Intelligent operation management method based on service robot community state

Abstract

The application discloses an intelligent operation management method based on a service robot community state. The method is executed by a cloud server, and the method comprises the following steps: acquiring a health value corresponding to each type of robot cluster in a robot community, wherein the robot community comprises at least two types of robot clusters; generating a target control instruction corresponding to each type of robot cluster according to the health value corresponding to each type of robot cluster, and sending the target control instruction to the corresponding robot cluster. Through the technical scheme of the application, the type and quantity of the robot cluster receiving the task can be adjusted, and then the overall processing capacity of the robot community is adjusted, and the overall service level and operation efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to an intelligent operation and management method based on the community status of service robots. Background Technology

[0002] Most current robots are single-type robot swarms, providing a single type of work. Robots within the same type of swarm can communicate or be managed uniformly, but robot swarms of different types cannot communicate effectively. When different types of robot swarms are in the same application scenario, each type of robot swarm serves a different target group and performs different types of work. Therefore, it is particularly necessary to form robot swarms of different types into robot communities and to carry out unified intelligent operation and management of robot swarms based on robot communities. Summary of the Invention

[0003] This invention provides an intelligent operation and management method based on the status of a service robot community. This method can adjust the type and number of robot clusters receiving tasks, thereby adjusting the overall processing capacity of the robot community and improving the overall service level and operational efficiency.

[0004] According to one aspect of the present invention, an intelligent operation management method based on the community status of service robots is provided, comprising:

[0005] Obtain the health value corresponding to each type of robot cluster in the robot community, wherein the robot community includes at least two types of robot clusters;

[0006] Based on the health value corresponding to each type of robot cluster, a target control command is generated for each type of robot cluster, and the target control command is sent to the corresponding robot cluster.

[0007] According to another aspect of the present invention, an intelligent operation management device based on the community status of service robots is provided, the intelligent operation management device based on the community status of service robots includes:

[0008] The first acquisition module is used to acquire the health value corresponding to each type of robot cluster in the robot community, wherein the robot community includes at least two types of robot clusters;

[0009] The generation module is used to generate target control instructions for each type of robot cluster based on the health value corresponding to each type of robot cluster, and send the target control instructions to the corresponding robot cluster.

[0010] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0011] At least one processor; and

[0012] A memory communicatively connected to the at least one processor; wherein,

[0013] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to execute the intelligent operation management method based on the community status of service robots according to any embodiment of the present invention.

[0014] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the intelligent operation management method based on the community status of service robots as described in any embodiment of the present invention.

[0015] This invention addresses the problem of how to perform unified intelligent operation and management of robot clusters based on robot communities by acquiring the health value of each type of robot cluster within a robot community, wherein the robot community includes at least two types of robot clusters; generating target control instructions for each type of robot cluster based on the health value of each type of robot cluster; and sending the target control instructions to the corresponding robot cluster. This allows for adjusting the type and number of robot clusters receiving tasks, thereby adjusting the overall processing capacity of the robot community and improving overall service levels and operational efficiency.

[0016] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of an intelligent operation and management method based on the community status of service robots according to Embodiment 1 of the present invention;

[0019] Figure 2 This is a schematic diagram of the structure of an intelligent operation management device based on the community status of service robots in Embodiment 2 of the present invention;

[0020] Figure 3 This is a schematic diagram of the structure of an electronic device according to Embodiment 3 of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 the invention 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 a non-exclusive inclusion; for example, a process, method, system, product, or apparatus 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 apparatus.

[0023] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0024] Example 1

[0025] Figure 1 This is a flowchart of an intelligent operation management method based on the community status of service robots according to Embodiment 1 of the present invention. This embodiment is applicable to intelligent operation management based on the community status of robots. The method can be executed by the intelligent operation management device based on the community status of service robots in this embodiment of the invention. This device can be implemented in software and / or hardware, such as... Figure 1 As shown, this method is executed by a cloud server and specifically includes the following steps:

[0026] S110, obtain the health value corresponding to each type of robot cluster in the robot community, wherein the robot community includes at least two types of robot clusters.

[0027] The health value serves as a health index for the robot cluster, used to determine whether different types of robot clusters within a robot community can perform tasks normally. A robot community includes at least two types of robot clusters, with each cluster consisting of multiple robots performing the same type of task.

[0028] Specifically, the health value of each type of robot cluster in the robot community can be obtained by: the cloud server obtaining the status information of each robot in each type of robot cluster in the robot community, and obtaining the health value based on the status information.

[0029] S120: Generate target control instructions for each type of robot cluster based on the health value corresponding to each type of robot cluster, and send the target control instructions to the corresponding robot cluster.

[0030] Among them, the target control instructions are the instructions that the robot swarm can execute.

[0031] Specifically, the method for generating target control instructions for each type of robot cluster based on its corresponding health value and sending these instructions to the corresponding robot cluster can be as follows: The cloud server generates target control instructions for each type of robot cluster based on its health value and sends these instructions to the corresponding robot clusters to enable coordinated operation among different types of robot clusters within the robot community. For example, if a robot cluster's health value is 90, which is higher than the preset health value threshold of 70, it indicates that the robot cluster is functioning normally. The cloud server then generates target control instructions based on the health value and the total workload corresponding to the robot cluster and sends these instructions to the robot cluster.

[0032] Optionally, obtain the health value corresponding to each type of robot cluster in the robot community, including:

[0033] Obtain the status information of robots in each type of robot cluster within the robot community;

[0034] The health value of each type of robot cluster is determined based on the status information.

[0035] The status information may include: battery remaining operating time, busy status, idle status, charging status, total robot operating time, total number of faults, hardware lifespan, frequency of anomaly reports, maintenance logs, etc.

[0036] Specifically, the way to obtain the status information of robots in each type of robot cluster in the robot community is as follows: the cloud server can maintain a real-time connection with all different types of robots through network communication, and the cloud server can obtain the status information of each robot in real time.

[0037] Specifically, the method for determining the health value of each type of robot cluster based on the status information can be as follows: after obtaining the status information of each robot, the cloud server aggregates the status information of robots in the same robot cluster and obtains the health value of each type of robot cluster based on the status information.

[0038] Optionally, a health value for each type of robot cluster is determined based on the status information, including:

[0039] The idle ratio of each type of robot cluster is determined based on the robot's status information;

[0040] The failure ratio of each type of robot cluster is determined based on the robot's status information;

[0041] The health value of each type of robot cluster is determined based on the status information, the idle ratio, and the fault ratio.

[0042] Specifically, the idle ratio of each type of robot cluster can be determined based on the robot's status information as follows: The cloud server obtains the number of idle robots in the same type of robot cluster and the total number of robots in the same type of robot cluster from the robot status information. The idle ratio is then calculated based on the number of idle robots and the total number of robots in the same type of robot cluster. For example, the idle ratio can be calculated as: Idle ratio = Number of idle robots in the same type of robot cluster / Total number of robots in the same type of robot cluster * 100.

[0043] Specifically, the method for determining the failure ratio of each type of robot cluster based on the robot's status information can be as follows: The cloud server obtains the total number of failures and the total uptime of all robots in the same type of robot cluster from the robot status information. The failure ratio is then calculated based on the total number of failures and the total uptime of all robots in the same type of robot cluster. For example, the failure ratio can be calculated as follows: Failure Ratio = (Total number of failures of all robots in the same type of robot cluster / Total uptime of all robots in the same type of robot cluster) * 100.

[0044] Specifically, the method for determining the health value of each type of robot cluster based on the status information, the idle ratio, and the fault ratio can be as follows: Determine the remaining battery power of all robots in the same type of robot cluster based on the robot's status information; then determine the health value of each type of robot cluster based on the remaining battery power, idle ratio, and fault ratio of all robots in the same type of robot cluster. For example, the health value can be calculated as: Health value = (Sum of remaining battery power of each robot in the same type of robot cluster / Total number of robots in the same type of robot cluster + Idle ratio) / 2 - Fault ratio. Alternatively, the method for determining the health value of each type of robot cluster based on the status information, idle ratio, and fault ratio can be as follows: Determine the health value of each type of robot cluster based on operational data such as the busy ratio, idle ratio, battery continuous working time, hardware lifespan, anomaly reporting frequency, and maintenance logs of robots in the same type of robot cluster.

[0045] It should be noted that after the cloud server determines the health value of each type of robot cluster based on the aforementioned status information, it can determine the overall health index of the robot community based on the health value of each type of robot cluster. The calculation method is: Overall Health Index = Sum of the health values ​​of all types of robot clusters in the robot community / Total number of robot cluster types. The cloud server can set an overall health value threshold. If the overall health index falls below the threshold, all robots will be stopped from operating, and maintenance personnel will be notified to repair the robot community. The cloud server monitors the robot community in real time based on the overall health index to ensure the normal operation of the robot community.

[0046] Optionally, generating target control instructions for each type of robot cluster based on the health value corresponding to each type of robot cluster, and sending the target control instructions to the corresponding robot cluster, including:

[0047] Obtain the health threshold value corresponding to each type of robot cluster;

[0048] If the health value of the robot cluster is lower than or equal to the health value threshold, then obtain the target task quantity corresponding to the health value;

[0049] Based on the target task volume, generate target control instructions for each type of robot cluster and send the target control instructions to the corresponding robot cluster.

[0050] There can be multiple health thresholds, and each type of robot cluster can correspond to one health threshold. The target task volume is the number of tasks that the robot cluster can handle, intelligently assessed based on its current health value, and is the number of tasks that the robot cluster can handle out of the total number of tasks it has already received.

[0051] Specifically, the health threshold for each type of robot cluster can be obtained by: the cloud server can preset the corresponding health threshold for each type of robot cluster.

[0052] Specifically, if the health value of the robot cluster is lower than or equal to the health value threshold, the target task volume corresponding to the health value can be obtained as follows: if the health value of the robot cluster is lower than or equal to the health value threshold, the cloud server evaluates the target task volume that each type of robot cluster can undertake based on the health value of each type of robot cluster.

[0053] Specifically, the method for generating target control instructions for each type of robot cluster based on the target task volume and sending the target control instructions to the corresponding robot cluster can be as follows: After determining the target task volume for each type of robot cluster, the cloud server generates target control instructions based on the target task volume and sends the target control instructions to the corresponding robot cluster. For example, when the health value of a spray disinfection robot cluster is lower than the health value threshold, it indicates that the spray disinfection robot cluster is unable to handle the total task volume it has received. The cloud server assesses the target task volume based on the health value of the spray disinfection robot cluster, generates target control instructions based on the target task volume, and sends the target control instructions to the spray disinfection robot cluster, causing the spray disinfection robot cluster to execute the target control instructions.

[0054] It should be noted that the cloud server assesses the target task volume of the robot cluster based on the cluster's health value. If the target task volume exceeds the total task volume already received by the robot cluster, the cloud server controls the task reception status valve, flexibly adjusting the total task volume to the target task volume and the remaining task volume. The target task volume valve is opened, and the remaining task volume is temporarily suspended. At the same time, each robot in the cluster can return to charge according to its remaining battery power, with robots with low battery power being charged first, thereby restoring the robot's health value. When the robot cluster completes the target task volume or the health value recovers to above the health value threshold, the remaining task volume reception status is restored.

[0055] Optional, also includes:

[0056] Obtain the occupied resources corresponding to at least two types of robot clusters that are in operation;

[0057] If at least two types of robot clusters occupy the same target resource, the priority of each type of robot cluster is determined based on the health value of each type of robot cluster.

[0058] The order in which target resources are occupied is determined based on the priorities of at least two types of robot clusters.

[0059] The occupied resources can be the resources required by the robot cluster when performing tasks, such as passageways and elevators. The target resource is the same resource among the occupied resources corresponding to at least two types of robot clusters.

[0060] Specifically, the method for obtaining the occupied resources corresponding to at least two types of robot clusters in operation can be as follows: the cloud server can obtain the occupied resources corresponding to at least two types of robot clusters in operation.

[0061] Specifically, if at least two types of robot clusters occupy the same target resource, the priority of each type of robot cluster can be determined based on its health value as follows: if at least two types of robot clusters occupy the same target resource, obtain the health values ​​of at least two types of robot clusters, and determine the priority of the robot clusters based on the health values. The lower the health value, the lower the priority.

[0062] Specifically, the method for determining the order of occupying target resources for at least two types of robot clusters based on their priorities can be as follows: the occupying order of robot clusters with higher priorities takes precedence over that of robot clusters with lower priorities.

[0063] For example, in a hospital setting, delivery robots and disinfection robots belong to different types of robot clusters. When the target resource is a hospital passageway, the two robots inevitably crowd each other out. If the cloud server detects that the health value of the delivery robot cluster is low, while the health value of the disinfection robot cluster is high, adjusting the priority of the delivery robots to be lower than that of the disinfection robots allows the disinfection robots to occupy the hospital passageway first. It should be noted that the cloud server can increase the priority of the disinfection robots while reducing the operating frequency of the delivery robots, thereby intelligently improving the service efficiency of the robot community.

[0064] Optionally, generating target control instructions for each type of robot cluster based on the health value corresponding to each type of robot cluster, and sending the target control instructions to the corresponding robot cluster, including:

[0065] The robot cluster is filtered based on the status information of each robot to obtain the target robot;

[0066] The target control command is generated based on the health value and then sent to the corresponding target robot.

[0067] The target robot is the robot that executes the target control commands.

[0068] Specifically, the robot cluster can be filtered to obtain target robots based on the status information of each robot. One method is for the cloud server to obtain the status information of each robot in the cluster and then filter the cluster based on the remaining battery power of each robot, identifying robots whose remaining battery power corresponds to a sustainable working time exceeding a preset target time as target robots. Another method is to filter the robot cluster based on the number of failures of each robot, identifying robots with a failure count below a preset failure threshold as target robots. It should be noted that the target robots can also be all robots in the robot cluster.

[0069] Specifically, the method of generating target control commands based on health values ​​and sending them to the corresponding target robots can be as follows: The cloud server generates target control commands based on the health values ​​of the robot cluster and sends them to the target robots in each type of robot cluster. Alternatively, the method can be: The target task volume is determined based on the health values, target control commands are generated based on the target task volume, and then sent to the target robots in each type of robot cluster.

[0070] Optionally, the status information of each robot includes: remaining battery power;

[0071] The robot cluster is filtered based on the status information of each robot to obtain the target robots, including:

[0072] Obtain the number of robots required for each type of robot cluster to perform the task;

[0073] The robot cluster is filtered based on the remaining battery power and the number of robots to obtain the target robot.

[0074] Specifically, the number of robots required for each type of robot cluster to execute a task can be obtained in the following ways: the number of robots required to execute a task can be obtained from historical data corresponding to the tasks executed by each type of robot cluster; or the number of robots preset when the task is published can be determined as the number of robots required to execute the task.

[0075] Specifically, the method for filtering the robot cluster based on the remaining battery power and the number of robots to obtain the target robot can be as follows: The cloud server sorts the robots from highest to lowest based on the remaining battery power of each robot in each type of robot cluster, and the robots with the highest number of remaining batteries in the sorted cluster are determined as the target robots. For example, if the number of robots is 3, then the top 3 robots sorted from highest to lowest based on remaining battery power are determined as the target robots.

[0076] By filtering the robot cluster using the status information of each robot, the target robot can be obtained. The health value of the robot cluster can be determined by the status information of each robot. Then, the robots in the robot cluster can be rationally allocated to perform tasks or recharge based on the status information of each robot and the health value of the robot cluster, thereby maintaining the health value of each type of robot cluster.

[0077] The technical solution of this embodiment obtains the health value corresponding to each type of robot cluster in the robot community, wherein the robot community includes at least two types of robot clusters; generates target control instructions corresponding to each type of robot cluster based on the health value of each type of robot cluster, and sends the target control instructions to the corresponding robot cluster. This solves the problem of how to perform unified intelligent operation and management of robot clusters based on the robot community, and can adjust the type and number of robot clusters receiving tasks, thereby adjusting the overall processing capacity of the robot community and improving the overall service level and operational efficiency.

[0078] Example 2

[0079] Figure 2 This is a schematic diagram of an intelligent operation management device based on the community status of service robots, according to Embodiment 2 of the present invention. This embodiment is applicable to intelligent operation management based on the community status of robots. The device can be implemented using software and / or hardware, and can be integrated into any device that provides intelligent operation management functionality based on the community status of service robots, such as… Figure 2 As shown, the intelligent operation management device based on the community status of service robots specifically includes: a first acquisition module 210 and a generation module 220.

[0080] The first acquisition module 210 is used to acquire the health value corresponding to each type of robot cluster in the robot community, wherein the robot community includes at least two types of robot clusters.

[0081] The generation module 220 is used to generate target control instructions for each type of robot cluster based on the health value corresponding to each type of robot cluster, and send the target control instructions to the corresponding robot cluster.

[0082] Optionally, the first acquisition module is specifically used for:

[0083] Obtain the status information of robots in each type of robot cluster within the robot community;

[0084] The health value of each type of robot cluster is determined based on the status information.

[0085] Optionally, the first acquisition module is specifically used for:

[0086] The idle ratio of each type of robot cluster is determined based on the robot's status information;

[0087] The failure ratio of each type of robot cluster is determined based on the robot's status information;

[0088] The health value of each type of robot cluster is determined based on the status information, the idle ratio, and the fault ratio.

[0089] Optionally, the generation module is specifically used for:

[0090] Obtain the health threshold value corresponding to each type of robot cluster;

[0091] If the health value of the robot cluster is lower than or equal to the health value threshold, then obtain the target task quantity corresponding to the health value;

[0092] Based on the target task volume, generate target control instructions for each type of robot cluster and send the target control instructions to the corresponding robot cluster.

[0093] Optional, also includes:

[0094] The second acquisition module is used to acquire the occupied resources corresponding to at least two types of robot clusters that are in operation.

[0095] The first determining module is used to determine the priority of each type of robot cluster based on the health value of each type of robot cluster if the same target resource exists in the occupied resources corresponding to at least two types of robot clusters.

[0096] The second determining module is used to determine the order of occupying target resources corresponding to at least two types of robot clusters based on their priorities.

[0097] Optionally, the generation module is specifically used for:

[0098] The robot cluster is filtered based on the status information of each robot to obtain the target robot;

[0099] The target control command is generated based on the health value and then sent to the corresponding target robot.

[0100] Optionally, the status information of each robot includes: remaining battery power;

[0101] The generation module is specifically used for:

[0102] The robot cluster is filtered based on the status information of each robot to obtain the target robots, including:

[0103] Obtain the number of robots required for each type of robot cluster to perform the task;

[0104] The robot cluster is filtered based on the remaining battery power and the number of robots to obtain the target robot.

[0105] The above-described products can perform the methods provided in any embodiment of the present invention, and have the corresponding functional modules and beneficial effects for performing the methods.

[0106] Example 3

[0107] Figure 3 This is a schematic diagram of an electronic device according to Embodiment 3 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0108] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0109] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0110] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as intelligent operation management methods based on the community status of service robots.

[0111] In some embodiments, the intelligent operation management method based on the service robot community state can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the intelligent operation management method based on the service robot community state described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the intelligent operation management method based on the service robot community state by any other suitable means (e.g., by means of firmware).

[0112] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0113] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0114] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0115] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0116] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0117] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0118] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0119] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An intelligent operation and management method based on the community status of service robots, characterized in that, The method, executed by a cloud server, includes: Obtain the health value corresponding to each type of robot cluster in the robot community, wherein the robot community includes at least two types of robot clusters; Based on the health value corresponding to each type of robot cluster, a target control command is generated for each type of robot cluster, and the target control command is sent to the corresponding robot cluster; This includes obtaining the health value for each type of robot cluster in the robot community, including: Obtain the status information of robots in each type of robot cluster within the robot community; The idle ratio of each type of robot cluster is determined based on the robot's status information; the idle ratio = number of idle robots in the same type of robot cluster / total number of robots in the same type of robot cluster × 100; The failure ratio of each type of robot cluster is determined based on the robot's status information; the failure ratio = (total number of failures of all robots in the same type of robot cluster / total uptime of all robots in the same type of robot cluster) × 100; Determine the remaining battery power of all robots in the same type of robot cluster based on the robot's status information; The health value of each type of robot cluster is determined based on the remaining power, idle ratio, and failure ratio of all robots in the same type of robot cluster; the health value = (sum of remaining power of each robot in the same type of robot cluster / total number of robots in the same type of robot cluster + idle ratio) / 2 - failure ratio.

2. The method according to claim 1, characterized in that, Based on the health value corresponding to each type of robot cluster, a target control command is generated for each type of robot cluster, and the target control command is sent to the corresponding robot cluster, including: Obtain the health threshold value corresponding to each type of robot cluster; If the health value of the robot cluster is lower than or equal to the health value threshold, then obtain the target task quantity corresponding to the health value; Based on the target task volume, generate target control instructions for each type of robot cluster and send the target control instructions to the corresponding robot cluster.

3. The method according to claim 1, characterized in that, Also includes: Obtain the occupied resources corresponding to at least two types of robot clusters that are in operation; If at least two types of robot clusters occupy the same target resource, the priority of each type of robot cluster is determined based on the health value of each type of robot cluster. The order in which target resources are occupied is determined based on the priorities of at least two types of robot clusters.

4. The method according to claim 1, characterized in that, Based on the health value corresponding to each type of robot cluster, a target control command is generated for each type of robot cluster, and the target control command is sent to the corresponding robot cluster, including: The robot cluster is filtered based on the status information of each robot to obtain the target robot; The target control command is generated based on the health value and then sent to the corresponding target robot.

5. The method according to claim 4, characterized in that, The status information of each robot includes: remaining battery power; The robot cluster is filtered based on the status information of each robot to obtain the target robots, including: Obtain the number of robots required for each type of robot cluster to perform the task; The robot cluster is filtered based on the remaining battery power and the number of robots to obtain the target robot.

6. An intelligent operation management device based on the community status of service robots, characterized in that, The device includes: The first acquisition module is used to acquire the health value corresponding to each type of robot cluster in the robot community, wherein the robot community includes at least two types of robot clusters; The generation module is used to generate target control instructions for each type of robot cluster based on the health value corresponding to each type of robot cluster, and send the target control instructions to the corresponding robot cluster. Specifically, the first acquisition module is used for: Obtain the status information of robots in each type of robot cluster within the robot community; The idle ratio of each type of robot cluster is determined based on the robot's status information; the idle ratio = number of idle robots in the same type of robot cluster / total number of robots in the same type of robot cluster × 100; The failure ratio of each type of robot cluster is determined based on the robot's status information; the failure ratio = (total number of failures of all robots in the same type of robot cluster / total uptime of all robots in the same type of robot cluster) × 100; Determine the remaining battery power of all robots in the same type of robot cluster based on the robot's status information; The health value of each type of robot cluster is determined based on the remaining power, idle ratio, and failure ratio of all robots in the same type of robot cluster; the health value = (sum of remaining power of each robot in the same type of robot cluster / total number of robots in the same type of robot cluster + idle ratio) / 2 - failure ratio.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the intelligent operation management method based on the community status of service robots as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the intelligent operation and management method based on the community status of service robots as described in any one of claims 1-5.

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