaining an integer ambiguity solution based on the floating point solution; and verifying the stability of an ambiguity resolving result through consistency, and finally obtaining an ambiguity fixed solution. According to the method provided by the invention, high precision, high efficiency and high stability of ambiguity calculation are realized, and the method is suitable for a high-precision satellite positioning system in a complex environment.

The invention provides a GNSS (Global Navigation Satellite System) integer ambiguity estimation method and equipment based on improved particle swarm optimization, which are used for realizing rapid and accurate estimation of high-dimensional integer ambiguity and comprises the following steps of: performing integer Gaussian transformation parameterization on floating point ambiguity and a variance-covariance matrix thereof; taking a minimum optimal integer candidate vector residual quadratic form as fitness, and establishing an ambiguity search target function; performing direct rounding estimation on the floating point ambiguity to obtain a search initial value; determining a search space of each ambiguity component by combining the floating point ambiguity and the median error after integer Gaussian transformation; setting an improved particle swarm optimization method, and setting a dynamic inertia weight, a dynamic learning factor, a boundary detection and control model, an adaptive iteration model and a scale factor improvement model; and performing optimal and suboptimal integer ambiguity candidate vector estimation, and obtaining a corresponding residual quadratic form. The method can be used for ambiguity calculation of non-difference ambiguity, dual-frequency and ionosphere-free combination models, and can also be popularized to other GNSS integer ambiguity estimation problems.

The invention discloses a broadband lightning very high frequency radiation source positioning method based on an ESPRIT algorithm, and the method comprises the steps: 1, constructing an orthogonal uniform linear very high frequency antenna array, and collecting broadband lightning very high frequency signals; 2, discrete Fourier transform is carried out on the broadband thunder and lightning very-high-frequency signals, the broadband thunder and lightning very-high-frequency signals are divided into J frequency points, and the frequency domain value of each frequency point signal is worked out; step 3, dividing the orthogonal uniform linear very high frequency antenna array into two sub-arrays in an x-axis direction and a y-axis direction, positioning each frequency point value of the signals in the two directions by using an ESPRIT algorithm, and respectively obtaining a calculation incident angle of each frequency point in the two directions; step 4, carrying out phase ambiguity resolution on the calculated incident angles of each frequency point in the two directions so as to obtain a real incident angle; and 5, calculating the azimuth angle and the elevation angle of the radiation source according to the real incident angle. According to the invention, rapid and refined positioning imaging of the lightning radiation source can be realized.

Aspects of the invention provide a method, system, and computer program product for retrieval augmented generation. In one aspect, the method includes receiving a query. The method further includes classifying the query to a first domain within a plurality of domains. The method additionally includes determining an ambiguity associated with classifying the query. The method also includes retrieving an index of domain-specific vector embeddings corresponding to the domains when the ambiguity does not exceed a threshold for ambiguity. The method further includes prompting a large language model with the query and the domain-specific vector embeddings. The method also includes receiving a query response from the large language model as grounded with the most relevant index results. The method further includes forwarding the query response.

The invention relates to the technical field of natural language processing, in particular to an NLP-based multi-source data fusion system and method.The NLP-based multi-source data fusion system comprises a data collecting and processing unit, an NLP processing unit, a data fusion unit and an output unit.The data collecting and processing unit collects multi-source heterogeneous data and executes standardization processing to obtain preprocessed data; the NLP processing unit extracts entity, relation and emotion features through deep semantic analysis, a context-aware entity relation graph is constructed by adopting a bidirectional attention mechanism model and a graph attention network, and the data fusion unit realizes cross-source entity ambiguity resolution through an iterative graph neural network based on a graph topological structure. The emotion confidence weight is dynamically distributed to generate a fusion vector, a rule feedback reconstruction map is extracted, and the output unit converts the fusion vector into a target format for output, so that the problem of semantic conflict of multi-source data is solved, and semantic coherence and availability of fusion data are improved.

The invention belongs to the technical field of natural language processing and geographic information systems, and particularly relates to a region address standardization method based on knowledge graph enhanced retrieval. Cleaning and preprocessing the original address text input by the user; utilizing a fine-tuned large language model to identify a geographic entity and performing standardized expansion on variant expression to generate a query candidate set; entity linking and context retrieval are carried out based on the knowledge graph, and attributes, hierarchy and spatial topology information of associated entities are obtained; in combination with the original input and the map context, an enhanced retrieval query text is generated through large language model reconstruction; vectorized semantic retrieval is carried out through the fine-tuned embedding model, and a preliminary candidate address set is obtained; carrying out multi-dimensional refined sorting by adopting a resorting model; and generating a structured standard address by using a large language model, and outputting the structured standard address after multi-level verification. According to the method, the problems of ambiguity resolution, alias recognition and context understanding in address processing are solved, and the accuracy and robustness of address standardization are improved.

The invention discloses an intelligent voice question-answering system and a knowledge reasoning method for operation and maintenance of power equipment. The system comprises a knowledge base construction module and a core question and answer engine module, the knowledge base construction module is used for constructing a power equipment knowledge graph and a fault case library, and the core question and answer engine module comprises a natural language understanding unit, a multistage semantic retrieval unit and a voice interaction ambiguity resolution unit. A natural language understanding unit identifies intent categories and power entities. The multi-stage semantic retrieval unit executes the following steps: matching in an ontology layer of the knowledge graph; performing extended query to obtain detailed information; and similar case matching is carried out in the fault case library. The voice interaction ambiguity resolution unit is used for executing disambiguation processing; analyzing the confidence and clarifying the dialogue; and triggering knowledge retrieval and reasoning and generating a sorting answer. The operation and maintenance efficiency is improved, the dependence on experts is reduced, the operation and maintenance quality and safety are improved, knowledge precipitation and sharing are promoted, the field work experience is improved, and scientific decision making is assisted.

The invention relates to a mine monitoring method based on millimeter-wave radar multi-feature fusion, and the method comprises the steps: transmitting an FMCW signal through a millimeter-wave radar, receiving a target echo, sequentially carrying out the signal preprocessing, 1DFFT distance measurement, 2DFFT speed measurement, velocity ambiguity resolution and DOA estimation angle measurement, and extracting the distance, velocity, angle and energy variation features of a target point cloud; then millimeter-level deformation is obtained through phase analysis; obtaining a vibration frequency through band-pass filtering and spectrum analysis; fusing the six types of features of the target point cloud, adopting a confidence counter weighting decision mechanism, and triggering early warning when a fusion score exceeds a preset threshold value; according to the invention, through the advantages of high reliability, strong anti-interference performance and high non-contact safety of multi-feature fusion decision, the false alarm rate is significantly reduced, and the real-time accurate early warning capability of the mine dangerous state is improved.

The invention discloses a phase interferometer DOA and polarization parameter joint estimation method based on multiple linearly polarized antennas, and belongs to the technical field of radar signal processing. According to the method, the problems of low ambiguity resolution probability and low signal DOA and polarization parameter estimation precision of an existing method are solved. Noise variance and signal power estimation is carried out by adopting a method of receiving data covariance matrix high-order power, and the complexity is reduced. Aiming at the problem that the defuzzification probability is limited due to polarization mismatch, the method firstly adopts a method of solving a short base line by a long base line to reduce a phase difference error, then utilizes a multi-base-line phase weighted defuzzification method, and utilizes phase differences and amplitude information of all base lines to perform polarization domain phase difference and spatial domain phase difference decoupling, so that the defuzzification probability is limited. And the power estimation error is reduced through the LMMSE method, and the precision of signal DOA and signal polarization parameter estimation is improved. The method can be applied to joint estimation of DOA and polarization parameters of the phase interferometer.

The invention discloses a low-altitude aircraft airway meteorological data acquisition and processing method, and relates to the technical field of airway meteorological data acquisition, and the method comprises the following steps: obtaining a carrier phase observation value of a target satellite from a GNSS receiver, recording a corresponding timestamp, and carrying out the original turnover ambiguity resolution of the obtained carrier phase observation value; carrying out first-order differential processing on carrier phase observation values of the same satellite at two continuous time points, and constructing an instantaneous carrier phase variation sequence reflecting the phase change rate; according to the invention, through carrier phase disturbance feature extraction and deep learning multipath risk prediction, dynamic weight adjustment of multipath interference satellites is realized, the system anti-interference capability and the data processing robustness are improved, the space mismatching and meteorological misjudgment risks are significantly reduced, and the positioning precision and the track sensing reliability in a complex environment are guaranteed.

The invention discloses a speed ambiguity resolution method suitable for 4D millimeter wave radar imaging. The method comprises the steps of 1, acquiring radar original target sampling data, and performing two-dimensional fast Fourier transform processing to obtain a target distance-Doppler matrix; carrying out constant false alarm rate detection on the target distance-Doppler matrix; 2, searching an optimal representative point as a speed representative point of the target; 3, adopting a hypothetical phase compensation speed ambiguity resolution algorithm for the speed representative point of the target to obtain a speed and a phase compensation value corresponding to the representative point; step 4, compensating all target points with phase compensation values calculated according to the representative points, and performing DOA estimation to obtain azimuth angle values; 5, coordinate transformation is carried out according to the obtained target point speed and azimuth angle value, the real position of the target under the three-dimensional coordinate system is obtained, and the representative point speed represents the real speed of the target. According to the invention, the detection capability of the MIMO radar imaging system on a high-speed target can be improved.

The invention relates to a sparse cloth double-array-element phase comparison and double-frequency phase solution ambiguity radar angle measurement method and device, and belongs to the technical field of radar measurement. The method specifically comprises the following steps of: 1, performing phase comparison measurement on sparse cloth double array elements at a dual-carrier frequency and a lower dual-channel to obtain a phase difference between the array elements so as to obtain a fuzzy coefficient containing a phase error; according to the fuzzy coefficient, determining constraint conditions of dual-frequency and carrier wave values; step 2, under the constraint condition determined in the step 1, selecting a radar signal working frequency, and constructing a virtual short baseline according to the dual-array-element phase difference under different frequencies; and step 3, based on a virtual baseline ambiguity resolution method, calculating to obtain a non-ambiguity high-precision one-dimensional angle measurement angle.

The application discloses an improved radar two-dimensional ambiguity resolution method for multi-targets, comprising the following steps: arranging point trail data after radar signal processing according to pulse repetition period from small to large; constructing a reference lookup table for resolving range ambiguity based on the arranged data; constructing a reference lookup table for resolving velocity ambiguity based on the arranged data; traversing all the frequency combinations of radar transmission, selecting N groups from M groups of frequency for multi-target pairing; obtaining a range pairing table based on the reference lookup table for resolving range ambiguity, calculating the standard deviation between rows of the range pairing table, and solving the real range of targets; obtaining a velocity pairing table based on the reference lookup table for resolving velocity ambiguity, calculating the standard deviation between rows of the velocity pairing table, and solving the real velocity of targets; and merging and processing output target data. The application can solve the problem that the traditional one-dimensional set method cannot meet the real-time requirement when the number of targets is large and the ambiguity is large.

Aspects of the invention provide a method, system, and computer program product for retrieval augmented generation. In one aspect, the method includes receiving a query. The method further includes classifying the query to a first domain within a plurality of domains. The method additionally includes determining an ambiguity associated with classifying the query. The method also includes retrieving an index of domain-specific vector embeddings corresponding to the domains when the ambiguity does not exceed a threshold for ambiguity. The method further includes prompting a large language model with the query and the domain-specific vector embeddings. The method also includes receiving a query response from the large language model as grounded with the most relevant index results. The method further includes forwarding the query response.

The invention belongs to the technical field of millimeter-wave radars, and relates to a millimeter-wave radar speed ambiguity resolution method and system. The method comprises the following steps: a transmitter transmits a first group of transmitted waveform signals and a second group of transmitted waveform signals; performing two-dimensional FFT processing on the echo signal to obtain two-dimensional spectrum data; performing target detection on the two-dimensional spectrum data to obtain a detection result; performing target angle measurement on each target obtained by target detection to obtain angle information of each target; performing ambiguity resolution matching by using a remainder theorem until matching succeeds, and obtaining a velocity ambiguity multiple when matching succeeds; and calculating to obtain the real speed of the target. According to the method, hypothesis matching is carried out by using the target angle, the target angle has much higher stability than the target amplitude and is not influenced by RCS flicker, so that the success rate of target matching is greatly improved, and meanwhile, the ambiguity resolution success rate of multiple targets can also be improved due to the fact that the angles of the targets are generally different under the multi-target condition.

The invention discloses a comprehensive quality evaluation method and system for Beidou deformation monitoring observation data in a complex environment, and relates to the technical field of satellite navigation positioning, and the method comprises the steps: carrying out the comprehensive evaluation of an elevating angle, a signal-to-noise ratio, an epoch difference and an environment model of the observation data of a Beidou single station, and determining the initial quality of the data; based on the double-difference observation values among the multiple stations, the data quality evaluation precision is further improved by combining a double-difference ambiguity resolving method; according to the method, ionosphere delay, three-difference errors and inter-epoch difference errors are used for data fusion, a more accurate quality evaluation result is obtained, and finally, the data are optimized through comprehensive analysis based on the quality evaluation results of various types of data so as to ensure accurate positioning and deformation monitoring. The technology aims at improving the accuracy and reliability of data quality evaluation by comprehensively analyzing influence factors of Beidou observation data in a complex environment, and provides support for geological disaster monitoring, smart city construction and other high-precision application scenes.

The invention relates to the technical field of navigation positioning, and discloses an INS-assisted positioning system and method under a GNSS / INS positioning system, and a medium, and the system comprises a prediction pseudo-range confirmation module, a floating point solution calculation module, a first optimal fixed solution calculation module, a second optimal fixed solution calculation module, and a fusion solution module. According to the scheme, the floating point ambiguity resolving and fixing process is optimized by correcting inertial information in real time, specifically, inertial prior information is corrected by using a combined positioning high-precision result, a traditional GNSS pseudo-range estimation method is replaced, an improved partial ambiguity fixing strategy is introduced, the fixing efficiency of non-optimal subset ambiguity is improved, and the positioning accuracy of the GNSS pseudo-range estimation method is improved. According to the method, the positioning precision, the stability and the real-time performance can be remarkably improved in a complex urban environment.

The invention relates to the technical field of GNSS high-precision positioning, and provides a BIE-based real-time dynamic positioning integer ambiguity resolving method and system, and the method comprises the steps: obtaining a preliminary ambiguity subset through the screening of a satellite elevation angle and a carrier-to-noise ratio, and carrying out the correlation reduction processing; a multi-level screening mechanism is adopted and comprises three stages of dynamic optimization of coarse screening, fine screening and candidate group generation; a weight distribution model is improved based on Laplacian distribution to calculate candidate solution weights and probability weighted fusion is carried out; in combination with an ILS and BIE mixed fixing strategy, BIE weighted averaging is adopted when ILS fixing fails; a positioning result is optimized through dynamic satellite screening and multi-system data fusion, and a jump detection threshold value is set to realize abnormal recalculation. The method improves the reliability of real-time dynamic positioning, and guarantees the continuous and stable operation of the system in a signal shielding or multi-path interference scene through a jump detection and recalculation mechanism.

The invention discloses a partial ambiguity resolving method and device, a medium and equipment, and relates to the technical field of satellite navigation and positioning. Based on the concept that in the partial ambiguity resolving process, after multiple-dimensional ambiguity corresponding parameters are removed, the more accurate the whole-cycle ambiguity resolving based on the remaining ambiguity related parameters is, the more stable the resolving of partial parameters corresponding to partial-dimensional ambiguity subsets is, the invention proposes that in each round of partial ambiguity resolving process, the more accurate the whole-cycle ambiguity resolving is, and the more accurate the whole-cycle ambiguity resolving is, the more stable the resolving of partial parameters corresponding to partial-dimensional ambiguity subsets is. According to the current ambiguity related parameters and the integer ambiguity, and different parameter parts corresponding to ambiguity subsets of different dimensions in the current ambiguity related parameters and the integer ambiguity, respectively solving baseline fixed solutions for multiple times to obtain multiple groups of baseline fixed solutions; the difference between the maximum value and the minimum value in the multiple groups of baseline fixed solutions is compared with the preset threshold value, the stability of the integer ambiguity solution is judged, and the accuracy and the reliability of the partial ambiguity solution are improved by utilizing the statistical characteristics of the ambiguity integer solution.

The invention discloses an ambiguity adaptive resolving method and system based on ILS and BIE estimation. The method comprises the following steps: acquiring GNSS original observed quantity; constructing a pseudo-range and carrier phase double-difference observation equation, and calculating a floating point solution of an ambiguity parameter by using extended Kalman filtering; performing ambiguity fixation on the ambiguity subset through an ILS algorithm to obtain an ILS fixed solution, performing ambiguity fixed check on the ILS fixed solution, if the check is passed, obtaining a final solution, and if the check is not passed, performing ambiguity fixation through a BIE algorithm to obtain a BIE fixed solution: performing multiple screening on the ambiguity subset based on an observation value domain and a state domain to obtain an optimal ambiguity subset; searching the optimal ambiguity subset by using an improved SEVB algorithm to obtain a BIE multi-ambiguity candidate solution; and calculating a BIE fixed solution, and performing reliability verification on the BIE fixed solution to obtain a final fixed solution. According to the method, the ambiguity fixing success rate can be improved, meanwhile, the precision of a fixed solution is remarkably improved, and the ambiguity resolving efficiency is effectively optimized.

The invention discloses a domestic PC terminal cross-modal natural interaction method and system fused with generative AI, and relates to the technical field of man-machine interaction, and the method comprises the steps: obtaining multi-modal data, and carrying out the preprocessing and feature extraction; constructing a modal adapter, mapping the extracted multi-modal features to a shared semantic space, and generating a multi-modal semantic vector; calculating a dynamic weight coefficient of each mode according to the current scene features; fusing the multi-modal semantic vectors to generate cross-modal fusion features, and carrying out ambiguity resolution processing on the fusion features; inputting the disambiguated fusion features into a lightweight domestic generative AI model, carrying out intention understanding, and generating a multi-modal response; and the generated multi-mode response is adapted to domestic PC terminal hardware and an operating system, and natural interaction is completed. According to the method, intention understanding and response generation are performed by introducing the generative AI domestic large model, so that the accuracy and naturalness of cross-modal interaction of the domestic PC terminal are improved.

The invention discloses a real-time PPP whole-cycle ionosphere elimination combination ambiguity fixing method and device based on PPP-B2b, terminal equipment and a storage medium, and belongs to the technical field of GNSS positioning and navigation, and the method comprises the steps: obtaining original observation data of a plurality of satellites and PPP-B2b correction information; according to the original observation data and the correction information of each row, generating wide lane and narrow lane floating point ambiguity resolution; calculating wide lane and narrow lane FCB of each satellite according to the wide lane and narrow lane floating point ambiguity resolution; and according to the wide-lane floating point ambiguity resolution, the wide-lane FCB, the narrow-lane floating point ambiguity resolution and the narrow-lane FCB, generating the whole-cycle ionosphere elimination combined ambiguity. According to the method, the PPP-B2b service broadcasted in real time is used for resolving, the method does not depend on post precision products, and the real-time performance can be guaranteed. By implementing the invention, the problem that the whole-cycle ionosphere elimination combination ambiguity cannot be solved in real time in the prior art can be solved.

The invention relates to the field of robot technology and artificial intelligence, and discloses a robot fine operation method and system based on a visual language model and semantic key point characterization, a closed-loop multi-body Agent system is constructed, GPT-4o and Ground DINO are combined to accurately understand and disambiguate a natural language instruction of a user, an innovative bridging layer is introduced, and the robot fine operation method and system based on visual language model and semantic key point characterization are obtained. Abstract decision information is converted into bottom execution parameters represented by three-dimensional semantic key points, the problem of decision transfer distortion is solved, meanwhile, a KMP algorithm is improved, and the stiffness and contact force of trajectory tracking are dynamically optimized by introducing a learning-based time-varying hybrid impedance / force control strategy, so that the accuracy of trajectory tracking is improved. According to the method, the generalization success rate of fine operation tasks of the robot and the stability of physical interaction are remarkably improved, seamless connection from high-level semantic understanding to low-level action generation is achieved, and an efficient and reliable technical scheme is provided for autonomous operation of the robot in a complex scene.