CN116372958A

CN116372958A - RPA robot control method, device, computer equipment and storage medium

Info

Publication number: CN116372958A
Application number: CN202310418135.9A
Authority: CN
Inventors: 吴燕青; 薛鑫; 孙长青; 刘玲; 彭亮文
Original assignee: Yuanguang Software Co Ltd
Current assignee: Yuanguang Software Co Ltd
Priority date: 2023-04-18
Filing date: 2023-04-18
Publication date: 2023-07-04

Abstract

The embodiment of the application belongs to the technical field of RPA robots, and relates to an RPA robot control method, which comprises the following steps: receiving a task to be processed; acquiring performance evaluation information of each RPA robot in an RPA cluster, and selecting at least one RPA robot from the RPA cluster according to the performance evaluation information of each RPA robot; generating execution configuration information based on the selected at least one RPA robot and the task to be processed; and calling the at least one RPA robot to execute the task to be processed according to the execution configuration information to obtain a task execution result. The application also provides an RPA robot control device, computer equipment and a storage medium. The method and the device realize accurate management and control on the RPA robots in the RPA cluster.

Description

RPA robot control method, device, computer equipment and storage medium

Technical Field

The present disclosure relates to the field of RPA robots, and in particular, to a method and apparatus for controlling an RPA robot, a computer device, and a storage medium.

Background

RPA robots (Robotic process automation), also known as RPA robot process automation, software robots, refer to the use of intelligent automation technology to perform repetitive tasks for human workers. The RPA robot needs to design rules in advance and then deploy scripts simulating manual processes, and the RPA robot completes autonomous execution of various activities and transactions.

RPA robots are now widely used, and RPA robots often use more RPA robots in applications to form RPA clusters. However, in the current RPA robot technology, a single RPA robot in the RPA cluster is managed, and simple instructions such as start and end are issued to the RPA robot, so that the RPA robot cannot be managed and controlled more effectively.

Disclosure of Invention

An aim of the embodiment of the application is to provide an RPA robot control method, an apparatus, a computer device and a storage medium, so as to solve the problem of accurately managing and controlling RPA robots in an RPA cluster.

In order to solve the above technical problems, the embodiments of the present application provide a RPA robot control method, which adopts the following technical scheme:

receiving a task to be processed;

acquiring performance evaluation information of each RPA robot in the RPA cluster;

selecting at least one RPA robot from the RPA cluster according to the performance evaluation information of each RPA robot;

generating execution configuration information based on the selected at least one RPA robot and the task to be processed;

and calling the at least one RPA robot to execute the task to be processed according to the execution configuration information to obtain a task execution result.

Further, the step of obtaining performance evaluation information of each RPA robot in the RPA cluster includes:

acquiring a first performance evaluation factor and a second performance evaluation factor of each RPA robot in an RPA cluster, wherein the first performance evaluation factor is related to a first environment where the RPA robot is located, and the second performance evaluation factor is related to a second environment where the RPA robot is located;

and respectively generating performance evaluation information of each RPA robot according to the first performance evaluation factor and the second performance evaluation factor of each RPA robot.

Further, the step of selecting at least one RPA robot from the RPA cluster according to the performance evaluation information of each RPA robot includes:

calculating performance evaluation values of the RPA robots according to the performance evaluation information of the RPA robots;

and selecting at least one RPA robot from the RPA robots according to the obtained performance evaluation value.

Further, the step of generating execution configuration information based on the selected at least one RPA robot and the task to be processed includes:

acquiring task evaluation information of the task to be processed;

based on the selected at least one RPA robot and the task evaluation information, generating execution configuration information, wherein the execution configuration information comprises an RPA working mode and an execution sequence type.

Further, the step of calling the at least one RPA robot to execute the task to be processed according to the execution configuration information to obtain a task execution result includes:

according to the execution sequence type in the execution configuration information, adjusting a task execution queue of the at least one RPA robot, wherein the execution sequence type comprises sequential execution and priority execution;

and calling the at least one RPA robot based on the RPA working mode in the execution configuration information according to the adjusted task execution queue so as to execute the task to be processed through the at least one RPA robot to obtain a task execution result.

Further, the method further comprises:

for each RPA robot, acquiring the communication state of the RPA robot;

when the RPA robot is in a first communication state, communicating with the RPA robot according to a preset first communication mode, wherein the first communication mode is network communication;

when the RPA robot is in a second communication state, the RPA robot is communicated with the RPA robot according to a preset second communication mode, and the second communication mode comprises Bluetooth, infrared and Lora.

Further, the method further comprises:

Acquiring data to be processed, wherein the data to be processed comprises operation data and operation logs of each RPA robot and task execution results of each task to be processed;

carrying out data cleaning on the data to be processed to obtain cleaned data;

and processing the cleaned data according to a preset data processing strategy to obtain processed data, wherein the data processing strategy is matched with the data type of the data to be processed.

In order to solve the above technical problems, the embodiment of the present application further provides an RPA robot control device, which adopts the following technical scheme:

the task receiving module is used for receiving a task to be processed;

the evaluation acquisition module is used for acquiring performance evaluation information of each RPA robot in the RPA cluster;

the selecting module is used for selecting at least one RPA robot from the RPA cluster according to the performance evaluation information of each RPA robot;

the configuration generation module is used for generating execution configuration information based on the selected at least one RPA robot and the task to be processed;

and the task execution module is used for calling the at least one RPA robot to execute the task to be processed according to the execution configuration information to obtain a task execution result.

To solve the above technical problem, the embodiments of the present application further provide a computer device, where the computer device includes a memory and a processor, where the memory stores computer readable instructions, and the processor implements the steps of the RPA robot control method as described above when executing the computer readable instructions.

To solve the above technical problem, the embodiments of the present application further provide a computer readable storage medium, where computer readable instructions are stored on the computer readable storage medium, where the computer readable instructions implement the steps of the RPA robot control method as described above when executed by a processor.

Compared with the prior art, the embodiment of the application has the following main beneficial effects: receiving a task to be processed; the performance evaluation information of each RPA robot in the RPA cluster is acquired, and the performance evaluation information is used for evaluating the task processing capacity of each RPA robot, so that at least one RPA robot with stronger task processing capacity can be selected based on the performance evaluation information, and the processing efficiency of a task to be processed is ensured; based on the selected at least one RPA robot and the task to be processed, execution configuration information is generated, and the execution configuration information indicates how the selected at least one RPA robot processes the task to be processed, so that the task to be processed can be further ensured to be reasonably executed, the efficiency and the accuracy of a task execution result obtained after the task is executed are improved, and the RPA robots in the RPA cluster are accurately managed and controlled.

Drawings

For a clearer description of the solution in the present application, a brief description will be given below of the drawings that are needed in the description of the embodiments of the present application, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.

FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;

FIG. 2 is a flow chart of one embodiment of an RPA robot control method according to the present application;

FIG. 3 is a schematic structural view of one embodiment of an RPA robotic control device according to the present application;

FIG. 4 is a schematic structural diagram of one embodiment of a computer device according to the present application.

Detailed Description

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description and claims of the present application and in the description of the figures above are intended to cover non-exclusive inclusions. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

In order to better understand the technical solutions of the present application, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings.

As shown in fig. 1, a system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the

terminal devices

101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may interact with the server 105 via the network 104 using the

terminal devices

101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the

terminal devices

101, 102, 103.

The

terminal devices

101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like. At least one RPA robot is operated on each terminal device, and the RPA robots on all terminal devices form an RPA cluster.

The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the

terminal devices

101, 102, 103.

It should be noted that, the RPA robot control method provided in the embodiments of the present application is generally executed by a server, and accordingly, the RPA robot control device is generally disposed in the server.

It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

With continued reference to fig. 2, a flowchart of one embodiment of an RPA robot control method according to the present application is shown. The RPA robot control method comprises the following steps:

step S201, a task to be processed is received.

In this embodiment, the electronic device (for example, the server shown in fig. 1) on which the RPA robot control method operates may communicate with each terminal through a wired connection or a wireless connection. It should be noted that the wireless connection may include, but is not limited to, 3G/4G/5G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection.

Specifically, a task to be processed is received, where the task to be processed refers to a task processed by an RPA robot in the RPA cluster.

Step S202, performance evaluation information of each RPA robot in the RPA cluster is obtained.

Specifically, performance evaluation information of each RPA robot in the RPA cluster is obtained, where the performance evaluation information may include evaluation factors of multiple dimensions, and is used to evaluate the processing performance of each RPA robot on the task.

In the application, one RPA robot may operate on a plurality of terminal devices, and one terminal device may also operate a plurality of RPA robots. The states of the RPA robot include idle, working, and offline. Here, the performance evaluation information may refer to performance evaluation information of the RPA robot that has been run on the terminal device; the performance evaluation information of the new RPA robot may be obtained by allocating and operating the new RPA robot to a certain terminal device.

Step S203, selecting at least one RPA robot from the RPA cluster according to the performance evaluation information of each RPA robot.

Specifically, according to the performance evaluation information of each RPA robot in the RPA cluster, the processing performance/processing capability of each RPA robot on the task can be determined, and at least one RPA robot can be selected from each RPA robot based on the performance evaluation information of each RPA robot; it will be appreciated that the selected RPA robot should have a high task handling capability.

And, the selected RPA robot can be an RPA robot which is already operated on the terminal equipment; or a new RPA robot, which is assigned and operated to a certain terminal device after being selected.

Step S204, generating execution configuration information based on the selected at least one RPA robot and the task to be processed.

Specifically, based on the selected at least one RPA robot and the task to be processed, execution configuration information is generated, where the execution configuration information corresponds to an instruction, and indicates the processing of the task to be processed by the RPA robot, for example, the execution configuration information may indicate when to execute the task to be processed.

When the number of the selected RPA robots is more than two, each RPA robot needs to process the task to be processed together, at this time, the relation and the connection of each RPA robot in the task execution process are also required to be set, for example, the task to be processed is divided into a plurality of subtasks, different subtasks can be handed to different RPA robots for processing, and a certain RPA robot generates a final result; the above information may be recorded in the execution configuration information.

Step S205, at least one RPA robot is called to execute the task to be processed according to the execution configuration information, and a task execution result is obtained.

Specifically, based on the generated execution configuration information, at least one RPA robot is called to execute the task to be processed, and a task execution result is generated.

In this embodiment, a task to be processed is received; the performance evaluation information of each RPA robot in the RPA cluster is acquired, and the performance evaluation information is used for evaluating the task processing capacity of each RPA robot, so that at least one RPA robot with stronger task processing capacity can be selected based on the performance evaluation information, and the processing efficiency of a task to be processed is ensured; based on the selected at least one RPA robot and the task to be processed, execution configuration information is generated, and the execution configuration information indicates how the selected at least one RPA robot processes the task to be processed, so that the task to be processed can be further ensured to be reasonably executed, the efficiency and the accuracy of a task execution result obtained after the task is executed are improved, and the RPA robots in the RPA cluster are accurately managed and controlled.

Further, the step S202 may include: acquiring a first performance evaluation factor and a second performance evaluation factor of each RPA robot in the RPA cluster, wherein the first performance evaluation factor is related to a first environment where the RPA robot is located, and the second performance evaluation factor is related to a second environment where the RPA robot is located; and respectively generating performance evaluation information of each RPA robot according to the first performance evaluation factor and the second performance evaluation factor of each RPA robot.

Specifically, each RPA robot in the RPA cluster has an operating environment, and the operating environment of the RPA robot is divided into a first environment and a second environment in the application. The first environment may be a virtual machine where the RPA robot is located; the second environment may be a terminal device where the RPA robot is located, or a terminal device where the virtual machine is located.

The RPA robot has a first performance assessment factor and a second performance assessment factor, which may both be multi-dimensional assessment factors; wherein the first performance assessment factor is associated with the first environment for reflecting relevant parameters of the first environment, such as: whether the tasks to be processed exist, the number of the tasks to be processed historically, the execution time and the execution frequency, and the CPU service condition of the virtual machine; a second performance assessment factor is associated with the second environment for reflecting relevant parameters of the second environment, such as: whether the terminal equipment is idle, whether the terminal equipment is currently processing tasks, CPU service conditions and the like. It will be appreciated that the factor features in the first performance assessment factor and the second performance assessment factor may be similar, but one representing the first environment and one representing the second environment.

The first performance evaluation factor and the second performance evaluation factor of each RPA robot respectively form performance evaluation information of each RPA robot.

When the RPA robot directly operates in the first environment, only the first evaluation factor (the second evaluation factor is marked as null) may be acquired, or the first performance evaluation factor and the second performance evaluation factor may be acquired simultaneously (the second evaluation factor is not null). When the RPA robot is operating in the second environment, only the second evaluation factor thereof (the first evaluation factor is marked as null) may be acquired, or the first performance evaluation factor (the first evaluation factor is marked as null) and the second performance evaluation factor may be acquired at the same time.

In this embodiment, a first performance evaluation factor and a second performance evaluation factor of each RPA robot are obtained, where the first performance evaluation factor is related to a first environment where the RPA robot is located, and the second performance evaluation factor is related to a second environment where the RPA robot is located; the first performance evaluation factor and the second performance evaluation factor of each RPA robot form performance evaluation information of each RPA robot, so that comprehensive performance evaluation of the RPA robots is ensured.

Further, the step S203 may include: calculating performance evaluation values of the RPA robots according to the performance evaluation information of the RPA robots; and selecting at least one RPA robot from the RPA robots according to the obtained performance evaluation value.

Specifically, for each RPA robot, a factor weight may be added to each specific evaluation factor in its performance evaluation information. The factor weight can be preset, or can be calculated by a CRITIC algorithm, an analytic hierarchy process and other weight algorithms.

And carrying out weighted calculation according to the evaluation factors and the corresponding weights to obtain a performance evaluation value of the RPA robot, wherein the performance evaluation value represents the task processing capacity of the RPA robot in terms of the numerical value.

Each RPA robot may calculate a performance evaluation value, and select at least one RPA robot from the RPA robots according to the performance evaluation value, for example, select one or several RPA robots having the largest performance evaluation value.

In one embodiment, various evaluation factors in the performance evaluation information may be further input into a performance evaluation model, the performance evaluation model may be constructed based on the LGBM model, and trained in advance, the performance evaluation model classifies the RPA robots according to the evaluation factors, each class has a preset performance evaluation value, and the performance evaluation value of the class is used as the performance evaluation value of the RPA robot.

In this embodiment, according to the performance evaluation information of each RPA robot, a performance evaluation value of each RPA robot is calculated, and the performance evaluation value indicates the task processing capability of each RPA robot in terms of a numerical value; and selecting at least one RPA robot with stronger task processing capability from the RPA robots according to the performance evaluation value, thereby ensuring the execution efficiency of the task to be processed.

Further, the step S204 may include: acquiring task evaluation information of a task to be processed; based on the selected at least one RPA robot and task evaluation information, generating execution configuration information, wherein the execution configuration information comprises an RPA working mode and an execution sequence type.

Specifically, the task to be processed has task evaluation information, which may be multidimensional information, for evaluating and describing the task to be processed. For example, it includes the data amount of a data table to be processed by a task to be processed, the degree of urgency of the task to be processed, the execution condition of the task to be processed, and the like.

Based on the selected at least one RPA robot and task evaluation information, generating execution configuration information, wherein the execution configuration information comprises an RPA working mode and an execution sequence type. Because a plurality of RPA robots can be selected, the plurality of RPA robots have a cooperative relationship or an association relationship in data processing; the relation can be defined through an RPA working mode, wherein the RPA working mode comprises a master working mode, a slave working mode, a monomer working mode and the like; wherein, the main means that each RPA robot provides service at the same time, and the load is balanced; the master-slave means that one RPA robot is used as a host, other RPA robots are used as slaves, and the slave can be understood as slave to help the host to process data; the slave is the RPA robot; the monomer refers to the case where only one RPA robot is selected.

The RPA working mode can be preset, set randomly, or determined according to the data amount to be processed recorded in the task evaluation information, for example, when the data amount is small, one RPA robot can be selected and a single mode is performed; when the data amount is more, a master-slave mode can be selected; when the amount of data is larger, the main mode can be selected.

The type of execution sequence may be determined according to the urgency of the task to be processed and the execution condition. For example, when the task to be processed is urgent, the task to be processed can be preferentially executed; when the execution condition indicates that the task to be processed is a timed task, it can be executed normally.

In the embodiment, task evaluation information of a task to be processed is obtained, and the task evaluation information evaluates and describes the task to be processed; and generating execution configuration information based on the selected RPA robot and task evaluation information, wherein the execution configuration information comprises an RPA working mode and an execution sequence type, and indicating the execution of the task.

Further, the step S205 may include: according to the execution sequence type in the execution configuration information, adjusting a task execution queue of at least one RPA robot, wherein the execution sequence type comprises sequential execution and priority execution; and calling at least one RPA robot based on the RPA working mode in the execution configuration information according to the adjusted task execution queue so as to execute the task to be processed through the at least one RPA robot and obtain a task execution result.

Specifically, the RPA robot has a task execution queue, and the task execution queue records tasks to be processed to be executed by the RPA robot.

The execution sequence type in the execution configuration information comprises sequence execution and priority execution, wherein the sequence execution is to execute the task to be processed according to the common sequence, add the task to be processed to the tail part of the task execution queue, and execute the task to be processed in the task execution queue from front to back by the RPA robot; the priority execution means that the priority of the task to be processed is higher, the task to be processed is added to the head of the task execution queue, and the task to be processed in the task execution queue is executed from front to back by the RPA robot; when the task to be processed is added to the head of the task execution queue, the task to be processed can be added to the forefront, the emergency degree of the task to be processed can be compared with the emergency degree of other tasks to be processed of the head, and the task to be processed of the head can be reordered according to the emergency degree.

It will be appreciated that if the task to be processed involves multiple RPA robots, the task execution queue for each RPA robot needs to perform the same processing.

And calling at least one RPA robot based on the RPA working mode in the execution configuration information according to the adjusted task execution queue, and executing the task to be processed through the at least one RPA robot to obtain a task execution result.

In this embodiment, the task execution queue of the RPA robot is adjusted according to the execution order type in the execution configuration information, and the RPA robot is invoked to execute the task to be processed according to the adjusted task execution queue and the execution configuration information, so that correct processing of the task to be processed is ensured.

Further, the RPA robot control method may further include: for each RPA robot, acquiring the communication state of the RPA robot; when the RPA robot is in a first communication state, communicating with the RPA robot according to a preset first communication mode, wherein the first communication mode is network communication; when the RPA robot is in a second communication state, the RPA robot is communicated according to a preset second communication mode, wherein the second communication mode comprises Bluetooth, infrared and Lora.

Specifically, the RPA robot has a communication state, which refers to a communication manner between the RPA robot and the server, and it can be understood that it is also a communication manner between the terminal device and the server.

The communication state comprises a first communication state and a second communication state, wherein the first communication state refers to that communication can be carried out between the RPA robot and the server through a network, at this time, the server communicates with the RPA robot according to a first communication mode, and the first communication mode is network communication, including wired network communication and wireless network communication.

When the RPA robot is in the second communication state, communication between the RPA robot and the server through the network is not possible. The application improves the RPA robot and the server, and can communicate with the RPA robot according to a second communication mode under a second communication state, wherein the second communication mode comprises Bluetooth, infrared and Lora (a low-power local area network wireless standard, also called Long Range Radio).

In this embodiment, the communication state of the RPA robot is obtained, and different communication modes are adopted to communicate according to the communication state, so that it is ensured that communication can be performed with the RPA robot under various conditions, and the RPA robot can be controlled under various conditions.

Further, the RPA robot control method may further include: acquiring data to be processed, wherein the data to be processed comprises operation data and operation logs of each RPA robot and task execution results of each task to be processed; data cleaning is carried out on the data to be processed to obtain cleaned data; and processing the cleaned data according to a preset data processing strategy to obtain processed data, wherein the data processing strategy is matched with the data type of the data to be processed.

Specifically, data to be processed is obtained, wherein the data to be processed comprises operation data and operation logs of each RPA robot and task execution results of each task to be processed; the operation data may be data generated by the RPA robot in operation, and the operation log refers to a log generated by the RPA robot in operation, and the operation data and the operation log are generated no matter whether the RPA robot performs a task to be processed or not, and only if the RPA robot runs on the terminal device.

The server performs data cleaning on the data to be processed to obtain cleaned data. According to the data type of the data to be processed, a corresponding data processing strategy is acquired, for example, different data processing strategies are needed to be used for the operation log and the task execution result, and the task execution result may contain more business elements. And processing the cleaned data according to a preset data processing strategy to obtain processed data, and completing data fusion and summarization processing in the RPA cluster.

In this embodiment, data to be processed is obtained, including operation data and operation logs of each RPA robot, and task execution results of each task to be processed; data cleaning is carried out on the data to be processed to obtain cleaned data; and processing the cleaned data according to a preset data processing strategy to obtain processed data, and completing data fusion and summarization processing in the RPA cluster.

The server of the application can comprise a cluster center, a regulation and control component, a monitoring component and a data processing console. The cluster center is used for carrying out comprehensive scheduling and analysis, such as selecting an RPA robot, generating execution configuration information and the like; the regulation and control component is used for realizing specific scheduling and task execution of the RPA robot cluster; the resource monitoring component is used for collecting performance evaluation information, operation data and operation logs of each RPA robot; the data processing middle stage obtains the data to be processed to process the data.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by computer readable instructions stored in a computer readable storage medium that, when executed, may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.

With further reference to fig. 3, as an implementation of the method shown in fig. 2, the present application provides an embodiment of an RPA robot control device, where the embodiment of the device corresponds to the embodiment of the method shown in fig. 2, and the device may be specifically applied to various electronic devices.

As shown in fig. 3, the RPA robot control device 300 according to the present embodiment includes: a task receiving module 301, an evaluation obtaining module 302, a selecting module 303, a configuration generating module 304 and a task executing module 305, wherein:

the task receiving module 301 is configured to receive a task to be processed.

And the evaluation acquisition module 302 is configured to acquire performance evaluation information of each RPA robot in the RPA cluster.

And the selecting module 303 is configured to select at least one RPA robot from the RPA cluster according to the performance evaluation information of each RPA robot.

The configuration generating module 304 is configured to generate execution configuration information based on the selected at least one RPA robot and the task to be processed.

The task execution module 305 is configured to call at least one RPA robot to execute a task to be processed according to the execution configuration information, so as to obtain a task execution result.

In some alternative implementations of the present embodiment, the evaluation acquisition module 302 may include: factor acquisition module and evaluation generation sub-module, wherein:

the factor acquisition module is used for acquiring a first performance evaluation factor and a second performance evaluation factor of each RPA robot in the RPA cluster, wherein the first performance evaluation factor is related to a first environment where the RPA robot is located, and the second performance evaluation factor is related to a second environment where the RPA robot is located.

And the evaluation generation sub-module is used for respectively generating performance evaluation information of each RPA robot according to the first performance evaluation factor and the second performance evaluation factor of each RPA robot.

In some alternative implementations of the present embodiment, the selecting module 303 may include: the evaluation value calculation sub-module and the robot selection sub-module, wherein:

And the evaluation value calculation sub-module is used for calculating the performance evaluation value of each RPA robot according to the performance evaluation information of each RPA robot.

And the robot selecting sub-module is used for selecting at least one RPA robot from the RPA robots according to the obtained performance evaluation value.

In some alternative implementations of the present embodiment, the configuration generation module 304 may include: the system comprises an information acquisition sub-module and a configuration generation sub-module, wherein:

and the information acquisition sub-module is used for acquiring task evaluation information of the task to be processed.

The configuration generation sub-module is used for generating execution configuration information based on the selected at least one RPA robot and task evaluation information, wherein the execution configuration information comprises an RPA working mode and an execution sequence type.

In some alternative implementations of the present embodiment, the task execution module 305 may include: a queue adjustment sub-module and a task execution sub-module, wherein:

the queue adjusting sub-module is used for adjusting the task execution queue of at least one RPA robot according to the execution sequence type in the execution configuration information, wherein the execution sequence type comprises sequential execution and priority execution.

And the task execution sub-module is used for calling at least one RPA robot based on the RPA working mode in the execution configuration information according to the adjusted task execution queue so as to execute the task to be processed through the at least one RPA robot and obtain a task execution result.

In some optional implementations of the present embodiment, the RPA robot control device 300 may further include: the system comprises a state acquisition module, a first communication module and a second communication module, wherein:

and the state acquisition module is used for acquiring the communication state of each RPA robot.

The first communication module is used for communicating with the RPA robot according to a preset first communication mode when the RPA robot is in a first communication state, wherein the first communication mode is network communication.

And the second communication module is used for communicating with the RPA robot according to a preset second communication mode when the RPA robot is in a second communication state, wherein the second communication mode comprises Bluetooth, infrared and Lora.

In some optional implementations of the present embodiment, the RPA robot control device 300 may further include: the device comprises a data acquisition module, a data cleaning module and a data processing module, wherein:

the data acquisition module is used for acquiring data to be processed, wherein the data to be processed comprises operation data and operation logs of each RPA robot and task execution results of each task to be processed.

The data cleaning module is used for cleaning the data to be processed to obtain cleaned data.

The data processing module is used for processing the cleaned data according to a preset data processing strategy to obtain processed data, wherein the data processing strategy is matched with the data type of the data to be processed.

In order to solve the technical problems, the embodiment of the application also provides computer equipment. Referring specifically to fig. 4, fig. 4 is a basic structural block diagram of a computer device according to the present embodiment.

The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It should be noted that only computer device 4 having components 41-43 is shown in the figures, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.

The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.

The memory 41 includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the storage 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 4. Of course, the memory 41 may also comprise both an internal memory unit of the computer device 4 and an external memory device. In this embodiment, the memory 41 is typically used to store an operating system and various application software installed on the computer device 4, such as computer readable instructions of an RPA robot control method, and the like. Further, the memory 41 may be used to temporarily store various types of data that have been output or are to be output.

The processor 42 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is configured to execute computer readable instructions stored in the memory 41 or process data, such as computer readable instructions for executing the RPA robot control method.

The network interface 43 may comprise a wireless network interface or a wired network interface, which network interface 43 is typically used for establishing a communication connection between the computer device 4 and other electronic devices.

The computer device provided in the present embodiment may execute the RPA robot control method described above. The RPA robot control method here may be the RPA robot control method of each of the above embodiments.

The present application also provides another embodiment, namely, a computer-readable storage medium storing computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of the RPA robot control method as described above.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method described in the embodiments of the present application.

It is apparent that the embodiments described above are only some embodiments of the present application, but not all embodiments, the preferred embodiments of the present application are given in the drawings, but not limiting the patent scope of the present application. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a more thorough understanding of the present disclosure. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing, or equivalents may be substituted for elements thereof. All equivalent structures made by the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the protection scope of the application.

Claims

1. An RPA robot control method, comprising the steps of:

receiving a task to be processed;

2. The RPA robot control method according to claim 1, wherein the step of acquiring performance evaluation information of each RPA robot in the RPA cluster includes:

3. The RPA robot control method according to claim 1, wherein the step of selecting at least one RPA robot from the RPA cluster according to the performance evaluation information of each RPA robot comprises:

4. The RPA robot control method according to claim 1, wherein the step of generating execution configuration information based on the selected at least one RPA robot and the task to be processed comprises:

acquiring task evaluation information of the task to be processed;

5. The RPA robot control method according to claim 4, wherein the step of calling the at least one RPA robot to execute the task to be processed according to the execution configuration information, and obtaining a task execution result includes:

6. The RPA robot control method according to claim 1, further comprising:

for each RPA robot, acquiring the communication state of the RPA robot;

7. The RPA robot control method according to claim 1, further comprising:

carrying out data cleaning on the data to be processed to obtain cleaned data;

8. An RPA robot control device, comprising:

The task receiving module is used for receiving a task to be processed;

9. A computer device comprising a memory having stored therein computer readable instructions which when executed by the processor implement the steps of the RPA robot control method of any one of claims 1 to 7.

10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon computer readable instructions, which when executed by a processor, implement the steps of the RPA robot control method according to any one of claims 1 to 7.