226 results about "Task control" patented technology

The invention provides an interactive question and answer task processing method based on multi-agent cooperation and a related device, and relates to the technical field of artificial intelligence such as generative large language models and agents. The method comprises the steps of determining a to-be-solved target task according to natural language input of a user; the target task is decomposed into a plurality of sub-target tasks at least including interactive question and answer tasks, each sub-target task is correspondingly issued to each sub-target agent at least including an interactive question and answer agent, and different sub-agents are used for processing different types of sub-tasks; the interactive question-answering agent is controlled to present an interactive graphical user interface corresponding to the interactive question-answering task to the user, an answer result corresponding to the received feedback answer is presented, and the interactive graphical user interface comprises a question and an interactive answer area; an associated sub-target agent in the multiple sub-target agents is controlled to generate a corresponding associated processing result based on an answer result output by the interactive question and answer agent, and the associated sub-target agent is a sub-target agent which depends on the answer result and serves as part of task input information; and determining a target processing result corresponding to the target task based on the association processing result. Through application of the scheme, a better comprehensive task processing effect can be brought under the condition of lower comprehensive cost, especially for an interactive question and answer task in which a user needs to subjectively answer a proposed question and the effect is checked according to an answer result; the interactive questioning and answering agent provides the interactive graphical interface containing the question and the interactive answering area for the user, so that the task requirement of the user can be met more quickly in an interactive answering mode, and the task solving effect is improved.

The invention provides a multi-agent cooperation-based explicit result acquisition class task processing method and a related device, and relates to the technical field of artificial intelligence such as generative large language models and agents. The method comprises the steps of determining a to-be-solved target task according to natural language input of a user; the target task is decomposed into a plurality of sub-target tasks at least including clear result acquisition class tasks, each sub-target task is correspondingly issued to each sub-target agent at least including clear result acquisition agents, and different sub-agents are used for processing different types of sub-tasks; controlling each sub-target agent to output a sub-processing result corresponding to the subordinate sub-target task in combination with the personalized preference of the user, wherein the sub-processing result comprises a clear result which is output by the clear result acquisition agent and corresponds to the subordinate clear result acquisition class task; and summarizing the sub-processing results to obtain a target processing result corresponding to the target task. By applying the scheme, a better comprehensive task processing effect can be brought under the condition of lower comprehensive cost.

The invention provides an instant message inquiry type task processing method based on multi-agent cooperation and a related device, and relates to the technical field of artificial intelligence such as generative large language models and agents. The method comprises the steps of determining a to-be-solved target task according to natural language input of a user; the target task is decomposed into a plurality of sub-target tasks at least including instant information inquiry tasks, each sub-target task is correspondingly issued to each sub-target agent at least including an instant information inquiry agent, and different sub-agents are used for processing different types of sub-tasks; the instant information inquiry agent is controlled to inquire questions from the inquiry object to obtain instant feedback, and the instant information inquiry agent supports question inquiry in a background operation mode; an associated sub-target agent in the multiple sub-target agents is controlled to generate a corresponding associated processing result based on instant feedback output by the instant information inquiry agent, and the associated sub-target agent is a sub-target agent which depends on the instant feedback and serves as part of task input information; and determining a target processing result corresponding to the target task based on the association processing result. By applying the scheme, a better comprehensive task processing effect can be achieved under the condition that the comprehensive cost is lower, and in particular, an instant information inquiry task which needs to be combined with the instant information to verify whether the actual situation meets the task requirement or not and takes the verification result as instant feedback is obtained; in addition, the instant information inquiry agent also supports question inquiry (namely asynchronous task processing) in a background operation mode, so that the user does not need to stay in a session interface all the time, and other operations of the user are not influenced.

In one implementation, a device may identify a type of task and its context indicated by a prompt sent by a user for input to a language model. The device may authorize the prompt for input to the language model based on the type of task and its context. The device may make a determination as to whether a response of the language model to the prompt is authorized to be returned to the user based on the response, the type of task, and its context. The device may prevent the response from being returned to the user when the determination indicates that the response is not authorized to be returned.

The invention relates to the technical field of cloud control, in particular to a cloud-based steam cabinet control system, which comprises a humidity sampling processing module, a steam state judgment module, a task stage identification module, a control instruction reconstruction module and a scheduling execution response module. According to the method, the accuracy of steam management is improved through staged recognition of the steam release state, a matching mechanism is formed in combination with the task timestamp and the staged state, the real-time adaptation capacity in the task execution process is enhanced, a dynamic comparison and queue rearrangement mode is adopted in the task instruction updating link, and the task execution efficiency is improved. Synchronous cooperation of a control instruction and a current task state is achieved, targeted optimization of the task control instruction and dynamic adjustment of a control process are achieved through a multi-dimensional state analysis and time sequence mapping means, the feedback response efficiency, task scheduling flexibility and steam release accuracy in the equipment operation process are effectively improved, and the system performance is improved. Therefore, the adaptive capacity and the control precision of the steam cabinet control in various operation states are enhanced.

The invention discloses a real time operating system (RTOS) multi-task priority scheduling and real-time control method based on advanced RISC machines (ARM), and relates to the technical field of embedded computing and control. Comprising the following steps: S1, time slice management setting: dividing CPU time according to a preset time period to obtain time slices; s2, performing task scheduling: setting each task according to a task control block, and performing context switching and priority arbitration through an OSScheduler () function; and S3, performing exception response: performing forced interruption and exception recovery operation through a set multi-stage exception classification mechanism. Through a three-level decision model and a partition response mechanism, it can be ensured that a high-priority task can be responded in time within strict time constraints, the hard real-time requirement is met, meanwhile, CPU time is divided through a fixed time slice, a counter is updated through timer interruption, and therefore the time deviation of task execution can be reduced, and the task execution efficiency is improved. And the certainty of the system is improved.

The invention relates to the technical field of business process management, in particular to a data processing method, system and device based on business process management and a medium, and the method comprises the steps: constructing a business process model driven by an abstraction layer, and configuring a multi-protocol standardized interface; according to the business process model driven by the abstraction layer and the multi-protocol standardized interface, a process instance matched with the business scene is generated, and a task is distributed to a target client according to a task demand; managing form state circulation and node jump logic according to a task control engine; an event monitor is deployed through a process key node to monitor the process, and when the process reaches a specified node, external service calling operation is triggered to form an end-to-end automatic closed loop. Therefore, the problems of code redundancy, high maintenance cost, difficulty in quickly adapting to diversified customer requirements and the like due to the fact that business process management generally needs to be subjected to customized development for different subsystems in related technologies are solved.

The invention discloses a graphics processor, a graphics drawing method, a chip and electronic equipment, and belongs to the field of chips. The graphics processor comprises a geometric processing assembly line, and the geometric processing assembly line comprises a first task generation assembly line, a task control unit, a second task generation assembly line and a task execution unit. The task control unit is used for acquiring a first coloring result based on the received first task information in the single-pipeline mode, and outputting the first coloring result to a pipeline behind the geometric processing pipeline; and acquiring a first coloring result based on the received first task information in the double-pipeline mode, and controlling the first coloring result to enter a second task generation pipeline, and based on the received second task information, obtaining a second coloring result, and outputting the second coloring result to an assembly line behind the geometric processing assembly line. According to the geometric processing pipeline, geometric processing parts of different rendering pipelines can be combined into the same data stream.

The invention discloses a kernel task execution method, electronic equipment, a readable storage medium and a program product, and relates to the technical field of computers. The method comprises the following steps: creating at least three layers of nested mapping table structures; the first layer of mapping table stores a task identifier and a nesting relationship between the task identifier and a lower layer, and the other layers of mapping tables store control rules and corresponding nesting relationships. Target task control rule information extracted from the resource strategy file is divided into task execution control rules with the corresponding number, the task execution control rules are correspondingly stored in mapping tables of corresponding layers, and the task execution control rules serve as task execution control rule storage tables to be issued to a kernel mode; and the kernel mode performs layer-by-layer control on kernel task operation according to the task execution control rule storage table. According to the method and the device, the problem that the container scene cannot store the service requirement of the access control rule due to the fact that the eBPF Map cannot be nested in multiple layers in the related technology can be solved, and container access control can be realized in the container scene.

The invention provides a controller parameter optimization method and a task control method based on reinforcement learning, and relates to the technical field of control, and the method comprises the steps: inputting the parameters of a PID controller of a current task into a DDPG model, obtaining the parameters of a PID controller of a next task, inputting the parameters of the PID controller of the next task into the PID controller to obtain a control quantity; determining an evaluation result of the control of the PID controller based on the control quantity as a reward; taking the state, action and reward of the current time step and the state of the next time step as sample data and storing the sample data into an experience pool; and training the DDPG model based on the experience pool, and determining the target parameter output by the trained DDPG model as the optimal parameter of the PID controller. In the application stage, only the PID controller needs to output the target control quantity based on the optimal parameters, the participation of a DDPG model is not needed, and the light weight of the whole control model is realized.

The invention relates to the technical field of man-machine interaction, and provides an interactive task control method and device and a storage medium, an operation process of an interactive task comprises an execution process of a first sub-task and a second sub-task, the first sub-task can be controlled to be executed by operation of a user, and the second sub-task is controlled to be executed by an intelligent agent; the method comprises the steps of obtaining first subtask evaluation data of a first subtask in task execution time when an interactive task is in a running state; determining a preset deviation corresponding to the task execution time according to reference evaluation data corresponding to the task execution time and the first sub-task evaluation data; and according to the preset deviation, adjusting the preset interaction parameter of the intelligent agent so as to improve the difficulty adjustment accuracy of the interactive task.

The invention relates to the technical field of elevator control, and discloses an elevator task control method and system based on medical logistics robot scheduling. The method comprises the steps that according to a dispatching task of a medical logistics robot, the robot position and electric quantity information of an available medical logistics robot, a dispatching task to be executed, the floor where an elevator of an available elevator is located, the running direction, whether the elevator is fully loaded or not and the floor where the elevator needs to stop are recognized, and a distribution combination is constructed; an evaluation function is constructed according to the robot path length of each scheduling task in the distribution combination and the time of taking the corresponding available elevator, and a target medical logistics robot and a target available elevator are obtained through scheduling optimization based on the evaluation function; constructing a target control signal according to the target medical logistics robot and the target available elevator; and a scheduling path of the target medical logistics robot is generated, and elevator task control is conducted on the target available elevator according to the scheduling path and the target control signal. The accuracy of elevator task control can be improved.

The invention provides a computing chip, a computing device, a data processing method, a storage medium and a program product. The computing chip comprises one or more computing modules and is used for executing computing tasks; the command processor is used for issuing a first calculation task to the one or more calculation modules; the data transmission module is used for carrying out data transmission with an external computing chip in a remote memory direct access mode; the transmission control module comprises a task queue creating module used for receiving the control command and adding the first calculation task to a first task queue created by the task queue creating module according to the control command; the task scheduling module is used for responding to the fact that the one or more computing modules execute the first computing task, controlling the data transmission module to communicate with an external computing chip, and transmitting a computing result corresponding to the first computing task to the external computing chip in a remote memory direct access mode.

The invention provides a data processing method and device for a stream processing framework, equipment and a medium, and relates to the technical field of big data, in particular to the technical field of data warehouses. The method comprises the steps of pausing a real-time task of a stream processing framework in response to a first task control instruction, obtaining a first consumption data position corresponding to the real-time task when the real-time task is paused, and starting a first offline batch task, the first task control instruction is sent based on a real-time monitoring result of a real-time task state and consumption delay data in the streaming processing framework; after the capacity expansion operation is executed on the stream processing framework, the real-time task is started again, so that the real-time task starts to process data from a corresponding second consumption data position when the real-time task is started; wherein the first offline batch task is used for processing data between the first consumption data position and the second consumption data position. According to the invention, an integrated data warehouse of real-time stream and offline stream can be realized, and the concurrency and accuracy of data are improved.

A method for controlling a robotic manipulator according to a task comprises accepting a feedback signal including a sequence of multi-modal observations of a state of execution of the task. The multi-modal observations are processed with a neural network having a self-attention module with a hierarchically conditioned output to produce a skill of the robotic manipulator and an action conditioned on the skill. The neural network is trained in a supervised manner with demonstration data to produce a sequence of skills and a corresponding sequence of actions for the actuators of the robotic manipulator to perform the task. The method further comprises determining one or more control commands for the one or more actuators based on the produced action and submitting the one or more control commands to the one or more actuators causing a change of the state of execution of the task.

The invention relates to a matrix accelerator sharing a chip system memory and an operation method of the matrix accelerator. The matrix accelerator comprises a system memory module, a task management module, a data access module and a matrix operation module. According to the matrix accelerator, the chip system memory is directly shared through the dual-port SRAM, so that the matrix accelerator can be suitable for a navigation baseband chip with small size and low power consumption, meanwhile, when the matrix accelerator does not work, the shared memory can still be used as the chip system memory, and idle waste of memory resources is avoided. Through the task queue, a plurality of operation tasks and corresponding task control instructions can be loaded into the matrix accelerator at one time, and an interrupt signal is generated after all the operation tasks are completed to complete interaction between the CPU and the matrix accelerator, so that the efficiency of the CPU is improved to the maximum extent, and the performance of a chip system is remarkably improved.

The invention relates to an unmanned aerial vehicle cluster task dynamic recombination system and method. The system comprises a task control program, a module engine, a program API interface, a task upgrading program, an ROS2 data distribution service and a plurality of task modules. The task control program controls the starting, stopping and running state monitoring function of each module, the module engine is responsible for managing the starting, stopping and running states of the modules, the program API interface is responsible for receiving an external task upgrading request or task configuration request, the task upgrading program receives a platform external request, and the module engine is responsible for managing the starting, stopping and running states of the modules. The upgrade package information is sent to a program API interface of the task control program, the task module is a specific task processing unit, and the ROS2 data distribution service is used for realizing data interaction among the task modules. The problem that an unmanned aerial vehicle cluster system lacks the capability of performing dynamic adjustment according to actual conditions in the task execution process is solved, the flexibility, expandability and task execution efficiency of the system are remarkably improved, and effective application in a complex task environment is achieved.

The invention provides a task scheduling method for realizing equipment on an electric energy meter verification assembly line, which comprises the following steps of: determining equipment and tasks participating in scheduling according to a verification working link of an electric energy meter, and determining the workload, priority and completion time of each task; acquiring state information data of each device, after preprocessing the state information data into feature data of each device, importing the feature data into the trained multifunctional prediction model, and predicting the load capacity and fault risk of each device; calculating the load capacity of each device according to the load capacity and the fault risk of each device, and calculating the load demand of each task in combination with the workload, the priority and the completion time of each task; and constructing a target function, and solving an optimal solution to obtain a task scheduling queue in combination with the load demand of each task so as to perform intelligent scheduling task control on each device. By implementing the method, the task scheduling efficiency and accuracy are improved, the generation efficiency of the electric energy meter verification assembly line is also improved, and the verification period is shortened.

The invention discloses a general query field aggregation method and device for multi-source heterogeneous data, electronic equipment and a storage medium, and the method comprises the steps: employing a task flow annotation configurator to carry out annotation marking for each task chain in advance, and marking the task chain as a column aggregation processing flow task chain; managing an execution chain type task set marked by the same type through a task control manager, and loading a task processor to a system cache; loading a task processor in a system cache through a chained task processor, and executing a preset task based on a task process processor interface; and receiving a plurality of chained task processors through a column data aggregation executor, constructing processor request context parameters, executing the processors in sequence, and outputting an aggregation result. By means of the method and device, on one hand, flexible arrangement of the processing sequence of the function processors is achieved, dynamic expansion of the processors is achieved, on the other hand, the processing flow of field-level aggregation is unified, and the aggregation query efficiency is improved.

The present invention discloses an enterprise human resources comprehensive management platform, which relates to the field of data management technology and includes: a resource management system determination module for determining a resource management system; a management logic chain determination module for determining a management logic chain; a task management strategy determination module for determining a task management strategy; a sensitive management mode setting module for setting a sensitive management mode for sensitive data classes; a sensitive management strategy determination module for determining a sensitive management strategy; and a pre-management task control module for executing and controlling pre-management tasks. The platform solves the technical problems of the existing enterprise human resources management, such as the difficulty in coping with complex and changing enterprise management needs, the lack of integration of multiple enterprise application systems, and the risks of sensitive data management, which lead to the inaccuracy and security of enterprise human resources management. The platform intelligently realizes the comprehensive integration and efficient use of human resources information, achieving the technical effect of improving the accuracy and security of enterprise management.

The invention discloses a multi-robot synchronous control method and system, and relates to the technical field of robot control, and the method comprises the steps: uploading a directional task to a task management center, carrying out the task interpretation and role marshalling planning through a task engine, determining an execution unit cluster, and building a task communication system based on the execution unit cluster through a 5G private network. Gathering at a task side end and deploying a dynamic management component; and based on the task communication system and the dynamic management component, the execution unit cluster is taken over, and driving control and tracking supervision are carried out by robot coding, so that the technical problems of relatively limited efficiency, flexibility and expandability of robot cluster task control and scheduling in a complex environment in the prior art are solved. And efficient, flexible and extensible task management and scheduling can be realized in a complex environment.

A computing device displays a graphical user interface (GUI) comprising a navigator interface component. The navigator interface component comprises an interactive graphical representation of an asset. The device, responsive to detecting a predefined event, generates an alert. The device updates the navigator interface component to indicate the alert in association with the asset in the interactive graphical representation. The device receives a selection of the asset via the interactive graphical representation. The device displays, in the GUI, a second interactive graphical representation specific to the asset. The second interactive graphical representation of the asset comprises a task control element for controlling tasks specific to management of the asset. The device receives, using the task control element: a task for resolving the alert; and an association with the task and the asset. The device updates the navigator interface component to indicate the association with the task and the asset.

The present application provides a process task control method and a semiconductor device. The method comprises: on the basis of a plurality of preset times in a process recipe, calculating a bottleneck time of a semiconductor device and a maximum task operation cycle of a single process task; on the basis of the bottleneck time and the maximum task operation cycle, calculating a minimum task quantity; on the basis of the minimum task quantity and the maximum task operation cycle, calculating a target time interval, and controlling the interval between the start times of two adjacent process tasks in the minimum task quantity to be the target time interval, so that the yield of the semiconductor device reaches a target productivity. In the control method, the target productivity is calculated on the basis of the bottleneck time, and the minimum task quantity and the target time interval are calculated on the basis of the maximum task operation cycle, so as to determine the optimal start occasion of process tasks, so that the production capacity of the semiconductor device reaches the target productivity.

The invention belongs to the technical field of robot control, and discloses a foot-arm multi-task control method and system based on time-varying terminal cost, and the method comprises the steps: generating a whole-body reference trajectory of a robot offline, and pre-calculating a time-varying terminal cost matrix sequence based on the reference trajectory; based on the time-varying terminal cost matrix sequence, constructing and solving a nonlinear model predictive control optimization problem to obtain an optimization sequence of a system state and control input; and the optimization sequence serves as a reference instruction and is input into a layered whole-body controller for multi-task priority optimization, and a joint control instruction is generated and output to a robot execution mechanism. According to the method, the problem of short vision of a traditional NMPC in a long-time task is effectively relieved, and the operation precision of the robot is remarkably improved.

The invention discloses a composite AGV feeding and discharging control method and device, electronic equipment and a readable storage medium, and relates to the technical field of composite AGVs, and the method comprises the steps: responding to a current feeding and discharging task, controlling the composite AGV to move to a task area, recognizing a calibration point, and obtaining a current calibration point location; comparing the current calibration point location with an initial calibration point location to obtain point location deviation information; combining the point position deviation information to a task target point position based on a coordinate transformation matrix to obtain a current target point position; and executing the loading and unloading task based on the current target point location. The method and the device have the effect of improving the tail end execution positioning accuracy of the composite AGV.

The satellite-borne autonomous task planning method based on the thermodynamic diagram comprises the following steps: acquiring a ground remote control instruction, including first start time TS0, planning duration TP and thermodynamic subgraph data, including a thermodynamic subgraph file and a thermodynamic value growth function set; the task management module reads reference time Tb and TS0 and starts on-satellite autonomous planning; the thermodynamic subgraph management module analyzes the thermodynamic subgraph file, and the thermodynamic value is updated to the TS0 moment; the autonomous task planning unit screens grids larger than a thermal threshold value and performs task planning, and planning data comprises observation tasks and a power-up interval delta T; the task control management module receives the data and then powers off the autonomous task planning unit to complete task execution; obtaining the task execution condition state of the last period, and calculating the start operation time TS1 of starting the autonomous planning unit next time; and the autonomous task planning unit updates the thermodynamic value of the observed thermodynamic grid in the previous period. According to the method, the dependence of satellite observation task planning on a measurement and control link can be remarkably reduced in a certain period.

The invention provides a robot operation task control system and a robot, the robot operation task control system comprises a processing unit, a display unit and a receiving unit, the display unit displays a robot task setting interface, and the task setting interface comprises an AI creation service function control; the receiving unit receives a trigger instruction of a user for the AI creation service function control, pops up an intelligent chat program Chatbox window on the upper layer of the current task setting interface, receives text information input by the user and displays the text information in a text dialog box; and the processing unit translates the text information into codes and tests the codes, and generates a robot operation task control flow diagram for controlling the robot to execute corresponding tasks. Therefore, the method can be suitable for personalized robot operation control scenes, code compiling does not need to be carried out by professional technicians, codes can be automatically generated by inputting natural language texts from a user side, an interface is friendly and easy to operate, the code development period is greatly shortened, and compiling efficiency is high.

The invention relates to the technical field of computers, in particular to an interaction method, electronic equipment, a readable medium and a program product. According to the method, thumbnail windows respectively corresponding to one or more task windows displayed on a screen are intensively displayed in an area, and the area can be named as a task control area hereinafter. On the basis, the foldable equipment can recognize the window operated by the user and the target area or the target position to which the window is dragged according to the operation, which is applied by the user in the task control area and indicates to move the display position of the window, of the thumbnail window. Therefore, according to the interaction scheme provided by the invention, the screen is prevented from being damaged by the sliding operation on the screen of the user, the efficiency of adjusting the position of each window displayed on the screen by the user can be improved, and the use experience of the user is further improved.

This application relates to the field of automatic feeding technology, and provides a distributed control method and system for feeding motor rotor laminations. The method includes: setting up programmable logic controllers (PLCs) at multiple feeding nodes, each controller connected to a synchronous Buck topology circuit; reading and parsing the feeding task script, identifying the collaborative feeding nodes and their task control precision from multiple feeding nodes; sending a precision synchronization command to a coordination terminal based on the task control precision to obtain a corresponding fluctuation limiting signal; and the coordination terminal performing distributed collaborative control on the output of the synchronous Buck circuit connected to the collaborative feeding nodes based on the fluctuation limiting signal to complete the execution of the feeding task script. This application solves the technical problems of inconsistent actions and large precision fluctuations caused by independent control of each feeding node in the traditional motor rotor lamination feeding process, achieving the technical effect of highly consistent actions of each feeding node and controllable feeding precision through distributed synchronous control and high-precision DC bus clamping.