587 results about "Interaction control" patented technology

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 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 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 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 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 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 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.

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.

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 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 intelligent decision making, can be applied to business scenes such as financial science and technology and medical health, and discloses an interaction control method, device and equipment based on multi-source perception, and a medium, and the method comprises the steps: collecting and preprocessing multi-source heterogeneous perception data in an operation environment, and generating a standardized perception data set; analyzing the current state information of the interaction object and the constraint condition of the working environment based on the standardized sensing data; generating an action strategy by using the optimization model in combination with the task target and controlling the robot to execute; and collecting execution feedback data in the execution process, adjusting and controlling output according to the execution deviation, and performing safety monitoring and optimization model updating based on the execution feedback data. According to the method, the execution feedback data is introduced into the safety monitoring and optimization model updating process, closed-loop self-adaptive control is formed, the robot can dynamically adjust the action strategy according to the state change, and therefore the execution safety and adaptability in the complex environment are improved.

The invention discloses an inspection interaction control method based on three-dimensional live-action virtual-real mapping, belongs to the technical field of industrial inspection and digital operation and maintenance, and aims to solve the problems of virtual-real space interaction splitting, model updating lagging and control closed loop deficiency in a traditional inspection mode. A system integrating laser scanning and positioning is used for collecting live-action data and constructing a high-fidelity three-dimensional live-action model, then high-precision feature matching and space alignment are carried out on the high-fidelity three-dimensional live-action model and a preset virtual inspection model, a stable virtual-real mapping relation is established, an operator can input a control instruction in a natural interaction mode, and the real-time performance of the system is improved. According to the mapping relation, the instruction is analyzed into specific control parameters for the physical scanning system, the physical scanning system is driven to adjust the scanning posture or path so as to pertinently collect and update data, and the three-dimensional live-action model is fused and updated in real time. According to the method, accurate linkage of virtual and real spaces and dynamic enhancement of the model in the inspection process are realized, and the interactivity, the real-time performance and the intelligent level of inspection are remarkably improved.

The invention discloses a wheelchair robot which comprises a seat and a movable chassis, an interaction control module and a motion control module are arranged on the movable chassis, a mechanical arm is arranged on the seat, a first camera is arranged on the mechanical arm, and a second camera is arranged on the seat. A first radar and a second radar are arranged on the two sides of the movable chassis respectively, and the first radar, the second radar and the second camera are electrically connected with the motion control module. Through cooperation of the first camera, the second camera, the first radar and the second radar with the interaction control module and the motion control module, the detection visual field of the wheelchair robot can be widened, so that the surrounding environment of the wheelchair robot is comprehensively sensed, and the safety of the wheelchair robot during use is improved.

The invention relates to the field of unmanned aerial vehicle control, and discloses a multi-modal fusion unmanned aerial vehicle intelligent interaction control method, which comprises the following steps: S1, receiving an interaction instruction, and carrying out analysis and expected generation; s2, executing fine granularity perception and consistency verification; the unmanned aerial vehicle end constructs an actual observation semantic distribution map at the current moment based on the environment data; the unmanned aerial vehicle end compares the actual observation semantic distribution map with the expected nine-sector semantic distribution map, and calculates an expected-observation consistency score between the actual observation semantic distribution map and the expected nine-sector semantic distribution map; S3, constructing a semantic weight topology memory index chain; and S4, executing navigation failure judgment and self-adaptive backtracking. The multi-mode instruction is analyzed through a base station end large language model, a fuzzy natural language or gesture is converted into a specific verifiable visual expectation standard, and the effect that closed-loop verification is conducted on the instruction execution condition through environment semantics while flight control is executed is achieved.

The invention discloses a digital twinborn mechanical arm gangue poking training platform based on multi-sensor fusion and a construction method thereof, a real environment is perceived by constructing a digital twinborn model of a high-fidelity mechanical arm and a working environment and introducing a multi-sensor fusion entity layer, a virtual environment is provided for reinforcement learning Agent, large-scale trial and error learning is carried out, and the real environment is simulated. And an intelligent shifting strategy for irregular gangues is formed. According to the platform, through the virtual-real interaction control module, the real-time unified environment state output by the multi-sensor fusion entity layer is mapped to digital twinning, a trained strategy is converted into a control instruction capable of being executed by a real mechanical arm to be issued, the training cost is greatly reduced, the safety is improved, and meanwhile the training efficiency is improved. And efficient, accurate and self-adaptive gangue poking operation of the mechanical arm in a complex unstructured environment is achieved, and the mechanical arm has wide industrial application prospects.

The invention relates to the technical field of interaction control, and discloses an interaction control method and device, a display screen and a computer storage medium, and the method comprises the steps: displaying a cursor at a first position of the display screen; receiving a control operation of the user at a second position of the display screen, wherein the control operation comprises a gesture operation or a key operation; in response to the control operation, moving the cursor to a third position; the third position is determined according to operation information corresponding to the control operation. According to the embodiment of the invention, the technical problem that touch control is inconvenient when a large touch screen performs touch control operation is solved, so that a user does not need to frequently move the position to perform touch control operation, and the fluency of man-machine interaction is improved.

The embodiment of the invention provides a gesture instruction recognition method, electronic equipment and a vehicle, and the method comprises the steps: obtaining multi-modal sensor data corresponding to a gesture instruction in response to the gesture instruction of a driver and passengers; identifying corresponding initial gesture feature data according to each modal sensor data, and determining initial gesture fusion feature data among the modal sensor data according to the modal contribution degree of the modal sensor data and the initial gesture feature data; and determining final gesture fusion feature data based on the initial gesture fusion feature data, generating a gesture instruction execution action of the vehicle according to the final gesture fusion feature data, controlling the vehicle to execute the gesture instruction execution action, and obtaining the gesture instruction execution action of the vehicle through multi-modal sensor data fusion and feature calculation based on modal contribution degree. Effective gesture features are accurately screened, execution actions are generated, and high-robustness and low-misjudgment-rate interaction control of gesture instructions in a vehicle cabin is achieved.

The invention relates to the technical field of voice semantics, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a voice interaction control method, device, equipment and medium, and the method comprises the steps: obtaining multi-mode perception data, and constructing a dynamic scene model; session feature parameters are extracted and input into a decision model to generate a strategy parameter set; a dialogue process and expected voice output are generated according to the strategy parameter set and voice characteristics of the voice interaction device; controlling the voice interaction device to execute voice output and collect actual voice output; monitoring an error between the actual voice output and the expected voice output, and performing compensation adjustment; and collecting feedback data after the voice interaction session is ended, and optimizing the model and the control parameters according to the feedback data. According to the method, closed-loop control of perception, decision, output and feedback is established, so that the voice interaction equipment can dynamically adjust voice output according to a real-time environment and user characteristics and continuously perform self-learning optimization, and the accuracy and naturalness of voice interaction are improved.

The invention provides an automobile personalized unlocking and locking prompt tone interaction control system, and relates to the technical field of intelligent interaction, and the system is characterized in that the system comprises a control module which is used for receiving an instruction, processing data, and coordinating the work of each module; the storage module is used for storing preset prompt tone resources and user personalized audio files; the sound playing module is used for playing audios; the cloud sound big model generation module is used for generating a customized audio file according to a user demand; and the interaction module is used for realizing instruction input and feedback interaction between the user and the system. The method has the advantages that high personalized setting can be realized, the interestingness and emotion connection of human-vehicle interaction are enhanced, meanwhile, multi-mode internal and external flexible interaction of the vehicle is supported, and the extension and optimization of sound effect styles can be realized in cooperation with a cloud loud sound model.

Embodiments of the present disclosure provide an interaction method and apparatus, an electronic device, and a storage medium. The method includes: displaying, in a search result page, at least one interaction control corresponding to a target object in response to a search operation for the target object; and displaying a target animation in response to a trigger operation for a target interaction control in the at least one interaction control, wherein the target animation is an animation of a target visual element, and the target visual element is associated with the target object.

The invention discloses a metering detection intelligent glasses system integrating artificial intelligence visual identification and a cloud platform, and relates to the technical field of computer software, the metering detection intelligent glasses system comprises an intelligent glasses driving module and adaptive hardware, and has the functions of dynamic scheduling, multi-thread processing, communication self-adaption and non-lagging AR rendering; the AI visual identification module supports batch identification, fine defect detection, off-line operation and incremental learning by using a lightweight model; the cloud platform software framework module adopts a distributed micro-service framework to realize data partition storage, real-time parallel analysis and the like and elastic capacity expansion and contraction; the interaction control module develops a multi-mode program and supports batch instructions and the like; and the system collaboration module realizes multi-module scheduling based on event driving, and ensures efficient collaboration of the whole detection process. According to the method, the precision, efficiency and environmental adaptability of measurement detection are remarkably improved, the batch processing capacity and the network fluctuation coping capacity are greatly enhanced, and efficient and reliable software support is provided for measurement detection.

The utility model discloses an interactive visual training system, which belongs to the technical field of visual training equipment, and comprises an imaging module, a somatosensory tracking module, an eye movement tracking module and an interactive control module, and the imaging module comprises imaging equipment for displaying training contents; the somatosensory tracking module comprises a limb action capturing device used for capturing limb actions of the trainee; the eye movement tracking module comprises an eyeball action capturing device for capturing eyeball actions of the trainee; the interaction control module comprises a controller, the controller is used for receiving the data and converting the data into a limb action instruction and an eyeball action instruction, and the imaging module adjusts training content displayed by the imaging device according to the limb action instruction and the eyeball action instruction. By combining imaging display, somatosensory control, eye movement tracking and the like, richer, interactive and personalized visual training is provided for trainees, coordinated training of bodies, brains and eyes is realized, and the problems of single training content and poor interactivity are avoided.

This invention relates to a force feedback handle and its control method, belonging to the field of human-computer interaction technology based on tactile and force sensing. The force feedback handle is not only miniaturized but also has advantages such as low moment of inertia and good response, making it applicable to gantry crane operation, robot manipulation in extreme environments, and helicopter towing. The force feedback handle of this invention exhibits independent motion in two degrees of freedom, requiring no decoupling. In use, by interactively controlling the position of the handle in both degrees of freedom with the feedback force—that is, increasing the absolute value of the position in one degree of freedom corresponds to a corresponding increase in the damping force in the other—accidental activation can be prevented.

The application discloses a kind of man-machine interaction method of vehicle, nonvolatile storage medium and vehicle.Therein, the method includes: starting the man-machine interaction mode of vehicle, wherein, man-machine interaction mode is used to indicate the mode between vehicle and the user located outside vehicle interaction;Interaction information corresponding to man-machine interaction mode is projected to the first preset area on vehicle;Select information corresponding to interaction information is projected to the second preset area located outside vehicle;Determine the target scene parameter corresponding to man-machine interaction mode, wherein, target scene parameter is obtained by at least one scene parameter being selected by target selection item in at least one selection item by user;Target device is controlled based on target scene parameter, wherein, target device is used to create the atmosphere of the scene where vehicle is currently located according to target scene parameter.The present application solves the technical problem that the experience of user interaction control of the scene outside the vehicle in the related art is relatively low.

This invention belongs to the field of human-computer interaction technology and relates to a human-computer compliant interaction control method based on a multi-dimensional force sensor. This method involves setting characteristic parameters for switching human-computer interaction control modes; measuring the pre-grasping state using a multi-dimensional force sensor to obtain the gravitational disturbance of the gripper in the pre-grasping state; measuring the robot's grasping state using a multi-dimensional force sensor to obtain the gravitational disturbance of the object; calculating the automatic switching characteristic parameters for the human-computer interaction control mode; and achieving compliant human-computer interaction by comparing the automatic switching characteristic parameters with the switching characteristic parameters and by applying preset constraints. This invention achieves a quasi-balance between the human gripping force and the object's gravity at the moment of object transfer and release, thereby significantly reducing the impact during the human-computer interaction process and improving the compliance and safety of the interaction.

Provided in the embodiments of the present disclosure are methods and apparatuses for interaction control, a device, a medium, and a program product. A method comprises: receiving voice information of a user from a wearable device connected to a terminal device; in response to receiving the voice information, at least on the basis of a current interaction state at the terminal device, determining a target function to be executed at the terminal device; executing the target function at least on the basis of the voice information; and providing at the terminal device a reply to the voice information, the reply indicating an execution result of the target function.