928 results about "Interaction control" patented technology

The invention discloses a digital twin interaction control system based on robot vision and tactile fusion, and the system comprises a data collection module which is used for collecting visual image data and tactile sensing data; the preprocessing module is used for preprocessing; the multi-mode perception modeling module is used for executing spatial perception modeling and tactile state modeling; the fusion state vector construction module is used for generating a fusion state vector; the digital twinborn mapping module is used for constructing a digital twinborn body; the simulation interaction control module is used for executing interactive action control and generating a control instruction parameter group; the action execution and feedback module is used for controlling the robot to execute the actual action and updating the fusion state vector; and the dynamic evaluation and self-adaptive adjustment module is used for dynamically optimizing and adjusting the fusion state vector. Visual and touch information of the robot is fused, a digital twinning synchronous control mechanism is constructed, and the interactive optimization method which is fast in operation response, high in execution precision and stable in control process is achieved.

The invention provides a multi-source information fusion automobile light personalized interaction control system and method, and relates to the technical field of automobile intelligent light control. The system comprises a multi-source sensing module, a data preprocessing module, a data analysis processing module and a vehicle lamp driving module. The multi-source sensing module collects multi-source heterogeneous data, after the multi-source heterogeneous data is processed by the data preprocessing module, fusion analysis and intelligent decision are carried out by the data analysis processing module, a control instruction is generated, and finally, the instruction is executed by the vehicle lamp driving module and a state is fed back. According to the invention, the defects of the existing automobile light control technology in the aspects of intelligence, situational and individuation are overcome, the efficient, intelligent and individualized control of the automobile light is realized, and the driving safety, comfort and entertainment are improved.

The invention provides a control method, which is applied to an artificial intelligence experiment system, at least comprises a robot hardware platform, a controller, a wheeled robot chassis and an industrial mechanical arm, and the method comprises the following steps: starting an operation system and executing hardware self-inspection; loading a large language model service and a traditional AI model, wherein the traditional AI model comprises a speech recognition model, a target detection model and a semantic analysis model; a natural language instruction of a user is received, voice is converted into a structured text through a voice recognition model, an instruction intention is analyzed through a large language model and a semantic analysis model, robot control parameters are generated, and a multi-modal interaction control signal is obtained; based on the multi-mode interaction control signal, a camera is called to collect image data, the position and category of a target object to be grabbed by the robot are recognized through a target detection model, the moving path of the robot and the grabbing track of the mechanical arm are calculated in combination with laser radar data, and the wheeled robot chassis and the industrial mechanical arm are controlled to execute coordinated actions.

The invention relates to the technical field of computers, and discloses an interaction control method of intelligent glasses. The method comprises the following steps: synchronously acquiring multi-modal data such as eye movement, voice, gestures and head postures and environment and application context information; carrying out independent time sequence feature coding on each modal data; generating a modulation vector in combination with the context, and outputting probability distribution of user intentions through a cross-modal attention fusion network; and a unique execution instruction is determined through an instruction arbitration module based on rules and a state machine. The system comprises corresponding function modules. According to the method, the accuracy, robustness and naturalness of interaction are improved through multi-modal synchronous fusion and a context self-adaption mechanism.

The invention discloses an interaction control method and system for an intelligent agent and a front-end and back-end system, and the method achieves the automatic control of the intelligent agent on the front-end and back-end system through the integration of a large language model. The method comprises the following steps: an intelligent agent performs natural language intention recognition through a large language model, automatically selects a proper tool, extracts parameters required by the tool, converts the intention into a target task, generates a structured control instruction, maintains a complete session history and supports multiple rounds of dialogue interaction; the back end receives a user request, calls an intelligent agent to generate a structured instruction, transmits the structured instruction to the front end, and dynamically adjusts a subsequent instruction according to the received front end feedback; and the front end receives the instruction transmitted by the rear end, automatically identifies an instruction format through a regular expression, performs corresponding operation after parameter verification and feeds back a result. According to the method, unified control of the agent on the front-end UI and the back-end business logic is realized, complex multi-round dialogue and multi-step operation are supported, and the method has a wide application prospect.

The invention discloses a multi-device and multi-mode centralized control system which comprises an interaction control end and a device assembly. The interactive control end is configured according to three different control modes of centralized control, independent control and hybrid control, in the centralized control mode, a set of main control unit is configured for all devices, and the main control unit comprises a main control server which is used for operating a main control program and coordinating and controlling operation of all device components; in the independent control mode, each equipment component is provided with a corresponding embedded controller, and the embedded controller comprises an embedded control server which is used for operating a main control program for controlling the corresponding equipment component; in the hybrid control mode, one or more independent devices are provided with embedded controllers, the embedded controllers communicate with the main control server, the device assembly comprises a device body and a driving unit, and the device body is driven by the driving unit to achieve various operation functions. According to the invention, centralized control of multiple devices in a large-scale manufacturing factory can be realized.

The invention discloses an intelligent driving recording method and system based on voice AI, and relates to the technical field of intelligent driving recording. The method comprises the following steps: acquiring a user voice instruction through voice acquisition equipment, and identifying the user voice instruction through a vehicle-mounted lightweight ASR model; analyzing the instruction to generate a structured control instruction containing an event type and a time reference; determining a time window of the event to be marked in combination with the time reference, the motion data of the IMU sensor and the video data; packaging, encrypting and storing the video clip in the window, the sensor data and the structured control instruction to generate an event record; the video is analyzed in real time through a local lightweight computer vision model, and when a preset dangerous scene is detected, voice early warning is triggered and an associated video is automatically stored. According to the invention, voice interaction control, accurate event marking, real-time danger early warning and efficient data management of the driving record are realized, and the convenience, accuracy and safety of the driving record are improved.

The invention provides a voice interaction control method and device of a browser, electronic equipment and a storage medium, and the method comprises the steps: obtaining a voice control instruction input by a user, and determining a target control intention based on the voice control instruction; obtaining a target document object model tree corresponding to the current webpage of the browser; sending the target control intention and the target document object model tree to a server, and receiving at least one control instruction generated by the server based on the target control intention and the target document object model tree; and executing the at least one control instruction, and controlling the webpage to render an interaction result corresponding to the voice control instruction. In this way, the steps of maintaining and developing each website and exhausting all webpage functions to generate the instruction set can be reduced, and the control efficiency of browser voice interaction control can be improved.

The invention discloses a robot multi-mode interaction control method and a related device, and the method comprises the steps that a robot controller obtains user interaction information, and the user interaction information comprises user voice information and / or user action information; analyzing the user interaction information, and determining a shopping guide service type and a target vehicle part; acquiring first component information of the target vehicle component from a preset vehicle knowledge base according to the shopping guide service type; according to the shopping guide service type and the first component information, a target action sequence is determined from a preset action library, the target action sequence comprises joint actions and voice actions, the voice actions are used for outputting voice shopping guide information, and the voice shopping guide information is determined according to the first component information; and sending a first control instruction to the target robot, wherein the first control instruction is used for indicating the target robot to execute the target action sequence. According to the invention, the functionality and intelligence of the humanoid robot as an intelligent shopping guide robot can be improved.

The invention discloses a virtual interaction system for realizing multi-dimensional perception, which relates to the technical field of virtual interaction, and comprises a man-machine interaction unit, a mapping matching unit, a data processing unit and a data processing unit, and the coordinate matching module is responsible for establishing a coordinate matching relation of the virtual object in the virtual space according to the size, shape and attitude parameters of the virtual object. The interaction device is operated to control the intelligent mark point in the virtual interaction system to interact with the target object, according to the position relation in the interaction process, the position posture of the interaction object is collected to determine whether contact occurs, event triggering and target interaction are achieved through the triggering control unit, a user senses the event, and the interaction efficiency is improved. Interaction requirements can be met, multi-target interaction control requirements are met, and the purpose of saving system resources is achieved.

The invention discloses a lanyard data line interaction control method based on artificial intelligence, and the method comprises the following steps: S1, collecting interaction data of a lanyard data line, and carrying out the preprocessing of the interaction data; s2, segmenting according to a set window, performing singular value decomposition on each segment, and constructing a main feature set; s3, performing hypersphere embedding on the principal component vector, performing linear projection on the residual vector, and generating a characteristic spectrum by adopting Laplacian mapping; s4, performing tensor decomposition on the characteristic spectrum, and constructing a multi-order structure; s5, executing bidirectional loop iteration on the tensor interaction sequence and controlling information transmission; s6, analyzing the prediction action, matching the prediction action with an instruction mapping table, generating a control instruction, and sending the control instruction to the terminal equipment; and S7, counting execution feedback, updating a tensor interaction sequence weight, and optimizing an interaction control strategy. According to the invention, high-precision identification and stable adaptive control of the lanyard data line are realized, and the interaction precision, the response speed and the use convenience are effectively improved.

The invention relates to a clinical surgery experiment virtual simulation teaching method and device, equipment and a medium. The method comprises the following steps: responding to an obtained teaching task configuration file; the teaching task configuration file comprises a clinical scene and an evaluation standard; calling a corresponding three-dimensional digital physiological model according to the teaching task configuration file, and performing special effect rendering according to the clinical scene to obtain a visual virtual simulation experiment scene; responding to the obtained user action data, performing real-time deformation on the three-dimensional digital physiological model, and generating feedback parameters; the feedback parameter is used for indicating the interaction control to work according to the feedback parameter; and comparing the user action data with preset standard expert action data, and generating a teaching evaluation result based on an evaluation standard. By adopting the method, high fidelity can be carried out on the whole process of clinical surgery experiment teaching, effective technical support is provided for medical skill teaching, and the method is suitable for multi-scene and multi-level medical teaching practice requirements.

The invention provides a screen interaction method and device, a display device and a storage medium, and the method comprises the steps: obtaining a hand key point of a master control person controlling a target screen, and carrying out the user positioning and skeleton tracking of a target image containing the master control person to determine the hand key point; according to the three-dimensional position information of each hand key point, target pose information of a hand limb of the master control person is determined, and the target pose information comprises at least one of the curvature, the pointing direction and the movement trend; determining a target gesture of the master control person according to the target pose information of the hand limb and standard pose information of the hand limb in the preset gestures; and performing interaction control on the target screen in response to an operation event corresponding to the target gesture. According to the technical scheme, additional interaction equipment such as a mouse does not need to be configured, the equipment configuration cost is reduced, hand pointing analysis is performed based on the three-dimensional space to determine the target interaction position, the interaction accuracy is ensured, and then the interaction performance is improved.

The invention relates to the technical field of intelligent education and Internet of Things fusion, in particular to a multi-modal interaction control method and system of a multifunctional teaching-assistant robot and the robot. According to the system, a tablet AI processor runs an Android system as a core, a display module, a man-machine interaction module, an audio input module, an audio output module, an image acquisition module, a temperature and humidity sensor module, a WIFI or Bluetooth module, an Ethernet module and an Internet of Things module are connected, and the Internet of Things module supports RS485 wired access and Zigbee wireless access at the same time; the tablet AI processor executes voice interaction, video call, face recognition, environment monitoring, network interaction and equipment linkage, and provides a face recognition alignment and depth feature matching algorithm and an annular microphone array beam forming and sound source direction estimation algorithm, so that multi-modal interaction and multi-equipment linkage in a teaching scene are realized. The convenience and the safety are improved; and the equipment access cost is reduced.

The invention relates to a multi-user holographic sand table collaborative resolving system and method based on 360-degree omni-directional perception gesture recognition. The method comprises the following steps: acquiring continuous multi-frame multi-view hand image data; hand instance separation and key point extraction are carried out on the multi-view hand image data of each frame, and spatial 3D coordinates of 21 key points are independently solved for each hand instance; based on the space 3D coordinate sequence of the continuous frames, space-time action features are extracted, and a gesture template library is matched to recognize gesture types and motion parameters; analyzing the gesture type, matching an interaction intention in combination with a predefined gesture-instruction mapping table, and generating an interaction control instruction according to a matching result; generating a three-dimensional holographic sand table image cooperatively operated by multiple persons in real time according to the interaction control instruction; through a multi-hand parallel processing technology, different hand instance feature extraction paths are separated, the problem of multi-hand ID jump is solved, occlusion area coordinate prediction is optimized, and interactive use experience is improved.

The invention provides an interactive multi-dimensional data visualization display sand table and method for business data analysis, and the method comprises the steps: carrying out the semantic mapping of state parameters in an interaction control operation when the interaction control operation is received, obtaining a plurality of pieces of visualization intention metadata, and generating a structured query instruction; based on the structured query instruction, extracting a target data subset rendered visually by the heterogeneous commercial data source from a multi-dimensional data cube of the commercial data source, performing visual optimization on the visually rendered chart type, the visual coding channel and the initial visual parameter through the cardinal number of the dimension field in the target data subset and the data distribution type and the numerical range of the measurement field to obtain a visual configuration set of the target data subset; and using the visualization configuration set to render and generate a multi-dimensional data visualization view, and outputting and displaying the data visualization view in a graphical user interface. Based on the scheme, automatic closed loop generation from heterogeneous data to interactive views can be realized.

The invention provides an interaction control method and device of a foot type robot, equipment and a medium. The interaction control method comprises the following steps: determining local accumulated point cloud data according to pose transformation information and registered point cloud data; performing passable judgment on the foot-type robot through the local accumulated point cloud data to obtain a local passable region; according to the local accumulated point cloud data, low obstacle point cloud data and impassable obstacle point cloud data of the foot-type robot in a local passable region are determined; clustering the low obstacle point cloud data to obtain a low obstacle representation shape; clustering the impassable obstacle point cloud data to obtain an impassable obstacle representation shape; and rendering the low obstacle representation shape and the impassable obstacle representation shape into a local passable region displayed in a first display interface at the handle end of the foot robot in real time. Therefore, the user experience is effectively improved.

The invention discloses a data processing and interaction control system based on dynamic eye position tracking, and particularly relates to the technical field of man-machine interaction and eye movement tracking, which comprises an image acquisition module, a data processing module, an interaction control module and an equipment interface module. The image acquisition module controls a near-infrared camera to capture an eye video; the data processing module executes dynamic calibration, triggers calibration points based on a historical gaze point distribution sparse region, updates a sight line mapping model online by adopting a recursive least square method, and recognizes an interaction intention through a state machine in combination with a gaze point sequence and an eye movement event mode; the interaction control module carries out logic binding on the eye movement intention and signals such as head postures, gestures and voice, and a composite control instruction is generated through complementary fusion, concurrent binding and conflict arbitration; and the device interface module standardizes the instruction and then outputs the instruction to the controlled device. The system realizes non-intrusive dynamic calibration, effectively improves tracking precision and interaction robustness, and is suitable for a multi-modal fusion control scene.

The invention provides an interactive control system and method for a power module and an overcharge pile, a storage medium and a computer program product, and the method comprises the steps: obtaining a charging control parameter according to the input time sequence state data of a battery through a charging control parameter prediction model based on deep learning; generating a power instruction according to the charging control parameter and sending the power instruction to the power module; after the power supply module executes the power instruction, an instruction execution result and battery state data are transmitted back to the overcharge pile main control software; and the overcharge pile main control software adjusts the weight of the charging control parameter prediction model according to the received data or regenerates a power instruction based on the latest battery time sequence state data. According to the invention, the charging time can be shortened, the risks of overheating, overcharging and the like can be prevented, different battery states and complex working conditions can be adapted, and the real-time requirement of an overcharging scene on a control instruction and state data can be met.

The invention discloses an interaction control method and an interaction control system, and belongs to the technical field of interaction control, and the method comprises the steps: obtaining a current behavior time sequence graph of a vehicle in a current driving process; when the difference degree between the current attention distribution of the first large model and the reference attention distribution of the current driving scene is smaller than a preset value and the duration of the current driving scene exceeds a preset duration, updating the current attention distribution based on the duration; performing user preference modeling based on a behavior time sequence graph by using the first large model after the attention distribution update to obtain user preference information output by the first large model; and determining a target interaction strategy based on the user preference information, and controlling related components in the vehicle to execute interaction operation based on the target interaction strategy. Therefore, the problem of attention collapse of an attention mechanism of dynamic preference modeling in long-term interaction can be effectively avoided, and the adaptability of an interaction strategy is improved.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an interaction control method, device, equipment and medium based on user state awareness, and the method comprises the steps: collecting multi-modal original data to generate standardized multi-modal user information; predicting the emotion change trend of the user according to the standardized multi-mode user information, and generating a preliminary interaction scheme in combination with the intention demand of the user and the current interaction state; generating a cooperative control strategy based on the preliminary interaction scheme; real-time multi-mode user information is obtained and compared in the process of executing the cooperative control strategy, and when an adjustment condition is triggered, a new interaction scheme is generated and the cooperative control strategy is updated; after interaction is finished, interaction performance is analyzed according to interaction data, and substandard results are optimized. According to the method, user state perception is realized through multi-modal information fusion, an adaptive closed-loop mechanism of emotion prediction and interaction control is constructed, and the response capability and interaction naturalness to a dynamic state are improved.

A visual synthesis-based virtual or augmented reality pain treatment apparatus and device. In the apparatus, an interaction control unit generates a pain stimulation scheme matching a current patient to be treated and sends the pain stimulation scheme to a data processing unit. The data processing unit, on the basis of the received pain stimulation scheme, generates a virtual reality environment and a virtual stimulation source visible to the patient in the virtual reality environment. A display unit displays the virtual reality environment and the virtual stimulation source to said patient. The data processing unit, on the basis of a pain category to be induced, determines a stimulation target of a limb and parameters of the virtual stimulation source. The display unit drives the virtual stimulation source to implement a visual approaching motion to the stimulation target of the patient so as to achieve non-real stimulation. The somatosensory system of the patient is activated by means of a vision-nerve coupling mechanism to induce the patient to feel a tactile sensation, a thermal sensation, and / or a cold sensation at the stimulation target and in a nearby area thereof, thereby achieving neuromodulation therapy of a pain pathway.

The invention belongs to the field of visual impairment assistance, and particularly relates to a visual impairment person perception guide interaction control system and method, and the system comprises a multi-source sensor module, an information processing and analysis unit, an interaction feedback module, an intelligent Internet of Things module, and a user preference and scene self-adaption module. According to the visual impaired person perception guide interaction control system and method, through a multi-source sensor fusion technology, the limitation of a single sensor is effectively overcome. The high-definition imaging and low-light enhancement capability of the visual sensor, the close-range precise detection of the ultrasonic sensor, the stable motion monitoring of the inertial measurement unit and the high-precision positioning of the global navigation satellite system cooperate with one another, so that the comprehensive and precise sensing of the environment is realized, and the system is convenient to adapt to different environments. The accuracy of obstacle detection, target recognition and positioning is greatly improved, a solid and reliable environment cognition basis is provided for visually impaired people, and the visually impaired people can more accurately know the surrounding environment condition.

This application relates to a human-computer voice interaction control method and system based on a smart TV. The method includes acquiring voice data within a preset range, processing the voice data to obtain voice feature data carrying control commands; performing feature analysis on the voice feature data using a preset voice analysis model to extract wake-up keywords and compare them with a preset command library to obtain control command comparison results; sending a secondary confirmation request to the user based on the control command comparison results, and combining the confirmation voice information from the user feedback to perform command recognition evaluation and correct command deviation processing to obtain the corrected control command; performing function switching processing on the TV according to the correct control command, and optimizing the display effect by linking and adjusting related devices based on the program display requirements after the switch to obtain human-computer voice interaction control data. This application has the effect of improving the intelligence of voice interaction control of smart TVs.

An information processing method includes: displaying a video playback interface in a bullet comment display mode; displaying target information in a process of playing a video, and outputting an interaction control related to the target information; and displaying bullet comment interaction content in the video playback interface in response to a trigger operation for the interaction control.

The invention provides an edge session seamless migration method, system and device and a storage medium, which are suitable for real-time session scenes such as remote desktops, screen streaming media, interaction control and the like. The method comprises the following steps: generating a migration token based on trigger conditions such as load, link quality and proximity, executing snapshot and incremental log copying of a session state, establishing a parallel communication channel in a target relay, and completing NAT penetration and quality detection; calculating a sequence number and time offset between a source relay and a target relay, constructing a repetition suppression and ACK mapping mechanism, realizing mirror image drainage in a parallel window, and completing main path switching after a QoE condition is satisfied; and rollback control and key context synchronization are supported, and the stability and security of the migration process are ensured. The scheme has the advantages of low time delay, no interruption, high reliability and the like, and is suitable for various edge deployment and complex network environments.

The invention belongs to the technical field of multimedia publishing management and control, and particularly relates to a distributed multimedia publishing system based on environment interaction control, which comprises an environment multi-dimensional perception fusion module, a dynamic content decision module, a distributed resource scheduling module, a multi-mode interaction feedback module, a publishing quality monitoring module and a supervision center, according to the method, the dynamic environment feature vector is generated by collecting and fusing the multi-source environment data in real time, the content publishing strategy is dynamically generated based on the decision tree algorithm and the user behavior data, real-time linkage of the content and the environment is achieved to reduce manual intervention, and through distributed resource scheduling and intelligent load balancing, the user experience is improved. The resource utilization rate is optimized, energy consumption is reduced, multi-dimensional interaction such as voice, gestures and touch screens is supported to remarkably improve the user participation degree, service continuity is guaranteed by monitoring key indexes in real time and triggering a self-adaptive repairing mechanism, and closed-loop optimization of environment perception, dynamic decision making, resource scheduling and interaction feedback is achieved.

The invention relates to the technical field of digital exhibition hall intelligent control, and discloses a multi-mode digital exhibition hall multimedia equipment interaction control method and system. The method comprises the following steps: collecting and cutting a continuous behavior data stream of a user, and analyzing spatial-temporal characteristics of behavior fragments to establish dynamic mapping between behavior intentions and equipment responses; constructing a semantic deconstruction model, and decomposing the complex interaction scene into atomic interaction units which can be independently processed; generating an interaction quality evaluation index and dynamically correcting the processing priority of each atomic unit by analyzing closed-loop association of equipment response and user feedback; and finally, fusing the corrected unit and the real-time environment state to generate an equipment operation instruction sequence. According to the method, refined analysis and self-adaptive intelligent control of concurrent and complex interaction scenes are realized, and the system response accuracy and the natural fluency of multi-user interaction experience are improved.

The invention provides a multimedia interaction control method and system based on a man-machine feedback closed loop, and relates to the technical field of financial science and technology, and the method comprises the steps: obtaining the multi-mode original feedback data of a user in an interaction environment in real time; preprocessing the multi-modal original feedback data to obtain preprocessed multi-modal feedback data; performing space-time coupling processing on the preprocessed multi-modal feedback data to generate multi-modal fusion features; dynamically determining a plurality of feature reference points based on feedback data of different modalities in a feature space corresponding to the multi-modal fusion features; the feature reference points at least comprise a user pupil center coordinate point in the visual feedback data, a fundamental frequency energy peak point in the voice feedback data and a pressure distribution gravity center point in the tactile feedback data. According to the method, space-time cooperative processing, dynamic feature quantification and closed-loop adaptive compensation of multi-modal feedback in a financial scene can be realized, and the instruction precision and information response timeliness of financial interaction are improved.

The invention relates to the technical field of data processing, and discloses a multi-scene interaction control method and system in an IPTV education platform. The method comprises the steps that a user behavior data set is generated through educational behavior Latin hypercube sampling, a standardized educational scene type is obtained based on three-dimensional similarity calculation, an educational space-time hypergraph is constructed to extract scene feature vectors, a resource optimization model with the minimum delay cost as the target is established, and a standardized educational scene is obtained. And pre-allocation of network bandwidth and server resources and rapid scene switching scheduling are realized. The problem that multi-scene interaction control in an IPTV education platform lacks specialized sampling, modeling and optimization technologies is solved. According to the invention, the response speed of education scene switching and the intelligent level of resource allocation are improved.