601 results about "Interaction technology" patented technology

The invention discloses an intelligent interaction system based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence and intelligent interaction. According to the system, data processed by a data acquisition and preprocessing module is stored in a local knowledge warehouse in a three-layer nested structure; the multi-modal semantic understanding module constructs a knowledge system in which a triple knowledge graph and a vector database are complementary by optimizing a BERT model and performing dual-channel analysis; the intelligent interaction module realizes natural language interaction and business task automatic triggering based on an RAG technology and a dialogue memory mechanism; the information change identification and analysis module generates a personnel change risk report and performs early warning; and the summary report automatic generation module outputs a structured report. According to the method, the problems of data splitting, complex interaction and slow response in traditional enterprise management are solved, the functions of system intelligent question answering, personnel change risk analysis, structured report automatic generation and the like are realized, and the management efficiency and the information consistency are improved.

The invention discloses an Android system user interface interaction method and device based on a large language model, and relates to the technical field of intelligent man-machine interaction, and the method comprises the steps: receiving a natural language instruction of a user, and synchronously capturing a real-time interface state of a current Android screen to generate a structured context containing semantic information of interactive elements; inputting the instruction and the context into a large language model, and generating a hierarchical task plan formed by a plurality of atomic operations with a logic dependency relationship; based on a dynamic adaptation mechanism, converting the atomic operation sequence into an operation instruction which can be executed by the Android system; receiving interface change information after instruction execution, and feeding back the interface change information as a new round of context to the large language model to determine a task execution state; and finally generating natural language feedback information to the user according to the execution state. By means of the mode, complex cross-application tasks can be understood and executed, and interaction intelligence of the Android system is remarkably improved through real-time interface perception and dynamic planning adjustment.

The invention relates to the technical field of robot control and somatosensory interaction, and particularly discloses a knee joint exoskeleton robot control system based on somatosensory interaction. The system comprises a somatosensory signal acquisition and fusion module, a personalized dynamic model construction module, an adaptive intention decision module, a variable impedance compliance control module and a rehabilitation process evaluation and parameter self-tuning module. Through cooperative work of the modules, precise recognition of the motion intention of a wearer, online construction of an individualized biomechanical model and flexible and adaptive motion control are achieved, control parameters can be automatically adjusted according to the rehabilitation process, and therefore the flexibility and individuation level of man-machine interaction and the effectiveness of rehabilitation training are improved.

The invention provides a multi-intention processing method and device for a smart home, electronic equipment and a storage medium, and relates to the technical field of man-machine interaction. The smart home system can first judge whether intention conflicts exist among the different intentions, and if the intention conflicts exist, the smart home system can first calculate a first priority score corresponding to the intention map and a second priority score corresponding to the secondary intention; the method comprises the following steps: acquiring a first priority score and a second priority score, then performing strategy selection according to the first priority score and the second priority score, determining a conflict resolution strategy for the deliberate map and the secondary intention, and then executing a control instruction corresponding to the conflict resolution strategy, thereby improving intention understanding accuracy and response efficiency, and improving intention understanding experience. And the capability and decision of the system on complex intention conflicts are improved, the timeliness and flexibility of control instruction response are guaranteed, and the accuracy of system response is improved.

The invention discloses a multi-modal interaction evaluation system and method based on synchronous data acquisition, and relates to the technical field of biomedical engineering and man-machine interaction, and the method comprises the steps: generating a synchronous pulse sequence through a synchronous signal generator according to the same coding time base, and outputting the synchronous pulse sequence to an optical path and an electrical path at the same time; pulse events are recognized in the video and the electrophysiological data respectively, and observation pairs of counting numbers and timestamps are obtained; time drift is continuously estimated and compensated through robust regression in a sliding window, and a unified time axis is generated; furthermore, a dynamic time window of heart beat anchoring is constructed according to an R peak event of the electrocardiosignal, and consistent segmentation and feature extraction of cross-modal data are achieved.

The invention belongs to the technical field of vehicle safety control and man-machine interaction, and particularly relates to a man-machine co-driving takeover decision-making, stability control and optimization method, which comprises the following steps of: A, constructing a driving safety field model, reflecting the influence of a dynamic environment and road elements on a vehicle by constructing the safety field model, and providing a real-time basis for takeover decision-making; b, constructing a driver human factor capability field, and evaluating the takeover capability of the driver through multi-modal data acquisition and real-time analysis; c, dynamically coupling a safety field and a human factor capability field in the takeover decision; d, a man-machine takeover mode judgment and control power distribution method; e, the takeover scheme is screened and optimized, and further screening and adjustment are carried out through the comprehensive cost function of the optimization algorithm and used for being executed in actual operation. The method has the advantages that the handover between the automatic driving system and the driver is intelligently controlled by evaluating the environmental risk, the driver ability and the take-over time in real time, and it is ensured that driving right transfer is safely, timely and efficiently completed.

The invention relates to the technical field of artificial intelligence voice interaction, in particular to a semantic analysis and feedback method for voice interaction of intelligent navigation equipment. According to the method, through multi-dimensional semantic analysis and dynamic confidence evaluation, the ability of understanding the complex intention of the user in a noise environment is effectively improved, and loss of key information is avoided. Meanwhile, a dynamic content generation engine driven by the knowledge graph is utilized, personalized feedback and deep culture guide can be provided according to the intention of the user, and both basic information and cross-spatio-temporal knowledge nodes can be accurately presented. In addition, due to the introduction of an intelligent fault tolerance and intention learning mechanism, the man-machine cooperation efficiency is optimized, the interaction steps are reduced, the knowledge graph weight is dynamically adjusted through user behavior feedback, and the user satisfaction is remarkably improved. The innovative designs jointly bring smoother, more accurate and story-rich guide experience to the user.

The invention relates to the technical field of artificial intelligence and man-machine interaction, and discloses a dynamic evaluation system and method for robustness of a graphical user interface agent, and the system comprises a task execution environment module, an abnormal triggering mechanism module, a state verification module, a data acquisition module and an evaluation index calculation module. The intelligent agent enters a simulation environment and completes a circulation interaction process of perception-decision-execution-feedback, abnormal events are monitored, automatically triggered, abnormal scene generation and recovery are carried out, state verification is carried out, whether tasks are successfully completed or not is judged, multi-source data acquisition of continuously recording the tasks in the whole operation period is carried out, and the task execution time is shortened. The method has the beneficial effects that the evaluation environment is converted from a static state to a dynamic state, the authenticity is obviously improved, a semantic-driven exception injection mechanism is introduced, context-aware interruption is realized, the evaluation is more objective, and the method has good expandability and reusability.

The invention provides an intelligent examination and approval method, system and device based on a multi-modal large model and a medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: analyzing a multi-modal examination and approval material through a visual large model to obtain multi-modal feature information; performing semantic understanding by using the language large model to generate structured semantic data; performing entity matching, relationship verification and logical reasoning based on the knowledge graph to generate a research and judgment report; intelligent decision support and risk early warning are realized; approval instruction conversion, service evaluation and self-adaptive interaction are realized through a multi-mode interaction technology; and continuously optimizing the model and the knowledge base by using the approval process data. According to the invention, by constructing a technical framework of deep fusion of vision, language and knowledge, comprehensive intelligentization of the approval process is realized, and the beneficial effects of improving the approval efficiency, guaranteeing decision fairness, enhancing the complex material processing capability, improving the user experience and realizing continuous evolution of the system are achieved.

The invention relates to the technical field of artificial intelligence and man-machine interaction, and discloses an AI multi-mode everything identification child interaction star key system, which comprises a multi-mode perception module, a data storage module, a self-adaptive strategy decision module, a situation arrangement and retrieval module, a content generation and safety control module, a multi-mode expression execution module and an asynchronous capability evaluation module. The system maps visual features to a semantic space through an attention mechanism to analyze a multi-modal anaphora intention, determines a cognitive age stage based on a user dynamic portrait matrix and matches an interaction strategy, generates reply content by using a large language model, and dynamically adjusts voice and action output parameters according to a real-time emotion vector. And finally updating the portrait by using a moving average algorithm. The problems that in the prior art, visual semantic alignment is lacked, and the content difficulty cannot follow dynamic evolution of the user ability are solved, and accurate intention understanding and personalized growth interaction are achieved.

The invention discloses a human-computer interaction efficiency evaluation method for a central control screen of an intelligent automobile, and belongs to the technical field of intelligent automobile interaction. Determining use requirements of the central control screen; the method comprises the following steps: acquiring indexes in three aspects of driver response behavior, vehicle control and user experience, performing fuzzy C-means clustering on three dimensions for each vehicle using scene to obtain clustering scores of each sample on different dimensions in different vehicle using scenes, calculating weights of all dimensions in different vehicle using scenes according to the clustering scores, and calculating the weights of all the dimensions in different vehicle using scenes; calculating average clustering scores of all the samples in all the vehicle use scenes, and judging the man-machine interaction efficiency level of the central control screen of the intelligent vehicle; in combination with a Fuzzy C-means clustering algorithm and an entropy weight method, clustering results of different dimensions in each scene and the weight of each dimension in different vehicle use scenes are adaptively calculated, and the objectivity and generalization ability of data are improved.

The invention discloses a Rhatish culture VRAR virtual-real fusion interaction method based on eye movement tracking, and particularly relates to the technical field of virtual reality and augmented reality man-machine interaction. The method comprises the following steps: acquiring an eye image of a user through a near-infrared image acquisition unit, and inputting the eye image into a double-branch convolutional neural network model to estimate a two-dimensional fixation point of a screen; performing nonlinear correction on a fixation point based on the user personalized sight line offset correction model established in the offline calibration stage; in the online interaction stage, the corrected fixation point is combined with equipment pose data to be converted into three-dimensional space rays, the distance and angle relation between the three-dimensional space rays and an interaction target is calculated, and an interaction instruction is triggered when a threshold condition is continuously met. According to the method and the system, accurate, stable and natural eye movement interaction of the virtual contents of the Rhatish culture and the entity exhibits in the VR / AR environment is realized, and the user experience and the system robustness are improved.

The invention relates to the technical field of electric power intelligent interaction, and discloses an AI large language model intelligent interaction system oriented to the electric power industry. The system comprises a multi-source data acquisition module for acquiring power industry multi-dimensional data from a plurality of heterogeneous data sources and integrating the power industry multi-dimensional data into a data warehouse; the semantic feature extraction module performs semantic analysis and feature extraction on the integrated data warehouse to obtain a semantic feature matrix; the industry knowledge graph construction module is used for constructing a power industry knowledge graph based on the semantic feature matrix; the user query analysis module is used for analyzing user query and extracting query feature vectors; the core semantic screening module is used for screening a core semantic sequence based on the semantic feature matrix and the query feature vector; and the intelligent response generation module generates an intelligent response based on the core semantic sequence and the power industry knowledge graph. The system can deeply understand user demands, generates professional and accurate responses, and is suitable for diversified intelligent interaction scenes in the power industry.

The invention discloses a naked-eye 3D augmented reality interactive display system, and relates to the technical field of naked-eye 3D display and reality interaction. According to the invention, the multi-source depth data acquisition module acquires and fuses a user limb depth image, the parallax physical depth mapping module completes depth and parallax mapping and visual angle correction, the occlusion relation determination module divides regions to determine the occlusion type, and the adaptive mask layer generation module generates a dynamic smooth mask layer. The shielding effect fusion display module is used for overlapping and synthesizing the shielding layer and the multi-view virtual image and then displaying the overlapped and synthesized shielding layer and the multi-view virtual image; the problems that in naked eye 3D interaction, the occlusion relation between the limbs of the user and the virtual object is not accurate, and the vision is abrupt are effectively solved, the space consistency and the vision fluency of interaction are remarkably improved, and the real and natural naked eye 3D augmented reality interaction experience is achieved.

The invention provides a cross-platform session context synchronization method and system based on browser request interception, and is applied to the technical field of browser extension and network data interaction. The method comprises the steps of loading site strategy configuration to define a data mapping and input container positioning rule, injecting proxy codes to monitor a page request state, locking a target input container in a DOM tree based on a multi-dimensional score, intercepting a session submission request and analyzing an original load, retrieving a historical context and converting the historical context into an implicit data segment according to a mapping relation, combining the data to an original load to generate a recombination request and then sending the recombination request; according to the scheme, session context non-inductive synchronization of cross-heterogeneous platforms can be realized on the premise of not depending on a fixed selector and not changing a page UI (User Interface), the continuity of user memory by different platforms is kept, the robustness of element positioning and the accuracy of an operation time sequence are improved, and the user experience is improved. The problem of data islands is effectively solved, and man-machine interaction continuity is enhanced.

The invention belongs to the technical field of robot communication interaction, and relates to an equipment capability self-description and negotiation method and device, an upper computer and a storage medium. The peripheral equipment is powered on to issue an equipment access instruction, so that the upper computer obtains the types and the number of the peripherals in the system in real time; state and capability information is obtained based on a unified standard frame, operation parameters and controllable range structuring are achieved, and a basis is provided for unified control; a control instruction template is automatically generated according to the information, multiple sets of adaptive logics are not needed, cross-device instruction and strategy multiplexing is supported, and the extension and operation and maintenance cost is reduced; the target execution instruction is issued through the preset verification strategy, problems can be found in advance when parameters cross boundaries or condition conflicts occur, wrong execution is avoided, the system stability is improved, peripheral automatic identification, capability unified expression, instruction template automatic generation and safe execution are achieved, and the compatibility and reliability of a robot system in a multi-device environment are enhanced.

The invention discloses a dialect recognition and emotion feedback multi-mode interaction system based on large model driving, and relates to the technical field of intelligent man-machine interaction, the system comprises a dialect emotion interaction engine, an article situation analysis module and a situation self-adaptive response module, and the problems of dialect emotion transmission distortion and situation understanding splitting in the prior art can be solved. The dialect emotion interaction engine generates a target dialect acoustic parameter through a pronunciation decoupling architecture, and combines a thermodynamic diagram to dynamically compensate and optimize emotion expression; the article situation analysis module improves the emotion recognition robustness in a complex environment based on an article-emotion knowledge graph and cross-modal arbitration; the context adaptive response module generates adaptive dialect responses according to the emotions and the item semantics. According to the system, technologies such as end-to-end generation and adversarial learning are adopted, zero-sample dialect adaptation and progressive capacity upgrading are achieved, the emotion requirements of old dialect users can be accurately matched, and the interaction experience is improved.

The invention relates to the technical field of computer graphics and human-computer interaction, in particular to an immersive literature interaction system based on WebGL and 3DGS, which comprises a scene reconstruction and data processing module based on 3DGS, a 3DGS real-time rendering engine based on WebGL and an interaction narration module fused with a 3DGS scene. The 3D GS-based scene reconstruction and data processing module is used for reconstructing a high-precision 3D scene from multi-source data and executing lightweight optimization; the WebGL-based 3DGS real-time rendering engine is used for loading and rendering a 3D Gaussian splash model at a browser end, supporting dynamic illumination, texture and viewpoint switching and realizing low-delay interaction; and the interactive narrative module fusing the 3DGS scene associates literature content through AI driving logic, triggers scene visualization response and integrates a role dialogue system to realize immersive narrative experience. The module realizes seamless fusion of literature interaction logic and a 3DGS scene.

The invention discloses an intelligent backpack multifunctional control system and method based on AI voice, and relates to the technical field of intelligent wearable equipment and AI interaction. The method comprises the steps of collecting a user voice instruction and multi-dimensional state data of the intelligent backpack, performing AI semantic analysis on the voice instruction to obtain an instruction intention, and performing fusion processing on the multi-dimensional state data to obtain a comprehensive state of the backpack; generating a target control strategy based on the instruction intention, the comprehensive state of the backpack and the user portrait; and driving an execution unit of the intelligent backpack to complete corresponding function actions according to the target control strategy, and feeding back an execution state to a user in real time. The system comprises a voice interaction unit, a sensor unit, a control unit, an execution unit and other core modules. According to the invention, the voice recognition accuracy and the control precision are remarkably improved, dual safety verification and a dynamic energy consumption optimization mechanism are combined, the use safety and the cruising ability are enhanced, and the personalized and intelligent travel requirements of the user are comprehensively met.

The invention discloses an intelligent sand table identification system based on an artificial intelligence multi-modal technology, which belongs to the field of sand table identification and comprises a multi-modal data acquisition module, a multi-modal feature fusion module, an intelligent analysis and interaction module and a system integration optimization module. According to the method, the problems of insufficient recognition robustness, poor dynamic analysis real-time performance, weak cross-scene generalization ability, high data labeling cost and single interaction mode caused by dependence on a single sensor and lack of multi-dimensional perception ability in the prior art are solved, the limitation of traditional single-mode recognition is broken through by collecting vision, force sense, voice and environment data, and the recognition efficiency is improved. The real-time intelligent analysis and dynamic interaction technology is adopted, real-time intelligent analysis and dynamic interaction of sand table operation are achieved, the system further has strong generalization ability, a meta-learning framework and an active learning strategy are adopted, dependence on annotation data is reduced, the system is reasonable in architecture, distributed collection, heterogeneous calculation and micro-service deployment are adopted, and the system has good application prospects. And high-efficiency operation and expandability are ensured.

A method for providing item access comprises an item being locked in a storage area of a storage apparatus via a lock; an unlocking code, to unlock the lock, being provided to a user, via an electronic device of the user; and the storage area being unlocked by the user via using the unlocking code. Disclosure is provided of the user paying for the item. Short-range communication / interaction technology, such as QR code, may be used to facilitate the unlocking code being provided to the user.

The invention relates to an interaction method, an interaction system and a vehicle, and belongs to the technical field of cabin interaction. The interaction method is used for near field communication between a first electronic device and a second electronic device, the first electronic device comprises at least two near field communication chips located at different positions, the first electronic device judges a target near field communication chip by sensing and analyzing the near field communication requirement of the second electronic device, and sends the target near field communication chip to the second electronic device. And the position of the target communication near-field communication chip is indicated, so that interconnection between the target communication near-field communication chip and the target communication near-field communication The interaction system can be used for the vehicle, and can improve the efficiency of near field communication between the passenger end equipment in the vehicle and the vehicle machine system.

The invention relates to the technical field of aged intelligent interaction, and discloses an aged intelligent interaction system and method for cognitive impairment and semi-disabled old people, a multi-modal information acquisition unit cooperatively works through voice, vision, touch, physiology, micro-action and environment perception units, and awakens and acquires multi-modal data as required; the adaptive processing unit performs multi-modal data verification, adaptive adjustment of an instruction guide mode and an intention recognition mode, adjusts an interaction mode according to a scene, and provides sound-visual-touch multi-mode feedback output; the cloud server interacts preset data with the adaptive processing unit, the remote collaboration unit synchronizes key data in the preset data to the remote terminal, triggers remote collaboration with the remote terminal and interface / scene sharing, and triggers remote alarm to the remote terminal and / or an emergency center when abnormity occurs. Potential risks are warned through the behavior baseline, and a remote terminal is triggered to limit care. According to the invention, an interaction system which is really adaptive to the physiological and psychological characteristics of the special group is constructed.

The invention relates to the technical field of brain-computer interaction, in particular to a patient mental state assessment system for a clinician, which comprises a semantic manifold calibration module, a state trajectory projection module, a geometric curvature resolving module and an emotion transformation quantification module. According to the method, electroencephalogram data are collected and deeply analyzed, high-dimensional neural activity characteristics are converted into a visual three-dimensional state track in combination with titer and awakening degree information, continuous dynamic monitoring of the mental state of a patient is achieved, then the emotion conversion process is quantitatively analyzed according to the geometric curvature change rate of the state track, and therefore the mental state of the patient can be rapidly and accurately monitored. According to the method, rapid emotion fluctuation which is difficult to perceive in a traditional evaluation mode can be accurately recognized and marked, objective and fine data support is provided for clinical diagnosis, and the accuracy and instantaneity of mental state evaluation are remarkably improved.

The invention relates to the technical field of multi-modal interaction, in particular to a vision, language and behavior linkage grassland robot inspection and driving integrated method, which comprises the following steps: acquiring a cattle herd image annotation coordinate attitude acquisition distance density input model to generate an inspection target sequence, driving a robot to acquire physical signs, judging abnormity and generating an abnormal individual identifier set, screening a monitoring target, inputting visual questions and answers, outputting a next inspection position coordinate, calculating an inspection path motion instruction set by fusing topographic semantics, completing detection and calculation of deviation, adjusting acousto-optic output, and generating a driving control instruction set. A semantic inspection sequence is generated in combination with text vision, target adaptive updating and real-time response are achieved, sign abnormity is recognized through infrared depth comparison, paths are optimized through image semantic matching, obstacle avoidance and adaptability are improved by fusing terrain semantics and motion parameters, and task continuity and recognition reliability are ensured.

The invention discloses a bionic robot facial expression synchronization method and device based on visual perception, equipment and a medium, and relates to the technical field of man-machine interaction, and the method comprises the steps: controlling a target bionic robot to execute a target expression control instruction used for achieving a preset expected robot facial expression, and capturing a robot visual facial expression of the robot; based on the robot visual facial expression and a preset expected robot facial expression, carrying out calibration on the target bionic robot so as to construct a hardware compensation parameter vector; executing a facial expression synchronization operation based on the hardware compensation parameter vector and a pre-trained target expression mapping model by asynchronously running a preset sensing thread and a preset driving thread; the preset sensing thread is used for collecting a target face image in real time and outputting a target steering engine control vector through a target expression mapping model; and the preset driving thread is used for outputting a steering engine control instruction at a preset output frequency based on a preset frame compensation algorithm, the hardware compensation parameter vector and the target steering engine control vector.

The invention discloses a multi-modal three-dimensional hand grid reconstruction method and system based on topology perception Transform, and belongs to the technical field of computer vision and intelligent interaction. According to the method, a topology perception hierarchical coding denoising network containing anatomy and topology constraints is introduced in the three-dimensional hand posture and grid reconstruction process; a real hand 3D joint coordinate is subjected to perspective projection, forward noise addition and feature fusion, and then is processed by a topology perception hierarchical coding denoising network composed of a hand part hierarchical coding module, a hierarchical feature aggregation mechanism and a topology perception Transform module to obtain a joint feature containing rich structure information; and finally, two-stage hand grid vertex construction from rough to fine is realized through a joint-guided grid reconstruction module. According to the method, the precision and robustness of three-dimensional hand posture and grid reconstruction are remarkably improved.

The invention relates to the technical field of artificial intelligence and teaching interaction, and discloses a multi-modal behavior perception interaction guidance method, device and equipment and a medium, and the method comprises the steps: obtaining vision, voice and screen data to form multi-modal behavior perception data; identifying learner operation state information and teaching software state information based on the data, deducing the learning progress, and constructing a learner state information set; matching the learner state information set with a preset practical training knowledge base to generate a teaching guidance scheme; generating an execution interaction instruction sequence based on the teaching guidance scheme; and outputting teaching guidance content according to the practical training link sequence and executing interactive guidance operation adapted to the practical training process. According to the method, accurate state recognition is realized through multi-modal behavior perception, a personalized teaching guidance scheme is generated through matching of the state and the knowledge base, adaptive practical training teaching is completed through collaborative multi-modal output, and the accuracy and adaptability of teaching are improved.

The invention relates to the technical field of robot interaction, in particular to a guide robot interaction method and system based on a large language model and an intelligent agent architecture, and the interaction method comprises the steps: S1, carrying out the input processing of a user; s2, identifying and classifying user intentions; s3, service intelligent routing is carried out; s4, executing control; and S5, performing interrupt processing. The interaction system comprises a user interaction layer, a core processing layer, a back-end service layer and an execution layer.

The invention relates to the technical field of man-machine interaction, and discloses a naked eye 3D interaction guiding method and system based on posture perception data, and the method comprises the steps: obtaining a continuous posture sequence of a user in a naked eye 3D display space; recognizing an action mode according to the motion vector and acceleration change of the key joint points in the continuous attitude sequence; generating a predicted interaction track according to the spatial orientation and the change trend of the action mode; comparing the predicted interaction track with a preset interaction area in real time, and taking the interaction area as a target interaction area when a main path section of the predicted interaction track is within a triggering range of the interaction area; calling interaction logic bound with the target interaction area in the naked eye 3D display space to determine a target interaction event; generating visual guidance information synchronized with the naked eye 3D display space according to the target interaction event; according to the invention, the accuracy of naked eye 3D interaction guidance can be improved.