191 results about "Control Interaction" patented technology

A system uses a large language model (LLM) to implement a controlled artificial intelligence chat environment. The system may control interaction with the LLM using prompt templates that may be selected, customized, and / or modified based on information known about the user with whom the LLM will be interacting. Further, the system may evaluate output of the LLM to make changes to the LLM, the prompt templates, and so on. In some implementations, the system may use evaluation training data to adapt and fine-tune the LLM and / or another language model to evaluate output of the LLM in order to evaluate the efficacy of the chronic condition and / or disease management coaching path(s), and make improvements to the online or offline implementation of the language model in the future.

The invention discloses a dynamic water quality monitoring system based on an unmanned ship and a data acquisition and distribution algorithm. Comprising an unmanned ship platform module, an initial navigation path setting module, a water quality data acquisition module, a dynamic adjustment and optimization module, a control interaction module and a dynamic adjustment and optimization module, wherein the dynamic adjustment and optimization module dynamically adjusts the navigation strategy and sampling frequency of the unmanned ship in a target to-be-detected water area through a second branch of a first neural network model; the unmanned ship can sail autonomously, continuous and global water quality monitoring is achieved, through an efficient data processing algorithm, the accuracy and reliability of data are improved, a scientific basis is provided for water quality management, a distributed algorithm model is achieved to conduct predictive analysis on each specific target sampling point, the accurate predictability of unmanned ship monitoring is improved, and the water quality monitoring efficiency is improved. The monitoring strategy is dynamically adjusted according to actual requirements, optimal configuration of monitoring resources is achieved, the monitoring cost is reduced, the water quality change trend is found in advance through prediction analysis of the neural network model, and powerful support is provided for early warning and emergency response.

Provided are systems and methods for AI management configured to guide interactions between end users systems and generative AI services. Various examples can manage data operations, among other options. In various embodiments, an AI management system is configured to host an interactive session via generating workflow steps for controlling interaction with AI models. The interactive session is configured to identify data management operations on user specified data sources. The AI management system can be used to analyze the data sources specified to generate a canonical data format spanning the multiple data sources, generate code for mapping the data sources into a canonical format, normalize the resulting data, cleanse the resulting data, validate the resulting data, and automatically generate code for each such function that can then be triggered by users interacting with the user interface.

The invention relates to an unmanned aerial vehicle power management and information monitoring system, and the system comprises a power management and information monitoring device which is connected among an unmanned aerial vehicle power supply, an unmanned aerial vehicle flight controller, and an unmanned aerial vehicle load set. Wherein the power management and information monitoring equipment is internally integrated with a unified power management module used for receiving electric energy of an unmanned aerial vehicle power supply and providing one or more transformed stable power supplies for an unmanned aerial vehicle load set; and the information and control concentrator module is used as an information and control relay among the unmanned aerial vehicle flight control, the unmanned aerial vehicle load set and the sensor. The invention aims to help to solve the problems of complex flight control interface and overweight operation burden caused by direct data and control interaction between numerous airborne equipment and a flight controller, and low system integration degree and insufficient reliability caused by decentralized management of a power supply in an existing unmanned aerial vehicle system.

The invention provides a vehicle lane control interaction method and device, electronic equipment, a vehicle and a medium, and the method comprises the steps: obtaining the real-time sensing data of the surrounding environment of the vehicle, and generating and displaying a lane touch identifier corresponding to a lane in the surrounding environment on an intelligent driving sensing image of the vehicle according to the real-time sensing data; detecting a touch operation received by the lane touch identifier in real time, determining a lane corresponding to the touched lane touch identifier as a target lane, and displaying at least one lane control mode; any one lane control mode in the at least one lane control mode is determined as a target lane control mode; and according to the real-time lane information, controlling whether the vehicle runs on the target lane according to the target lane control mode. According to the man-machine interaction method for vehicle lane control provided by the invention, the driving safety is ensured while the individuation degree of an intelligent driving system is improved, so that the user experience of automatic driving is improved.

A system can generate a risk assessment associated with an identity element used in interactions associated with a user entity. For example, the system can receive historical data related an identity element associated with a user entity, the identity element used in a set of interactions associated with the user entity. The system can generate a binomial distribution of the historical data associated with the identity element. The system can determine, based at least in part on the binomial distribution of the historical data, a risk indicator associated with the identity element. The system can control, based at least in part on the risk indicator associated with the identity element, an interaction involving a target entity and the user entity using the identity element.

A method for compensating for dynamic changes in a body of a patient during a controlled interaction with the body includes acquiring data from at least one sensing device disposed on the body and detecting a change along at least one optical fiber of the sensing device caused by dynamic changes associated with the body during the controlled interaction. A respiratory gating signal is generated based on the change along the at least one optical fiber of the sensing device measured over time. The method further comprises controlling relative movement between the body and an interactive device in response to the respiratory gating signal to compensate for the dynamic changes associated with the body during the controlled interaction.

A method for compensating for dynamic changes in a body of a patient during a controlled interaction with the body includes acquiring data from at least one sensing device disposed on the body and detecting a change along at least one optical fiber of the sensing device caused by dynamic changes associated with the body during the controlled interaction. A respiratory gating signal is generated based on the change along the at least one optical fiber of the sensing device measured over time. The method further comprises controlling relative movement between the body and an interactive device in response to the respiratory gating signal to compensate for the dynamic changes associated with the body during the controlled interaction.

The interactive game room systems described herein incorporates various components such as player data, game data, control data, and a network of servers to support interactive game room facility management. Player data may include names, team affiliations, historical gameplay, and preferences, while game data is generated from sensors within the room, tracking player actions and game states. Control data can regulate technician access to various features, depending on authorization levels and game types. These systems can be interconnected via servers, enabling seamless communication between game logic, status screens, control apps, and site operations. Machine learning can be used to analyze player data and control interactions, optimizing game configurations and technician controls. Additionally, machine learning can improve team onboarding such as assignments, waiver processing, and gameplay by leveraging historical data to offer personalized experiences. Together, this can create a robust, flexible environment for managing interactive games, allowing for efficient gameplay.

The utility model provides a charging gun, relates to the technical field of charging guns, and solves the problem that a charging gun cannot provide control interaction and is difficult to configure and use in the prior art. The charging gun can provide a fault prompting function for a user through a display screen and a three-color indicating lamp on the charging gun, so that the user can know a fault reason conveniently, and the charging gun can also provide a corresponding touch control function for the user through a touch key, so that the user can perform touch control configuration on the charging gun conveniently. The charging gun can perform corresponding detection, so that a user can know the current charging state of the charging gun and perform corresponding configuration, and the use experience of the user can be improved.

The invention discloses a multi-person interaction method based on a large-space computing technology, and relates to the technical field of multi-person interaction. In order to solve the technical problem that in the prior art, most of existing multi-user virtual interaction systems depend on a single interaction area, so that the user experience is poor when multiple users interact at the same time, the technical scheme provided by the invention is as follows: a multi-user interaction method based on a large-space computing technology is provided. Comprising the following steps: dividing a virtual space into a plurality of functional areas; controlling the temperature of the interaction area and the non-interaction area in real time; sharing of virtual roles is realized through the cloud computing platform; a sharing conflict coordination mechanism is introduced, an operation request of a user for a virtual role is managed, and conflicts are coordinated; creating a virtual computing space and dynamically allocating computing resources by combining distributed computing and a cloud platform; a digital co-construction and sharing platform is built through a 5G network and a holographic image technology, and multi-user interaction and co-construction and sharing of virtual articles are achieved. The method is suitable for being applied to virtual reality scene building work of multi-person interaction.

The invention discloses a three-dimensional scene multi-dimensional instruction collaborative mapping method and system based on a multi-modal large model and a knowledge graph, and belongs to the technical field of artificial intelligence. The method comprises the following four steps: acquiring and preprocessing a multi-mode instruction; performing instruction analysis and element disassembly, calling a built-in pre-training large language model by the multi-modal large model, disassembling the instruction into appearance, scene and control interaction elements through customized Prompt, and processing logic and dependency relationships; multi-dimensional state driving is carried out, and appearance parameter mapping, action sequence generation and cross-modal conflict resolution and semantic-voice-expression linkage execution are achieved through appearance, action and language intelligent agents; and the central coordinator schedules agent parallel tasks based on the knowledge graph. The system correspondingly comprises a function module for executing four steps. According to the method, the multi-dimensional instruction cooperative control precision and response efficiency of the three-dimensional scene can be effectively improved, the labor cost is reduced, and the method is adaptive to diversified interaction scenes.

The invention discloses a robot compliance force control interaction method, system and device for a collaborative sewing scene and a storage medium. The method comprises the steps of setting a preset period of a contact force track, a speed track and a pose track; before the task is started, collecting data of a plurality of groups of force sensors, completing dynamic gravity compensation, and calculating real contact force in real time; in the task process, the real contact force is continuously obtained, the speed deviation and the pose deviation are obtained, the real contact force, the speed deviation and the pose deviation are input into a compliant controller based on an admittance model, and the target pose of the mechanical arm in the next step is dynamically adjusted; the compliant cooperation is repeatedly executed until the whole cooperation sewing task is completed; after the task is finished, a parameter optimization algorithm based on smooth iterative learning is constructed, the real contact force trajectory, the speed trajectory and the pose trajectory are used as input, the smooth iterative learning algorithm autonomously optimizes parameters of a compliant controller, and the optimal force-position trajectory tracking performance is achieved. According to the invention, a safe and stable robot cooperation sewing task is realized.

The invention provides an XR interaction method, device and equipment based on voice control, and belongs to the technical field of human-computer interaction. The method comprises the following steps: receiving a multi-modal interaction data stream acquired by a multi-modal sensor; recognizing and analyzing a voice signal in the multi-modal interaction data stream to determine a corresponding voice control instruction; wherein the voice control instruction comprises an operation intention and space description; the spatial description is spatial constraint information of the user on the target operation object; determining a corresponding target interaction space area based on the voice control instruction and one or more non-voice behavior information synchronized with the voice signal in the multi-mode interaction data stream; and matching a target operation object corresponding to the voice control instruction according to the information of each operable object in the target interaction space region, and executing an XR interaction operation corresponding to the operation intention according to the target operation object. Therefore, high-precision, high-dynamic-adaptability and high-reliability voice control interaction is realized.

The invention relates to the technical field of smart home and health monitoring, and particularly discloses a sleep monitoring control interaction system and method based on artificial intelligence and data fusion, and the system comprises a sensing data acquisition module, a sleep environment recognition module, a mattress adjustment judgment module and a control strategy feedback module. A high-density sensor array network is embedded in a mattress body and is used for detecting pressure distribution data and temperature distribution data at a current sleep time point in real time; the sleep environment at the current sleep time point is further judged, the sleep environment is divided into a single-person sleep environment and a multi-person sleep environment, and the multi-person sleep environment is further divided into an adhesive multi-person sleep environment and a non-adhesive multi-person sleep environment; and finally executing dynamic adjustment strategy analysis. By monitoring and analyzing the pressure distribution in real time, the system can identify the part where a human body is in contact with the mattress and the pressure change, so that the supporting structure of the mattress is dynamically adjusted, and the sleep quality is improved.

The invention relates to the technical field of computer science, in particular to a robot control reinforcement learning method and device based on dynamic potential energy reward, and the method comprises the steps: obtaining the robot information and initial state information of a robot; based on the robot information and the initial state information, at least one round of robot control interaction is carried out on the robot, and in each round of control interaction, a dense reward value constructed based on dynamic potential energy of the robot is calculated based on the control instruction and the state information of the robot; and training an initial control strategy neural network of the robot by combining a dense reward value constructed based on the dynamic potential energy and training data generated in a control interaction process so as to obtain a final control strategy neural network. Therefore, the problems that in the related technology, the potential energy function is fixed, so that the award obtained by each state in the whole training process is determined, strategy exploration is limited, and complex control cannot be carried out on the robot are solved.

The invention provides a nanoscale metal tip intelligent detector and a use and analysis method thereof. The device integrates a high-precision imaging and positioning module, an intelligent analysis module, an intelligent control interaction module and an automatic execution mechanism. The imaging and positioning module is composed of an optical microscope, a high-resolution CCD camera and a three-axis precision objective table and supports nanoscale morphology feature capture and micron-scale positioning precision. The intelligent analysis module can automatically extract the curvature radius, the taper angle, the surface roughness and other key parameters. The control interaction module is coupled with the automatic execution mechanism, so that automatic control of the detection process and remote storage and optimization of process data can be realized. The device can automatically complete the detection and intelligent analysis of the morphology of the nanoscale metal tip, is compatible with application scenes such as single nanopore / pore channel preparation, scanning probe tip morphology characterization and nano device detection, and remarkably improves the operation efficiency while maintaining high-precision detection.

The invention discloses a bridge self-adaptive rapid dismantling system and method based on digital twin and SPMT module vehicles, and the system comprises construction equipment which is used for cutting and dismantling a bridge structure; the SPMT module vehicle cluster is used for bearing and jacking a bridge structure; the digital twinborn decision-making platform comprises a data acquisition module, a simulation analysis module and a control interaction module, and the data acquisition module is used for acquiring operation state data of a bridge structure and construction equipment in real time; the simulation analysis module is used for carrying out stress analysis on the bridge structure, predicting stress distribution in the cutting, jacking and transportation processes, comparing preset data with a threshold value, triggering a corresponding three-level alarm mechanism if the preset data is greater than the threshold value, and optimizing a moving path of the SPMT module vehicle by adopting a preset dynamic path planning algorithm; and the control interaction module is used for realizing real-time data exchange and interaction control among the digital twinborn decision-making platform, the SPMT module vehicle and the construction equipment. The construction safety level and efficiency can be remarkably improved.

A robot system includes a multi-joint robot arm including a plurality of joints; a robot controller configured or programmed to control movement of the multi-joint robot arm; an interactor configured to interact with a workpiece; a signal output configured to output a moving amount signal based on a moving amount of the interactor arranged on a distal end part of the multi-joint robot arm at a fixed time period; and an interaction controller configured or programmed to control interaction of the interactor with the workpiece based on the moving signal output by the signal output.

A winch control apparatus (100) for a vehicle, a control system (200), a vehicle (1000), a winch control interaction method, an interaction apparatus (500), an interaction system (600), and a computer readable storage medium (700). The winch control apparatus (100) comprises a domain controller (20) and a high-voltage winch (30). The domain controller (20) is used for sending a control signal to the high-voltage winch (30). A controller (31) is used for receiving the control signal, and controlling a motor (32) on the basis of the control signal. Therefore, the controller can interact with the whole vehicle, thereby improving the convenience of control over the high-voltage winch.

The present application discloses a chassis component control device and method for a hierarchical wire-controlled chassis system, wherein the chassis component control device includes a function control interaction module, an execution component control module, and a chassis domain controller. The chassis domain controller is connected to each functional unit in the chassis function module of the hierarchical wire-controlled chassis system to control each functional unit. The execution component control module includes a function control subsystem with the same number of functional units as the chassis function module. Each function control subsystem is used to control the connected functional unit. The function control interaction module controls each functional unit in the chassis function module through the chassis domain controller or the execution component control module according to a preset control implementation protocol. Since the functional units can be independently controlled by the chassis domain controller or the execution component control module, the respective advantages of the hierarchical wire-controlled chassis system and the centralized chassis domain controller can be brought into play.

The invention provides a steel pipe whole-process intelligent tracking system based on multi-mode sensing fusion, and relates to the technical field of ferrous metallurgy intelligent manufacturing. The system comprises the following modules: a visual perception module, which is used for collecting the appearance characteristics, the spatial position and the motion state of a steel pipe in the whole process of steel pipe tracking; the one-by-one tracking and decision-making module is used for constructing a closed-loop work flow comprising data acquisition, fusion processing, decision-making output and feedback optimization by deeply fusing visual perception information and multi-source industrial signals; and the control interaction module is in two-way communication with the bottom PLC and an upper computer, receives equipment signals, feeds back the equipment signals to the tracking module, issues a tracking / alarming instruction to the PLC and synchronizes data to the MES. According to the method, the problems of blind areas, information chain scission and manual dependence of traditional tracking are solved, the whole process of the hot-rolled seamless steel pipes from a cooling bed area to material frame bundling through saw cutting segmentation is achieved, and one-by-one accurate tracking and quality control are achieved.

A method for compensating for dynamic changes in a body of a patient during a controlled interaction with the body includes acquiring data from at least one sensing device disposed on the body and detecting a change along at least one optical fiber of the sensing device caused by dynamic changes associated with the body during the controlled interaction. A respiratory gating signal is generated based on the change along the at least one optical fiber of the sensing device measured over time. The method further comprises controlling relative movement between the body and an interactive device in response to the respiratory gating signal to compensate for the dynamic changes associated with the body during the controlled interaction.

An apparatus includes a first qubit and a second qubit, and a qubit coupler coupled between the first qubit and the second qubit. The second qubit includes a first pattern and a second pattern, wherein the first pattern is configured to store data. The qubit coupler includes a first mode and a second mode, and operates in a first state or a second state. In a first state, the first qubit swaps a first pattern coupled to the qubit coupler and the second pattern of the second qubit swaps a second pattern coupled to the qubit coupler to suppress interaction between the first qubit and the second qubit. In the second state, the first pattern of the first qubit and the second qubit exchanges both the first pattern and the second pattern coupled to the qubit coupler to effect interaction between the first qubit and the second qubit for entanglement gate operation in response to a control signal applied to the qubit coupler.

The invention relates to the technical field of cockpit display and control interaction testing, and discloses a cockpit display and control interaction testing system based on multi-modal fusion, and the system comprises an interaction data input module which is used for obtaining the basic parameters of a to-be-tested cockpit display and control device, such as the device model and the screen size; the multi-mode signal acquisition module is used for acquiring visual, auditory and tactile signals in the cabin environment based on the basic parameters; the fusion feature processing module is used for carrying out feature fusion processing on the multi-modal signals to obtain interactive feature fusion data; the test scene construction module is used for generating a standardized test scene based on the interactive feature fusion data; and the interactive performance verification module inputs the standardized test scene into the to-be-tested equipment to execute a verification test, and transmits a result to the display terminal for presentation. According to the system, acquisition and fusion of multi-modal signals are realized, a test scene close to reality can be generated, and the accuracy and efficiency of the interaction performance test of the cabin display and control equipment are improved.

According to one aspect, learning physics-based interactions from demonstration may include learning a sparse embedded interaction graph from a fully connected graph indicative of an interaction between a first character and a second character based on cross attention between a pose and a current interaction graph and training a policy for controlling interactions between the first character and the second character based on using the sparse embedded interaction graph as a reward.

The present application proposes a method for controlling an interaction behavior of a vehicle, comprising the following steps: during an automatic parking process of the vehicle, controlling one or more lighting devices of the vehicle to emit an indication signal relating to the automatic parking process in a manner perceptible by a user outside the vehicle, controlling a lighting device of a vehicle to emit an indication signal includes projecting a visual pattern on the ground surrounding the vehicle by means of the lighting device to identify a recommended parking area and / or a restricted entry area of a user during an automatic parking process. The invention further provides a device for controlling the interaction behavior of the vehicle, the vehicle and a computer program product. In the application, the visual ground projection not only helps the user to effectively supervise the automatic parking process at a proper position, but also helps to prevent the parking operation from being interfered or bringing potential safety hazards due to the improper position of the user, thereby greatly optimizing the automatic parking experience of the user.

A system uses a large language model (LLM) to implement a controlled artificial intelligence chat environment. The system may control interaction with the LLM using prompt templates that may be selected, customized, and / or modified based on information known about the user with whom the LLM will be interacting. Further, the system may evaluate output of the LLM to make changes to the LLM, the prompt templates, and so on. In some implementations, the system may use evaluation training data to adapt and fine-tune the LLM and / or another language model to evaluate output of the LLM in order to evaluate the efficacy of the chronic condition and / or disease management coaching path(s), and make improvements to the online or offline implementation of the language model in the future.

The invention provides a touch control type man-machine interaction method and device, electronic equipment and a storage medium. The method comprises the steps that real-time sensing data obtained when sensing equipment of a vehicle senses the surrounding environment of the vehicle is obtained; wherein the surrounding environment comprises vehicles and lanes; according to the real-time sensing data, a touch identifier is generated and displayed on an intelligent driving sensing picture of the vehicle; the touch identifiers comprise a vehicle touch identifier corresponding to a vehicle and a lane touch identifier corresponding to a lane, and each touch identifier is preset with a corresponding control object and a control mode; detecting that any one of the vehicle touch control identifier and the lane touch control identifier is touched in real time, and determining the control object and the control mode corresponding to the touched touch control identifier as a target control object and a target control mode; and controlling the vehicle to run relative to the target control object according to the target control mode. According to the touch control type man-machine interaction method provided by the invention, the user can request the intelligent driving system through touch control interaction to control the vehicle to run according to own desire.

1. The name of the design product: the graphical user interface of the rapid creation management and reuse control interaction of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the product interface is the interface for displaying and interacting with the rapid creation, management and reuse of controls; the interface is used to save containers containing multiple controls and complex styles as independent units and quickly reuse them in pages with similar layouts; the front view interface is the interaction interface for creating the home page; in the front view interface, clicking the "add as control combination" button triggers the creation process, and the interface change state diagram 1 is displayed; in the interface change state diagram 1 interface, fill in the control combination information, save it to the control combination, and display the interface change state diagram 2.