23results about How to "Improve task execution efficiency" patented technology

The invention discloses an LLM Agent task execution method and device and electronic equipment. The method comprises the following steps: S1, identifying a user role; s2, task planning and interaction point configuration; s3, performing active interaction execution; and S4, dynamically adjusting the execution path. According to the method, interaction can be actively initiated at key nodes, an execution strategy is dynamically optimized, personalized interaction experience is provided, task execution efficiency is effectively improved, the risk that an execution result deviates from user expectation is reduced, and system availability and user satisfaction are improved.

The application discloses an AXI bus-based SOC chip, an electronic device and a data transmission method, and relates to the technical field of integrated circuits.The SOC chip comprises a master device, a filtering processing unit, a bus interconnection unit and a slave device.The filtering processing unit is configured to forward a read data instruction sent by the master device to the bus interconnection unit, and store key information in the read data instruction in a storage unit of a storage module based on the receiving sequence of the read data instruction.The bus interconnection unit is configured to send the read data instruction to the slave device, and send read data information returned by the slave device to the filtering processing unit.The filtering processing unit is further configured to read the key information stored in the storage unit based on the receiving sequence of the read data information, determine the validity of the read data information based on the key information and the read data information, send the read data information to the master device when it is determined that the read data information is valid, and send a notification message to the master device when it is determined that the read data information is invalid.

The invention provides a project DFMEA cooperative processing method and system and electronic equipment, and the method comprises the steps: creating a target project DFMEA based on a DFMEA knowledge base and / or an existing project DFMEA; assigning tasks related to the DFMEA of the target project; displaying a task corresponding to the user through a DFMEA task board; displaying the function structure tree on an analysis interface; displaying knowledge data or project data corresponding to the object so that a user can select or apply the object; signing and auditing the DFMEA of the target project, and auditing whether the selection or application of the user to the object in the functional structure tree is accurate or not; and in response to the approval state, recording the approval process of the DFMEA of the target project in the target file. According to the technical scheme, the accuracy of the DFMEA analysis result can be improved, and the analysis efficiency is improved.

This invention provides a method and system for collaborative environmental monitoring and pollution source tracing using UAV swarms in complex terrain, relating to the fields of UAV environmental monitoring and pollution source tracing. The method includes: a ground control center planning layered and altitude-based tasks for the target area and sending them to each group containing master and sub-UAVs; the master UAV decomposing and encoding the sub-tasks and transmitting the results back; the ground-based optimization of flight paths being distributed; the sub-UAVs collecting pollution source data, which is then preprocessed by the master UAV and uploaded; ground-based analysis results being fed back; and the master UAV calculating the contribution value C using a source tracing model. en Once the source tracing is complete, the results are uploaded to the server, and the drone returns to base. The system includes a ground control center and at least one drone swarm; each swarm consists of a master drone and sub-drones. This invention can plan flight paths based on the geographical environment of the monitored target area, avoiding detection blind spots and conflicts, and coordinate actions based on the flight path, thus improving the convenience and accuracy of environmental monitoring and pollution source tracing.

The embodiment of the invention discloses a big data processing method and system based on cloud computing, and the method is realized based on a cloud computing platform, and the method comprises the steps: decomposing a big data processing task into a plurality of micro-tasks, and distributing the micro-tasks to distributed computing nodes; each computing node selects an adjacent node based on a hyper-local algorithm, and constructs a local task processing model only by using local data and metadata of the adjacent node dynamically selected based on a fast game mechanism, the metadata including micro-task data semantic features and task dependency relationships of the adjacent node, and the task dependency relationships of the adjacent node are calculated; semantic features are extracted through a natural language processing technology, and a task dependency relationship is determined based on input and output association of the microtasks; according to the local task processing model, independently executing the micro-task on each computing node, and dynamically adjusting the distribution of the micro-task through a point-to-point local negotiation mechanism; and aggregating the micro-task processing results of the computing nodes to generate a global data processing result. According to the method, the operation and communication overhead is reduced.

The utility model relates to the technical field of equipment coordination, and discloses a multi-equipment coordination control system, which comprises user equipment and a server, and is characterized in that the user equipment comprises main control equipment and at least one coordination equipment, and the main control equipment is connected with the coordination equipment in a wired or wireless manner; the server establishes communication connection with the main control equipment; the main control equipment comprises a first communication interface, a first processor and a first storage module; the cooperative device comprises a second communication interface and an execution module. According to the utility model, through optimizing the communication interface design of the master control device and the cloud instance, the efficient and stable client device cluster physical networking topology is constructed, the hardware module layout is innovated, and the hardware-level security protection structure is strengthened; the problems of unstable equipment connection, poor module collaboration, weak safety protection and the like in the system structure level in the prior art are solved, dynamic permission adjustment, intelligent task allocation and automatic switching after main control equipment fails are realized, and the performance and reliability of multi-equipment cooperative control are improved.

The embodiment of the invention provides a task scheduling method and device, electronic equipment and a storage medium, belongs to the technical field of artificial intelligence, and is suitable for the field of financial science and technology and the field of intelligent medical treatment. The method comprises the steps of obtaining a target task type of a robot, test calculation amount data of a test task and execution performance data of an original actuator; and constructing an initial mapping relation based on the target task type, the test calculation amount data and the execution performance data. And selecting a reference identifier from the original identifiers based on the initial mapping relationship and the current task type. And obtaining a reference actuator according to the reference identifier, obtaining current load data of the reference actuator, and matching current calculation amount data of the current task type. And updating the initial mapping relation according to the execution performance data, the current load data and the current calculation amount data to obtain a target mapping relation. And performing task scheduling based on the target mapping relationship. The task execution efficiency of the robot can be improved.

The application provides a task resource pool construction method for a large-scale satellite cluster, belongs to the technical field of aerospace, and is characterized in that, on the basis of abstractly and quantitatively representing required resources of a task and residual resources of each node, a node receiving a task request is taken as a center, communication is performed layer by layer outward, resource information of a participating node is collected, and when the total number of resources of the participating nodes meets the task demand, the search outward is stopped to complete the search of the task resource pool member nodes; the method can make the large-scale satellite cluster have the rapid response capability to deal with sudden tasks, strengthens the autonomous decision-making capability in orbit, and has a wide application prospect.

The invention relates to the technical field of data processing, can be applied to business system platforms of financial science and technology, medical treatment and health and the like, and discloses a task file exception re-reading method, device and equipment and a medium. Generating a to-be-executed task sub-file corresponding to the to-be-executed task main file according to the task configuration parameters; reading a reading progress value and a read data volume corresponding to the to-be-executed task main file, and monitoring a task data reading state of the to-be-executed task main file according to the reading progress value and the read data volume; when the task data reading state is reading failure, reading the to-be-executed task sub-file, and executing the to-be-executed task sub-file based on a reading result of the to-be-executed task sub-file to obtain a sub-file task execution state; identifying a reading abnormal factor of the main file of the task to be executed, and extracting a file configuration parameter of the reading abnormal factor; and synchronously updating the sub-file task execution state and the file configuration parameters to the to-be-executed task main file. According to the method, the task file exception rereading efficiency can be improved.

This application discloses a control method, apparatus, self-moving device, storage medium, and program product for a self-moving device. The self-moving device is equipped with a robotic arm that acquires first position information of a target shoe to be grasped and first grasping position of the target shoe. Based on the first position information and first grasping position, the robotic arm of the self-moving device is controlled to grasp the target shoe. This application embodiment achieves the grasping of footwear objects by acquiring the first position information and first grasping position of the target shoe and controlling the robotic arm to grasp the target shoe based on this information. By using a robotic arm to grasp the target shoe, this application embodiment ensures that the self-moving device autonomously completes the grasping of footwear objects, thereby improving the task execution efficiency and the versatility of the self-moving device.

This invention provides a task execution method, apparatus, electronic device, and storage medium, relating to the field of embodied intelligence technology. The method includes: determining redundant feature components from the first task reference information based on the feature sources of feature components and the importance values ​​of each feature source, wherein the importance value of each feature source represents the magnitude of the influence of the feature component of that feature source on the successful output of the robot's expected action by the first VLA model; performing redundancy removal processing on the redundant feature components in the first task reference information to obtain processed first task reference information; inputting the processed first task reference information into the first VLA model to obtain the predicted action of the robot output by the first VLA model; and controlling the robot to execute the task based on the predicted action. Applying the solution provided by this invention can improve the robot's motion control frequency, thereby improving task execution performance.

The application discloses a kind of distributed network scanning method and system based on multiple cloud nodes, by collecting the network state and load information of each scanning node, available domain is divided and dynamic scheduling loop is constructed;Reorganize scanning path and identify network blind area through bidirectional connectivity detection, build effective scanning coverage domain;Delay distribution is analyzed to determine low delay window, and the optimal scanning route is planned and task allocation strategy is formulated;Task is disassembled into core detection sequence and edge detection sequence, and hot standby node cluster is constructed for edge task;Abnormal monitoring is carried out to core task, and when node is disconnected, hot standby node is drafted to form takeover link node, and collaborative scanning grid is formed;According to collaborative scanning grid, node feedback topology is built, time delay calibration is carried out to generate distributed scanning instruction, and the execution efficiency and fault tolerance of scanning task in multi-cloud environment are improved.

The utility model discloses unmanned aerial vehicle task load replacement trolley, including trolley garage and electromagnet trolley, and trolley garage is equipped with an opening, and the inside bottom surface of trolley garage is equipped with guide recess and rack, and electromagnet trolley bottom is equipped with guide block, and guide block is inserted in guide recess, and electromagnet trolley is equipped with drive motor and gear inside, and drive motor drives gear rotation, and gear is engaged with rack and drives electromagnet trolley overall translation. Advantages lie in, through control electromagnet trolley on-off electricity, realize the adsorption and release of battery load, can quickly complete the loading and unloading and removal of battery load, and electromagnet trolley cooperates load tray and its track use, and this module structure is compact, and occupies small, can realize the quick disassembly and replacement of task load, significantly shorten the residence time of unmanned aerial vehicle in the nest, improve task execution efficiency.

The application relates to the technical field of mobile robots and discloses a complex under-actuated robot full-dynamics decoupling servo control system and method, wherein the control system comprises a calibration target module, a feature sensing module, a data processing module, a position control module and a posture control module; the control method comprises the following steps: energy equations and potential energy equations are established by analyzing the force conditions of each moving component of a robot body; a robot dynamics model is established by substituting a Lagrange function into a Lagrange equation; a conversion equation representing the conversion relationship between robot control variables and self-state variables is established by analyzing the mapping relationship between the robot control variables and the self-state variables; and a control model is obtained based on the conversion equation, a control algorithm is designed, and a control signal is generated. On the basis of ensuring that the robot self-model can fully reflect the dynamics characteristics of the robot, the posture and position dynamics of the robot are decoupled, the accuracy and stability of the body control are improved, and the maneuverability and sensitivity of the robot are effectively exerted.

This invention discloses a control method for an electrical appliance, comprising: acquiring a map of objects placed in a target space; the object map being generated based on map data constructed by a mobile device during its movement within the target space, the object map containing information on objects placed in different spatial areas within the target space; determining target operating parameters for the electrical appliance based on the object map; and controlling the electrical appliance to operate according to the target operating parameters to perform a target function. This invention also discloses an electrical appliance, an electrical system, and a computer-readable storage medium. This invention aims to improve the convenience of electrical appliances in realizing their functions in conjunction with the actual state of a space, and to improve task execution efficiency.

The application discloses a device resource application method and device, an electronic device and a storage medium. The method comprises the following steps: determining a single container demand quantity for a GPU resource card indicated by a task request in a current task request set; determining a whole machine card quantity of a GPU device in a device cluster; based on the whole machine card quantity and the single container demand quantity indicated by the task request, constructing a task request group in which the sum of the indicated single container demand quantities matches the whole machine card quantity, so as to apply for corresponding GPU device resources based on the task request group. The application can guarantee that the whole machine resources are applied to the device as much as possible at the task request level, thereby reducing the GPU resource cards in the form of fragments, effectively guaranteeing the device resource utilization rate and load balancing. Especially for the case where the task request is sufficient, the task execution efficiency can be improved.

The invention relates to the field of artificial intelligence, in particular to a computing power distribution and scheduling method and device, electronic equipment and a computer program product. The method comprises the following steps: performing quantification processing on computing power resources of various types of computing power nodes and computing power demands of computing tasks to generate quantification results; determining a target computing power distribution strategy at least based on the quantification result and a preset optimization model, the target computing power distribution strategy being used for indicating to distribute the computing task to a target computing power node with the highest matching degree; and based on the target computing power distribution strategy, distributing and monitoring the computing tasks. By dynamically analyzing and calculating the heterogeneity of task requirements and computing power resources and adopting an optimized allocation strategy and a scheduling mechanism, the resources are effectively utilized, and the task execution efficiency is improved.

The invention discloses a multimode data fusion online unmanned system perception fault detection method and system, and the method comprises the steps: obtaining an environment video stream through a vehicle-mounted monocular camera, recognizing a specific marker through a target detection algorithm, and extracting the pixel height of the specific marker; calculating the distance between the marker and the unmanned system by using a monocular vision ranging model in combination with the prior physical height of the marker and the focal length of the camera; calculating self-calculation coordinates of the unmanned system by using a geometric modeling method in combination with the distance information of the plurality of markers; meanwhile, obtaining a positioning coordinate provided by a positioning module of the unmanned system; comparing the calculation coordinates with the positioning coordinates, and calculating a deviation value; and when the deviation value continuously exceeds a preset threshold value, judging that the sensing sensor has a fault. A V2X communication mechanism is also introduced, and perceptual results are allowed to be shared or a detection model is allowed to be dynamically updated through a road side unit. According to the method, low-cost and light-weight online fault detection can be realized, extra hardware redundancy is not needed, and the robustness and safety of the unmanned system in a dynamic environment are effectively improved.

A SQL task link optimization method, device, equipment, storage medium and program product are disclosed, task related data of a SQL task is acquired, a dependency link between SQL tasks is filtered based on the task related data, wherein the dependency link is used to represent an association relationship between the SQL tasks, a directed graph network of the SQL tasks is constructed based on the filtered dependency link, the directed graph network is divided into at least two connected subgraphs, a SQL task in each connected subgraph is subjected to a merging feasibility test, a task merging decision is generated based on a test result, and a link of the SQL task is restructured and optimized according to the task merging decision. By adopting the embodiment of the present application, an execution exception of a SQL task can be captured in real time, system failure caused by problem accumulation can be avoided, and the management requirement of a high concurrency and large data volume SQL task link can be adapted.

This invention discloses a deployment and retrieval device and method for unmanned surface vessels (USVs), belonging to the field of USV technology. The device includes a rope thrower, a tow rope, a rotating drum reversing mechanism, a first rotating drum, a second rotating drum, a first clamping mechanism, a second clamping mechanism, a davit docking device, an automatic rope reeling device, and a towed load. The rope thrower is mounted obliquely on the USV. The rotating drum reversing mechanism drives the first and second rotating drums to swing in opposite directions. The first and second rotating drums rotate synchronously to retrieve the tow rope. One end of the tow rope is fixedly connected to the automatic rope reeling device, and the other end passes through a sub-docking device, then sequentially through the first and second clamping mechanisms to connect with the towed load. The towed load, under the action of the throwing device, throws the rope towards the mother ship. This invention not only enables multiple rope throws, reducing the difficulty of rope throwing, but also overcomes the problem of unmanned surface vessel attitude being difficult to control and unable to dock quickly and accurately in high sea states, avoiding the need for personnel to personally board the vessel for docking, effectively improving operational safety.

The application provides an adaptive pathfinding method for unmanned aerial vehicle clusters, specifically including task initialization and environment perception, path planning based on bionic intelligence, multi-vehicle cooperation and dynamic adjustment. The method designs an information pheromone updating strategy with variation mechanism and dynamic obstacle avoidance capability, making the path search more adaptive and stable. At the communication level, a decentralized communication architecture is adopted between unmanned aerial vehicles, supplemented by a cloud synchronization mechanism, to realize real-time sharing of task information and efficient adjustment of path schemes. The pathfinding method is applicable to various practical scenarios, including post-disaster search and rescue, ecological environment monitoring, and large-area inspection, and has good scalability and robustness, effectively addressing the challenges brought by dynamic environments and task changes.

This application provides a method, system, and computer device for dynamically selecting AGV devices. The method includes: obtaining a first set of ideal travel paths corresponding to the starting point of a plurality of AGV devices currently not performing tasks; determining whether the lengths of several travel paths in the first set of ideal travel paths are less than a first preset safe path length threshold; when none of the travel path lengths in the first set of ideal travel paths are less than the first preset safe path length threshold, performing dynamic selection strategy processing on the AGV devices currently not performing tasks; and selecting AGV devices that meet the criteria from the AGV devices currently not performing tasks using the dynamic selection strategy, and determining these AGV devices as the AGV devices to perform tasks. This improves the overall efficiency of selecting AGV devices to perform tasks.

The invention provides a robot dynamic path planning method and system based on deep learning, and the method comprises the steps: building a motion response model which can reflect the dynamic characteristics of a robot, and carrying out the global sensitivity analysis of key motion parameters including the track smoothness, the obstacle avoidance safety distance and the motion speed; determining a feasible interval of each key motion parameter according to an analysis result; a path point sequence and a system control instruction are taken as decision variables, path length and motion time minimization is taken as a target, numerical optimization solution is carried out under the constraint of a motion response model, and an optimal path point sequence and optimal control instruction combination and a corresponding optimal motion track are obtained through forward simulation; and determining an optimal trajectory tracking control parameter of each motion stage according to the feasible interval of each key motion parameter, the optimal path point sequence and the optimal control instruction. By adopting the scheme of the invention, accurate track tracking control of the multi-target optimization driven robot can be realized, so that the operation efficiency under a complex working condition is improved.