A resource coordination control method and device, electronic equipment and storage medium

Abstract

The application discloses a resource coordination control method and device, electronic equipment and a storage medium. The method comprises the following steps: in the case that the power consumption of a central processor is greater than a safety power consumption threshold, a first resource usage rate is calculated by an internal integrated algorithm; if the first resource usage rate is greater than or equal to a usage rate threshold, a second resource usage rate is obtained from an operating system through an in-band channel; the first resource usage rate and the second resource usage rate are verified to determine the resource occupation state of the central processor; in the case that the resource occupation state is a first occupation state, an abnormal proportion component of the central processor is identified and processed, and the first resource usage rate calculated by the internal integrated algorithm and the second group of resource usage rate data obtained from the operating system through the in-band channel are cross-verified to eliminate the misjudgment risk of single-source data, so that the humanoid robot can maintain an efficient and stable operating state in different use environments.

Description

Technical Field

[0001] This application relates to the field of humanoid robot control technology, and in particular to a resource coordination control method, device, electronic device and storage medium. Background Technology

[0002] With the explosive development of large-scale model technology and the profound evolution of human-computer interaction needs, humanoid robots have won widespread favor from customers and consumers in the market due to their superior anthropomorphic movement capabilities, intelligent decision-making abilities, and extremely high cost-effectiveness. To support complex visual perception, natural language processing, and real-time dynamic control, humanoid robots must rely on ultra-high-performance central processing units (CPUs) and graphics processing units (GPUs). Driven by both computing power demands and large-scale data models, the CPU's computing speed, response efficiency, and operational stability have become key factors determining whether humanoid robots can complete complex tasks and remain competitive in the market.

[0003] In existing technologies, as the complexity of robot tasks increases, the resource scheduling pressure within the CPU increases dramatically. Competition for CPU resources among various peripherals and internal modules intensifies, often leading to abnormal spikes in CPU load due to malfunctions, design flaws, or malicious resource hoarding by certain components or parts. Traditional monitoring methods often rely on a single data source, making them susceptible to operating system status fluctuations and failures. This results in the system's inability to promptly identify and handle abnormal loads, ultimately causing CPU computing power bottlenecks, system lag, or even crashes, severely hindering the long-term stable operation of humanoid robots. Summary of the Invention

[0004] To address existing technical problems, this invention provides a resource coordination and control method, device, electronic device, and storage medium. Under high power consumption, it cross-validates a first resource utilization rate calculated by an internally integrated algorithm with a second set of resource utilization rate data actively retrieved from the operating system via an in-band channel. This eliminates the risk of misjudgment based on single-source data. Based on the verified actual resource occupancy status, it identifies and processes components with abnormal proportions, thereby achieving refined and dynamic scheduling of computing resources. This ensures that humanoid robots maintain efficient and stable operation in different usage environments, contributing to a better user experience for humanoid robot services.

[0005] In a first aspect, embodiments of this application provide a resource coordination and control method, applied to the internal microcontroller unit of the central processing unit of a humanoid robot, comprising: When the power consumption of the central processing unit exceeds the safe power consumption threshold, the first resource utilization rate is calculated through an internal integrated algorithm; If the utilization rate of the first resource is greater than or equal to the utilization rate threshold, the utilization rate of the second resource is obtained from the operating system through the in-band channel. The resource occupancy status of the central processing unit is determined by verifying the first and second resource utilization rates. When the resource occupancy status is in the first occupancy state, identify and handle abnormal occupancy components of the central processing unit.

[0006] In one optional embodiment, the resource occupancy status of the central processing unit is determined by verification based on a first resource utilization rate and a second resource utilization rate, including: If the difference between the first resource utilization rate and the second resource utilization rate is less than or equal to the verification threshold, the first occupancy state is determined to be a resource occupancy state; or; If the difference between the first resource utilization rate and the second resource utilization rate is greater than the verification threshold, the verification is repeated a preset number of times, and the first occupancy state is determined to be the resource occupancy state.

[0007] In one alternative embodiment, identifying and handling abnormal percentage components of the central processing unit includes: Determine the total resource load of the central processing unit; If the total resource load is greater than or equal to the load threshold, the actual resource ratio of each component of the humanoid robot is collected in real time. Obtain the model information of each component; Based on the model information, retrieve the standard resource proportions of each component from the database; Identify and process components with abnormal resource ratios based on the difference between the actual resource ratio and the standard resource ratio.

[0008] In one alternative embodiment, determining the total resource load of the central processing unit includes: Obtain the number of external graphic processors and the proportion of static resources for the humanoid robot; The dynamic resource allocation is calculated based on the number of externally inserted graphical processors and a preset algorithm. The total resource load is obtained by summing the dynamic resource ratio and the static resource ratio.

[0009] In one optional embodiment, the component for identifying and processing abnormal resource ratios based on the difference between the actual resource ratio and the standard resource ratio includes: Perform the following for each part of the humanoid robot: Define the currently executing component as the current component; If the actual resource percentage of the current component is greater than or equal to the standard resource percentage, the current component is determined to be an abnormal resource percentage component; The processing order of multiple abnormal resource ratio components is determined based on the difference between the actual resource ratio and the standard resource ratio. Multiple components with different percentages of abnormalities are processed based on the processing order.

[0010] In an optional embodiment, after calculating the first resource utilization rate using an internally integrated algorithm when the power consumption of the central processing unit exceeds a safe power consumption threshold, the method further includes: If the first resource utilization rate is less than the utilization rate threshold, the second occupancy state is determined to be the resource occupancy state.

[0011] In an optional embodiment, the method further includes: Among the various components of the humanoid robot, a first-proportion component and a second-proportion component are selected; the resource proportion of the first-proportion component is greater than that of the second-proportion component. Implement resource restriction policies for the first-proportion component; Implement a backup resource strategy for the second-proportion component.

[0012] Secondly, embodiments of this application provide a resource coordination and control device applied to the internal microcontroller unit of the central processing unit of a humanoid robot, the device comprising: The calculation module is used to calculate the first resource utilization rate through an internal integrated algorithm when the power consumption of the central processing unit exceeds the safe power consumption threshold. The acquisition module is used to acquire the second resource utilization rate from the operating system through an in-band channel if the first resource utilization rate is greater than or equal to the utilization rate threshold. The determination module is used to verify the resource occupancy status of the central processing unit based on the first resource utilization rate and the second resource utilization rate. The processing module is used to identify and handle abnormal CPU usage when the resource usage status is in the first occupancy state.

[0013] Thirdly, embodiments of this application provide an electronic device, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the resource coordination and control method of the first aspect.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing at least one instruction or at least one program, wherein the at least one instruction or at least one program is loaded and executed by a processor to implement the resource coordination and control method of the first aspect.

[0015] Fifthly, embodiments of this application provide a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the resource coordination and control method of the first aspect.

[0016] The resource coordination and control method, apparatus, electronic device, and storage medium provided in this application have the following technical effects: When the power consumption of the central processing unit (CPU) exceeds the safe power consumption threshold, a first resource utilization rate is calculated using an internally integrated algorithm. If the first resource utilization rate is greater than or equal to the utilization rate threshold, a second resource utilization rate is obtained from the operating system via an in-band channel. Verification is performed based on the first and second resource utilization rates to determine the CPU's resource occupancy status. If the resource occupancy status is the first occupancy status, abnormal CPU components are identified and processed. In this embodiment, under high power consumption, the first resource utilization rate calculated by the internally integrated algorithm and the second set of resource utilization rate data actively retrieved from the operating system via an in-band channel are cross-validated to eliminate the risk of misjudgment from single-source data. Based on the verified true resource occupancy status, abnormal components are identified and processed, thereby achieving refined and dynamic scheduling of computing resources. This ensures that the humanoid robot maintains a highly efficient and stable operating state in different usage environments, helping the humanoid robot service achieve a better user experience. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a resource coordination and control method provided in an embodiment of this application. Figure 1 ; Figure 3 This is a flowchart illustrating a resource coordination and control method provided in an embodiment of this application. Figure 2 ; Figure 4 This is a flowchart illustrating a method for identifying and processing abnormally proportioned components provided in an embodiment of this application; Figure 5 This is a flowchart illustrating a resource coordination and control method provided in an embodiment of this application. Figure 3 ; Figure 6 This is a schematic diagram of the structure of a resource coordination and control device provided in an embodiment of this application; Figure 7 This is a hardware structure block diagram of a server for a resource coordination and control method provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0021] Please see Figure 1 , Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application. The humanoid robot 100 includes a central processing unit 101, an internal microcontroller unit 102, and various components 103.

[0022] In one possible embodiment, the central processing unit 101 is the core computing unit of the humanoid robot, used to complete complex computing tasks such as motion control, data processing, model reasoning, and peripheral scheduling. The operating state of the central processing unit 101 directly determines the overall performance and response speed of the humanoid robot.

[0023] In one possible embodiment, the internal microcontroller unit 102 is integrated inside the central processing unit 101 to independently monitor the power consumption and load status of the central processing unit 101, and to perform resource coordination and exception handling, thereby achieving low-level hardware-level monitoring and protection without relying on the operating system.

[0024] In one possible embodiment, the components 103 include, but are not limited to, graphics processors, motion control modules, vision acquisition modules, communication modules, sensor modules, etc. During operation, these components will occupy the interrupt resources, scheduling resources, and data interaction resources of the central processing unit 101.

[0025] In this embodiment, when the power consumption of the central processing unit 101 is greater than the safe power consumption threshold, the internal microcontroller unit 102 calculates a first resource utilization rate through an internal integrated algorithm; if the first resource utilization rate is greater than or equal to the utilization rate threshold, a second resource utilization rate is obtained from the operating system through an in-band channel; the resource occupancy status of the central processing unit is determined by verification based on the first resource utilization rate and the second resource utilization rate; when the resource occupancy status is the first occupancy status, abnormal occupancy components of the central processing unit are identified and processed.

[0026] In this embodiment, under high power consumption, the first resource utilization rate calculated by the internal integrated algorithm and the second set of resource utilization rate data actively retrieved from the operating system through the in-band channel are cross-validated to eliminate the risk of misjudgment from single-source data. Based on the verified real resource occupancy status, components with abnormal proportions are identified and processed, thereby achieving refined and dynamic scheduling of computing resources. This ensures that the humanoid robot maintains a highly efficient and stable operating state when operating in different usage environments, helping the humanoid robot service obtain a better user experience during use.

[0027] The following describes a specific embodiment of a resource coordination and control method according to this application. Figure 2 This is a flowchart illustrating a resource coordination and control method provided in an embodiment of this application. Figure 1 This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual system or server products, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Specifically, as shown in the embodiments or drawings... Figure 2 As shown, the internal microcontroller unit of the central processing unit used in humanoid robots may include: S201: When the power consumption of the central processing unit exceeds the safe power consumption threshold, the first resource utilization rate is calculated through an internal integrated algorithm.

[0028] In this embodiment, the internal microcontroller unit collects the operating power consumption of the central processing unit in real time.

[0029] When power consumption exceeds a preset safe power consumption threshold, it indicates that the central processing unit has entered a high-load or near-overload state, requiring resource coordination and control. The internal microcontroller unit independently calculates the first resource utilization rate through its integrated hardware monitoring logic and calculation algorithms.

[0030] In this embodiment, the first resource utilization rate is generated directly at the hardware level, without relying on the operating system, driver, or external software. Even if the operating system is abnormal or lags, it can still be obtained stably, with high reliability and real-time performance, and is used to make a preliminary judgment on the load of the central processing unit.

[0031] S202: If the first resource utilization rate is greater than or equal to the utilization rate threshold, obtain the second resource utilization rate from the operating system through the in-band channel.

[0032] When the utilization rate of the first resource reaches or exceeds the preset utilization rate threshold, it indicates that the CPU load is already at a high level.

[0033] In this embodiment of the application, in order to further improve the judgment accuracy, the internal microcontroller unit initiates a query to the operating system through the in-band communication channel to obtain the second resource utilization rate statistically analyzed by the operating system kernel.

[0034] The second resource utilization rate can be obtained by the operating system based on information such as task scheduling, time slice occupation, kernel mode and user mode overhead. It has finer granularity and higher accuracy, and can be used to further verify the load of the central processing unit.

[0035] S203: Verify the resource occupancy status of the central processing unit based on the first resource utilization rate and the second resource utilization rate.

[0036] The internal microcontroller unit compares and verifies the first resource utilization rate with the second resource utilization rate, and judges the actual resource occupancy status of the central processing unit based on the degree of consistency between the two.

[0037] In this application, the resource utilization rate obtained through two methods is used for verification, which can more accurately determine the resource occupancy status of the humanoid robot's central processing unit.

[0038] S204: When the resource occupancy status is in the first occupancy state, identify and handle abnormal occupancy components of the central processing unit.

[0039] In this application, the first occupancy state indicates that the central processing unit is currently under high load, close to overload, or has an abnormal occupancy state. At this time, the internal microcontroller unit initiates the abnormal occupancy component identification process, which statistically compares and analyzes the resource occupancy of each peripheral and functional module, locates the component that is maliciously occupying resources due to faults, design defects, or abnormal operation, and executes corresponding scheduling and processing strategies to avoid problems such as the central processing unit freezing or crashing due to resource exhaustion.

[0040] Figure 3 This is a flowchart illustrating a resource coordination and control method provided in an embodiment of this application. Figure 2 The method may include: S301: Obtain the power consumption of the central processing unit.

[0041] In one possible embodiment, the internal microcontroller unit can continuously collect the real-time operating power consumption of the central processing unit through built-in hardware monitoring circuitry, providing underlying hardware basis for subsequent load judgment.

[0042] S302: Determine whether the power consumption of the central processing unit is greater than the safe power consumption threshold. If yes, execute S303; otherwise, execute S301.

[0043] In one possible embodiment, the real-time power consumption is compared with a preset safe power consumption threshold. If the threshold is not exceeded, it indicates that the central processing unit is running in a normal load range, and the internal microcontroller unit continues to collect power consumption in a loop. If the threshold is exceeded, the subsequent high load monitoring process is entered.

[0044] S303: The first resource utilization rate is calculated through an internal integrated algorithm.

[0045] When the CPU power consumption exceeds the safe power consumption threshold, the internal microcontroller unit independently calculates the initial resource utilization rate using its own hardware logic and integrated algorithms. This calculation process is completed within the chip, independent of the operating system, and possesses high real-time performance and fault tolerance, serving as a preliminary safety net for CPU load assessment.

[0046] S304: Determine whether the utilization rate of the first resource is greater than or equal to the utilization rate threshold. If yes, execute S305; otherwise, execute S308.

[0047] The first resource utilization rate is compared with a preset utilization threshold. If the threshold is not reached, the CPU load is determined to be within a controllable range, and the CPU resource occupancy status is determined to be the second occupancy status. If the preset utilization threshold is reached or exceeded, further operating system-side data is obtained for more precise verification.

[0048] S305: Obtains the second resource utilization from the operating system via an in-band channel.

[0049] If the utilization rate of the first resource is greater than or equal to the utilization rate threshold, the internal microcontroller obtains the utilization rate of the second resource from the operating system through the in-band communication channel.

[0050] In this embodiment, the second resource utilization rate is obtained by the operating system based on information such as task scheduling, thread occupancy, and interrupt handling, which can more accurately reflect the actual load distribution of the central processing unit.

[0051] S306: Verify the resource occupancy status of the central processing unit based on the first resource utilization rate and the second resource utilization rate.

[0052] In an optional embodiment, if the difference between the first resource utilization rate and the second resource utilization rate is less than or equal to the verification threshold, the two sets of data are considered to have high consistency. At this time, both sets of data indicate that the resource utilization rate of the central processing unit is high, and the first occupancy state is determined to be the resource occupancy state.

[0053] In another optional embodiment, if the difference between the first resource utilization rate and the second resource utilization rate is greater than a verification threshold, the verification is repeated a preset number of times, and the first occupancy state is determined to be the resource occupancy state. In this embodiment, a large difference between the first resource utilization rate and the second resource utilization rate indicates that there is instantaneous fluctuation or abnormal deviation in the data. The internal microcontroller unit needs to repeatedly execute the data acquisition and comparison process a preset number of times. If a high load trend is still shown after multiple verifications, since the first resource utilization rate is calculated through a more reliable internal integrated algorithm, the first occupancy state is still determined to be the current resource occupancy state, thus avoiding the failure of load judgment due to operating system anomalies.

[0054] S307: When the resource occupancy status is in the first occupancy state, identify and handle abnormal occupancy components of the central processing unit.

[0055] When the central processing unit is confirmed to be in the first occupied state, that is, the high load state, the internal microcontroller unit performs statistics, comparison and analysis on the resource usage of each component, identifies the abnormal proportion of components whose actual resource usage significantly exceeds the standard range, and handles them in a targeted manner so that the central processing unit can maintain a stable operating state.

[0056] S308: Determine the second occupancy status as a resource occupancy status.

[0057] If the first resource utilization rate does not reach the utilization rate threshold, the CPU load is determined to be in the normal range, and the CPU resource occupancy status is determined to be the second occupancy status. The internal microcontroller unit maintains routine monitoring.

[0058] Figure 4This is a flowchart illustrating a method for identifying and processing abnormally high-performing components according to an embodiment of this application. In one possible embodiment, identifying and processing abnormally high-performing components of the central processing unit includes the following steps: S401: Determines the total resource load of the central processing unit.

[0059] In one alternative embodiment, determining the total resource load of the central processing unit includes: S4011: Obtain the number of external graphic processors and the percentage of static resources for the humanoid robot.

[0060] In one possible embodiment, the internal microcontroller unit identifies the number of externally inserted graphical processors currently connected to the humanoid robot and reads the system's preset static resource ratio, which is the basic central processing unit resources required for normal operation.

[0061] S4012: Calculates dynamic resource allocation based on the number of externally oriented graphical processors and a preset algorithm.

[0062] Based on the number of externally attached graphics processors, the dynamic resource usage generated during multi-GPU parallel operation is calculated using a preset model. The dynamic resource ratio is the maximum proportion of CPU scheduling and interrupt resources occupied by multiple graphics processors during parallel operation.

[0063] S4013: The total resource load is obtained by summing the dynamic resource ratio and the static resource ratio.

[0064] The total resource load of the central processing unit is obtained by summing the dynamic resource ratio and the static resource ratio, and then adding the static basic usage to the dynamic running usage. This is used to determine whether resource coordination needs to be initiated.

[0065] S402: Determine if the total resource load is greater than or equal to the load threshold. If yes, execute S403; otherwise, execute S401.

[0066] In one possible embodiment, if the total resource load is greater than or equal to the load threshold, it indicates that the central processing unit is under resource strain and there is a risk of overload. The internal microcontroller unit collects the actual resource ratio of each component of the humanoid robot in real time to further locate the component with abnormal ratio.

[0067] In another possible implementation, if the threshold is not reached, it indicates that there is no risk of overload for the time being, and the total load is monitored continuously.

[0068] S403: Real-time acquisition of the actual resource proportion of each component of the humanoid robot.

[0069] The internal microcontroller unit collects the proportion of central processing unit resources currently actually used by each component in real time through multiple interaction channels.

[0070] S404: Obtain model information for each component.

[0071] S405: Retrieve the standard resource percentage of each component from the database based on the model information.

[0072] The internal microcontroller unit (MCU) obtains the type, model, and hardware parameters of each component through hardware identification or by reading configuration information, providing a basis for subsequent standard resource usage queries. Based on the component model information, the MCU retrieves the standard resource ratio of that component model under normal operating conditions from its built-in database. This standard resource ratio can be used to determine whether the resource ratio of that component model is abnormal.

[0073] S406: Identify and process components with abnormal resource ratios based on the difference between the actual resource ratio and the standard resource ratio.

[0074] In one optional embodiment, the component for identifying and processing abnormal resource ratios based on the difference between the actual resource ratio and the standard resource ratio includes: Perform the following for each part of the humanoid robot: S4061: Determine the currently executing component as the current component.

[0075] S4062: If the actual resource percentage of the current component is greater than or equal to the standard resource percentage, the current component is determined to be an abnormal percentage component.

[0076] If the actual resource percentage of the current component is greater than or equal to the standard resource percentage, the current component is determined to have abnormal resource percentage behavior and is identified as an abnormal percentage component.

[0077] S4063: Determine the processing order of multiple abnormal resource ratio components based on the difference between the actual resource ratio and the standard resource ratio.

[0078] Calculate the difference between the actual resource ratio and the standard resource ratio of the current component. The larger the difference, the more serious the abnormal ratio of the component, and the greater the impact on system stability. Therefore, the higher the processing priority.

[0079] S4064: Process multiple abnormal percentage components based on processing order.

[0080] After determining whether each component exhibits abnormal resource usage and identifying the processing priority of components with abnormal resource usage, resource limiting, scheduling adjustments, or abnormal recovery operations are sequentially performed on multiple components with abnormal resource usage based on the processing order. This quickly eliminates malicious resource occupation and prevents the central processing unit from freezing or crashing.

[0081] Figure 5 This is a flowchart illustrating a resource coordination and control method provided in an embodiment of this application. Figure 3 The method may include: S501: Select the first proportion component and the second proportion component from the various parts of the humanoid robot.

[0082] In this embodiment, the resource share of the first-proportioning component is greater than that of the second-proportioning component. Specifically, the first-proportioning component is one with high resource usage exceeding the standard proportion range, while the second-proportioning component is one with normal or lower resource usage than the standard proportion and with remaining resources. The internal microcontroller unit classifies and filters components based on a comparison between the actual resource proportion and the standard resource proportion.

[0083] S502: Implement resource restriction policy for the first component.

[0084] For the primary component with excessive resource consumption, the internal microcontroller unit implements strategies such as resource limiting, priority reduction, frequency limiting, or task scheduling adjustment to control its consumption of central processing unit resources and prevent it from continuously over-consuming resources, which could lead to system load imbalance.

[0085] S503: Implement a spare resource strategy for the second-proportion component.

[0086] For the second component with reasonable resource usage and sufficient reserves, the internal microcontroller unit can dynamically allocate some spare central processing unit resources according to the overall system operation requirements to ensure the stable operation of key functional modules, realize the reasonable allocation and efficient utilization of resources among different components, and ensure that the overall performance of the humanoid robot is not excessively affected while limiting abnormal usage.

[0087] This application achieves dual resource utilization monitoring at both the hardware and system levels through an internal microcontroller unit. In high-power scenarios, a cross-validation mechanism is used to determine the true load status of the central processing unit, avoiding misjudgments caused by the failure of a single data source. At the same time, through total load calculation, actual component percentage collection, standard percentage comparison, and difference sorting, abnormal over-utilized components are accurately identified and prioritized for handling, thereby achieving fine-grained coordinated control of central processing unit resources.

[0088] This effectively avoids the problem of malicious resource occupation caused by component failures, design defects, or abnormal operation of humanoid robots, prevents the central processing unit from freezing or crashing, significantly improves the operational stability and reliability of humanoid robots in complex AI tasks and multi-peripheral concurrent scenarios, and ensures that humanoid robots can continuously, stably, and efficiently perform humanoid behaviors and complex tasks.

[0089] This application also provides a resource coordination and control device. Figure 6 This is a schematic diagram of the structure of a resource coordination and control device provided in an embodiment of this application, as shown below. Figure 6As shown, the internal microcontroller unit of the central processing unit used in a humanoid robot, device 600 includes: The calculation module 610 is used to calculate the first resource utilization rate through an internal integrated algorithm when the power consumption of the central processing unit exceeds the safe power consumption threshold. The acquisition module 620 is used to acquire the second resource utilization rate from the operating system through an in-band channel if the first resource utilization rate is greater than or equal to the utilization rate threshold. The determination module 630 is used to verify the resource occupancy status of the central processing unit based on the first resource utilization rate and the second resource utilization rate. The processing module 640 is used to identify and process abnormal CPU usage when the resource usage state is in the first usage state.

[0090] In one alternative implementation, it further includes: The first determining module is configured to determine the first occupancy state as a resource occupancy state if the difference between the first resource utilization rate and the second resource utilization rate is less than or equal to a verification threshold; or; The second determining module is used to perform the verification a preset number of times and determine the first occupancy state as the resource occupancy state if the difference between the first resource utilization rate and the second resource utilization rate is greater than the verification threshold.

[0091] In one alternative implementation, it further includes: The third determining module is used to determine the total resource load of the central processing unit; The data acquisition module is used to collect the actual resource ratio of each component of the humanoid robot in real time if the total resource load is greater than or equal to the load threshold. The first acquisition module is used to acquire the model information of each component; The retrieval module is used to retrieve the standard resource proportions of each component from the database based on the model information; The first processing module is used to identify and process abnormal resource ratio components based on the difference between the actual resource ratio and the standard resource ratio.

[0092] In one alternative implementation, it further includes: The second acquisition module is used to acquire the number of external graphic processors and the proportion of static resources of the humanoid robot; The first computing module is used to calculate the dynamic resource ratio based on the number of externally inserted graphical processors and a preset algorithm. The second calculation module is used to obtain the total resource load based on the sum of the dynamic resource ratio and the static resource ratio.

[0093] In one alternative implementation, it further includes: The fourth determination module is used to determine the currently executing component as the current component; The fifth determination module is used to determine that if the actual resource ratio of the current component is greater than or equal to the standard resource ratio, the current component is an abnormal ratio component. The sixth determination module is used to determine the processing order of multiple abnormal percentage components based on the difference between the actual resource percentage and the standard resource percentage. The second processing module is used to process multiple abnormal percentage components based on the processing order.

[0094] In one alternative implementation, it further includes: The seventh determination module is used to determine the second occupancy state as a resource occupancy state if the first resource utilization rate is less than the utilization rate threshold.

[0095] In one alternative implementation, it further includes: The filtering module is used to filter out the first proportion component and the second proportion component from the various parts of the humanoid robot; the resource proportion of the first proportion component is greater than that of the second proportion component. The first execution module is used to implement resource restriction policies on the first proportion component; The second execution module is used to execute the backup resource strategy on the second proportion component.

[0096] The apparatus and method embodiments in this application are based on the same application concept.

[0097] The methods and embodiments provided in this application can be executed on a computer terminal, server, or similar computing device. Taking running on a server as an example, Figure 7 This is a hardware structure block diagram of a server for a resource coordination and control method provided in an embodiment of this application. For example... Figure 7As shown, the server 700 can vary significantly due to different configurations or performance. It may include one or more Central Processing Units (CPUs) 710 (CPUs 710 may include, but are not limited to, microprocessors (MCUs) or programmable logic devices (FPGAs), a memory 730 for storing data, and one or more storage media 720 (e.g., one or more mass storage devices) for storing application programs 723 or data 722. The memory 730 and storage media 720 may be temporary or persistent storage. The program stored in the storage media 720 may include one or more modules, each module may include a series of instruction operations on the server. Furthermore, the CPU 710 may be configured to communicate with the storage media 720 and execute the series of instruction operations stored in the storage media 720 on the server 700. Server 700 may also include one or more power supplies 760, one or more wired or wireless network interfaces 750, one or more input / output interfaces 740, and / or one or more operating systems 721, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0098] The input / output interface 740 can be used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of server 700. In one example, the input / output interface 740 includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the input / output interface 740 may be a radio frequency (RF) module used for wireless communication with the Internet.

[0099] Those skilled in the art will understand that Figure 7 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, server 700 may also include... Figure 7 The more or fewer components shown, or having the same Figure 7 The different configurations shown.

[0100] This application provides an electronic device, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The processor loads and executes the at least one instruction, at least one program, code set, or instruction set to implement the above-described data processing method.

[0101] Embodiments of this application also provide a computer-readable storage medium, which can be disposed in a server to store at least one instruction, at least one program, code set, or instruction set related to implementing a resource coordination and control method in the method embodiment. The at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the above-described resource coordination and control method.

[0102] Optionally, in this embodiment, the storage medium may be located at at least one of the multiple network servers in a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0103] As can be seen from the embodiments of the resource coordination and control method, apparatus, electronic device, or storage medium provided in this application, when the power consumption of the central processing unit (CPU) exceeds the safe power consumption threshold, a first resource utilization rate is calculated through an internally integrated algorithm. If the first resource utilization rate is greater than or equal to the utilization rate threshold, a second resource utilization rate is obtained from the operating system through an in-band channel. Verification is performed based on the first and second resource utilization rates to determine the resource occupancy status of the CPU. When the resource occupancy status is the first occupancy status, abnormally occupied components of the CPU are identified and processed. In the embodiments of this application, under high power consumption, the first resource utilization rate calculated by the internally integrated algorithm and the second set of resource utilization rate data actively retrieved from the operating system through an in-band channel are cross-validated to eliminate the risk of misjudgment from single-source data. Based on the verified true resource occupancy status, abnormally occupied components are identified and processed, thereby achieving refined and dynamic scheduling of computing resources. This ensures that the humanoid robot maintains a highly efficient and stable operating state in different usage environments, helping the humanoid robot service obtain a better user experience during use.

[0104] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0105] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0106] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0107] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A resource coordination control method, characterized by, The internal microcontroller unit of the central processing unit used in humanoid robots includes: When the power consumption of the central processing unit exceeds the safe power consumption threshold, the first resource utilization rate is calculated through an internal integrated algorithm; If the first resource utilization rate is greater than or equal to the utilization rate threshold, the second resource utilization rate is obtained from the operating system through the in-band channel. Based on the verification of the first resource utilization rate and the second resource utilization rate, the resource occupancy status of the central processing unit is determined. When the resource occupancy status is in the first occupancy status, identify and handle the abnormal occupancy components of the central processing unit.

2. The method of claim 1, wherein, The step of verifying the resource occupancy status of the central processing unit based on the first resource utilization rate and the second resource utilization rate includes: If the difference between the first resource utilization rate and the second resource utilization rate is less than or equal to the verification threshold, the first occupancy state is determined to be the resource occupancy state; or; If the difference between the first resource utilization rate and the second resource utilization rate is greater than the verification threshold, the verification is repeated a preset number of times, and the first occupancy state is determined to be the resource occupancy state.

3. The method of claim 1, wherein, The component for identifying and processing abnormal percentages of the central processing unit includes: Determine the total resource load of the central processing unit; If the total resource load is greater than or equal to the load threshold, the actual resource percentage of each component of the humanoid robot is collected in real time. Obtain the model information of each component; Based on the model information, retrieve the standard resource percentage of each component from the database; The abnormal resource ratio component is identified and processed based on the difference between the actual resource ratio and the standard resource ratio.

4. The resource coordination and control method according to claim 3, characterized in that, Determining the total resource load of the central processing unit includes: Obtain the number of external illustration graphics processors and the percentage of static resources of the humanoid robot; The dynamic resource ratio is calculated based on the number of externally inserted graphic processors and a preset algorithm. The total resource load is obtained by summing the dynamic resource ratio and the static resource ratio.

5. The resource coordination and control method according to claim 3, characterized in that, The component for identifying and processing abnormal resource ratios based on the difference between the actual resource ratio and the standard resource ratio includes: Perform the following for each component of the humanoid robot: Define the currently executing component as the current component; If the actual resource percentage of the current component is greater than or equal to the standard resource percentage, the current component is determined to be the abnormal resource percentage component; The processing order of multiple abnormal resource ratio components is determined based on the difference between the actual resource ratio and the standard resource ratio. Multiple abnormal percentage components are processed based on the processing order.

6. The resource coordination and control method according to claim 1, characterized in that, After calculating the first resource utilization rate using an internal integrated algorithm when the power consumption of the central processing unit exceeds the safe power consumption threshold, the method further includes: If the first resource utilization rate is less than the utilization rate threshold, the second occupancy state is determined as the resource occupancy state.

7. The resource coordination and control method according to claim 6, characterized in that, The method further includes: Among the various components of the humanoid robot, a first proportion component and a second proportion component are selected; the resource proportion of the first proportion component is greater than that of the second proportion component. Implement resource restriction policies for the first component. Implement a backup resource strategy for the second-proportion component.

8. A resource coordination and control device, characterized in that, An internal microcontroller unit for a central processing unit used in a humanoid robot, the device comprising: The calculation module is used to calculate the first resource utilization rate through an internal integrated algorithm when the power consumption of the central processing unit is greater than the safe power consumption threshold. The acquisition module is used to acquire the second resource utilization rate from the operating system through an in-band channel if the first resource utilization rate is greater than or equal to the utilization rate threshold. The determination module is used to verify the resource occupancy status of the central processing unit based on the first resource utilization rate and the second resource utilization rate. The processing module is used to identify and process abnormal resource usage components of the central processing unit when the resource usage state is in the first usage state.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the resource coordination and control method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction or at least one program, which is loaded and executed by a processor to implement the resource coordination and control method as described in any one of claims 1-7.

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