CN115860366B

CN115860366B - Intelligent coordination control method and system for community robot and readable storage medium

Info

Publication number: CN115860366B
Application number: CN202211459185.3A
Authority: CN
Inventors: 邹杰慧; 李春泉; 张明; 黄红艳; 彭宏伟
Original assignee: Guilin University of Electronic Technology
Current assignee: Guilin University of Electronic Technology
Priority date: 2022-11-17
Filing date: 2022-11-17
Publication date: 2024-05-14
Anticipated expiration: 2042-11-17
Also published as: CN115860366A

Abstract

The embodiment of the application provides a community robot intelligent coordination control method, a community robot intelligent coordination control system and a readable storage medium. The method comprises the following steps: performing task quantity analysis on community service demand information to generate a task element list, performing task information data analysis, distributing robots of corresponding categories to generate a robot community task organization tree, performing statistics to obtain a task density data set, generating a community robot task data image, extracting robot project service data to process to obtain robot task response data, generating a task allocation list according to robot task data instruction in a generated time period, and performing task allocation on the robots; therefore, information acquisition and data processing are carried out on community services based on big data and intelligent robot technology so as to optimize allocation of type robots, function matching is carried out on the community service demand information and robot resources, optimal allocation of the community robot resources is achieved, and intelligence and accuracy of community robot management application are improved.

Description

Intelligent coordination control method and system for community robot and readable storage medium

Technical Field

The application relates to the technical field of big data and community robot services, in particular to a community robot intelligent coordination management and control method, a system and a readable storage medium.

Background

At present, the robot technology is developed rapidly, the application of robots is widened to the aspects of production and living, the research and development and application of household small and miniature multifunctional robots and community robots are wider, but aiming at the development and application of all-field, all-system and all-dimensional community robot service resources of community services, the development and application of the robot management application technology and the deployment system which can adapt to the multi-functional requirements of communities and users are weak, so that the scientific management and deployment of the community robot resources of solitary old people, child care, cooking cleaning, epidemic prevention and distribution services are realized, and the community robot service resources do not have a comprehensive, multi-system and multi-dimensional scientific management system.

Therefore, how to build the comprehensive, multi-directional and systematic intelligent robot resource management application technology and system for realizing the community service requirements is a main development direction of future community service robot resources, and the technology has a gap at present.

In view of the above problems, an effective technical solution is currently needed.

Disclosure of Invention

The embodiment of the application aims to provide a community robot intelligent coordination management and control method, a system and a readable storage medium, which can perform information acquisition and data processing on community services through big data and intelligent robot technology so as to optimize the allocation of a type robot, realize the function matching between the information according to the requirements of the community services and robot resources, enable the community robot resources to realize optimal allocation, and improve the intellectualization and the accuracy of the community robot management application.

The embodiment of the application also provides a community robot intelligent coordination control method, which comprises the following steps:

Collecting public service demand information and resident service demand information in communities, performing task quantity analysis on the service demand information to generate a task element list, and constructing a unit service list;

Performing task information data analysis according to the task element list and the unit service list, distributing service robots of corresponding categories according to the task information data, and generating a robot community task organization tree;

Carrying out robot task density statistics according to the robot community task organization tree, and generating community robot task data images according to a robot task density data set of a task period;

Extracting robot project service data according to the community robot task data image, and processing the robot project service data according to a preset robot task allocation model to obtain robot task response data;

Generating a robot task data instruction bar of a preset time period according to the robot task response data and the priority coefficient of the task information data;

generating a community robot task allocation list according to the robot task data instruction bar of each time period, allocating tasks to the robots according to the list, and generating task instructions.

Optionally, in the method for intelligently coordinating and controlling the community robot according to the embodiment of the present application, collecting public service demand information and resident service demand information in the community, performing task amount analysis on the service demand information to generate a task element list, and constructing a unit service list, including:

Respectively acquiring public service demand information and resident service demand information in communities;

extracting demand category information, service content information, demand duration information and service period demand information according to service demand information of public and households;

Carrying out information bar data analysis on the demand category information, the service content information, the demand duration information and the service period demand information to respectively obtain public service information bar data and resident service information bar data;

Generating a public service task element list and a resident service task element list according to the public service information strip data and the resident service information strip data;

And obtaining a unit service list according to the resident service task element list set of each unit resident.

Optionally, in the method for intelligently coordinating and controlling the community robots according to the embodiment of the present application, the task information data analysis is performed according to the task element list and the unit service list, service robots of corresponding categories are allocated according to the task information data, and a robot community task organization tree is generated, including:

Extracting service requirement information strips according to the public service task element list and the resident service task element list, and extracting service item data comprising service item data, item category data, service difficulty coefficients and service time data according to the service requirement information strips;

Carrying out service data analysis according to the service item data, the item category data, the service difficulty coefficient and the service time data to obtain task information data;

Obtaining unit task package data according to the task information data set of the unit resident corresponding to the unit service list;

comparing the task information data with a preset robot task allocation threshold value;

Service robot type distribution is carried out on each service requirement of public and households according to the threshold comparison range;

Generating a robot community task organization tree according to the service item data and task information data of public and households and corresponding service robot information;

the robot community task organization tree further comprises service robot information sets of each unit resident corresponding to the unit task package data.

Optionally, in the method for intelligently coordinating and controlling the community robots according to the embodiment of the present application, the performing robot task density statistics according to the robot community task organization tree, and generating a community robot task data image according to a robot task density dataset of a task period, includes:

Extracting robot task bar data of public households and households in each preset time period according to the robot community task organization tree;

according to the robot task bar data, the service difficulty coefficient and the service time data, the robot distribution number and the robot category coefficient of each task bar are combined to perform calculation processing, and the robot task density data in each preset time period are obtained;

Carrying out aggregation statistics according to the robot task density data and community service demand time to obtain a robot task density data set;

and generating a community robot task data image of a preset robot service period according to the robot task density data set.

Optionally, in the community robot intelligent coordination management and control method according to the embodiment of the present application, the extracting the robot project service data according to the community robot task data image, and processing the robot project service data according to a preset robot task allocation model to obtain robot task response data includes:

Extracting robot project service data according to the community robot task data image;

The robot project service data comprise robot task execution data, robot task quantity data, robot operation difficulty data and robot cooperation quantity of various service demand projects of public households and households;

And processing the robot task execution data, the robot task quantity data, the robot operation difficulty data and the robot cooperation quantity in a preset robot task allocation model to obtain robot task response data.

Optionally, in the community robot intelligent coordination control method according to the embodiment of the present application, the generating, according to the robot task response data, a robot task data command bar for a preset period of time in combination with a priority coefficient of the task information data includes:

Acquiring a corresponding priority coefficient of task information data;

Integrating the priority coefficient according to the robot task response data to obtain a robot task dispatching index;

and mapping the robot task dispatch index with the corresponding service requirement information bar to obtain a robot task data instruction bar of each preset time period.

Optionally, in the method for intelligently coordinating and controlling the community robots according to the embodiment of the present application, the generating a community robot task allocation list according to the robot task data command bar of each time period, performing task allocation on the robots according to the list, and generating task commands includes:

Sequencing according to preset requirements according to the robot task dispatching indexes of the robot task data instruction bars in each preset time period, and generating a community robot task allocation list;

task allocation is carried out on the robots according to the community robot task allocation list and the corresponding time period;

And generating a corresponding task instruction according to the allocation task of the community robot task allocation list and transmitting the task instruction to the robot.

In a second aspect, an embodiment of the present application provides a community robot intelligent coordination management and control system, including: the system comprises a memory and a processor, wherein the memory comprises a program of a community robot intelligent coordination control method, and the program of the community robot intelligent coordination control method realizes the following steps when being executed by the processor:

Optionally, in the intelligent coordination management and control system for a community robot according to the embodiment of the present application, the collecting public service requirement information and resident service requirement information in the community, performing task amount analysis on the service requirement information to generate a task element list, and constructing a unit service list includes:

In a third aspect, an embodiment of the present application further provides a computer readable storage medium, where the computer readable storage medium includes a community robot intelligent coordination control method program, where the community robot intelligent coordination control method program, when executed by a processor, implements the steps of the community robot intelligent coordination control method according to any one of the foregoing embodiments.

As can be seen from the above, according to the intelligent coordination control method, system and readable storage medium for community robots provided by the embodiments of the present application, task element lists are generated by performing task amount analysis on community service requirement information, performing task information data analysis, allocating robots of corresponding categories to generate a robot community task organization tree, counting to obtain task density data sets and generate community robot task data images, extracting robot project service data to process to obtain robot task response data, and then generating task allocation lists according to the generated time period robot task data command bars to allocate tasks to the robots; therefore, information acquisition and data processing are carried out on community services based on big data and intelligent robot technology so as to optimize allocation of type robots, function matching is carried out on the community service demand information and robot resources, optimal allocation of the community robot resources is achieved, and intelligence and accuracy of community robot management application are improved.

Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flowchart of a method for intelligent coordination control of a community robot provided by an embodiment of the application;

FIG. 2 is a flowchart of a method for intelligent coordination control of a community robot for generating a task element list and constructing a unit service list according to an embodiment of the present application;

FIG. 3 is a flowchart of a method for generating a robot community task organization tree for intelligent coordination control of a community robot, which is provided by an embodiment of the application;

fig. 4 is a schematic structural diagram of a community robot intelligent coordination management and control system according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.

It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.

Referring to fig. 1, fig. 1 is a flowchart of a community robot intelligent coordination control method according to some embodiments of the application. The intelligent coordination control method of the community robot is used in terminal equipment, such as computers, mobile phone terminals and the like. The intelligent coordination control method of the community robot comprises the following steps:

S101, collecting public service demand information and resident service demand information in communities, performing task quantity analysis on the service demand information to generate a task element list, and constructing a unit service list;

s102, analyzing task information data according to the task element list and the unit service list, distributing service robots of corresponding categories according to the task information data, and generating a robot community task organization tree;

s103, carrying out robot task density statistics according to the robot community task organization tree, and generating community robot task data images according to a robot task density data set of a task period;

S104, extracting robot project service data according to the community robot task data image, and processing the robot project service data according to a preset robot task allocation model to obtain robot task response data;

S105, generating a robot task data instruction bar of a preset time period according to the robot task response data and the priority coefficient of the task information data;

S106, generating a community robot task allocation list according to the robot task data instruction bar of each time period, allocating tasks to the robots according to the list, and generating task instructions.

It should be noted that, in order to realize comprehensive, adaptive and reasonable allocation management of public service demands of communities and individual service demands of households by utilizing various types of robot resources of communities, so as to adapt to community public services, and individual services of households such as cooking cleaning, child care, elderly care, purchasing and distribution, task information analysis is required to be performed on service demands of public and households, task element lists and unit service lists are established according to information content, task data analysis is performed on the lists to define information such as types, duration, content, difficulty and the like of service tasks, corresponding service robots are matched according to service task data, then a robot community task organization tree is generated according to community service task data information and corresponding matched robot information, so as to define the data detail conditions of community service content and robot resources, carrying out robot task density statistics according to an organization tree to obtain demand change of community service robot resources in different time periods and time period demand density conditions, generating community robot task data portraits according to a density data set of task time periods, reflecting conditions of robot use type quantity distribution, use frequency, robot demand distribution and the like in community task time, extracting robot project service data, processing according to a preset robot task allocation model to obtain robot task response data, namely response allocation conditions of demands of the community service robot, cleaning demand information, screening important and secondary, urgent and non-urgent robot demand tasks, and generating a robot task data instruction bar in the preset time period by combining priority coefficients of task information data, the command strip effectively evaluates the requirements of the robots to generate effective task commands in each period, screens out invalid or abnormal or non-important urgent robot requirements, generates a community robot task allocation list according to the robot task data command strip in each period, allocates tasks to the robots and generates task commands, so that robot resources are effectively, maximally and preferentially allocated and applied, optimal allocation of community robot resources is realized, and the community robot management application is intelligent and accurate.

Referring to fig. 2, fig. 2 is a flowchart illustrating a method for intelligent coordination and control of a community robot to generate a task element list and construct a unit service list according to some embodiments of the present application. According to the embodiment of the application, the public service demand information and the resident service demand information in the community are collected, task quantity analysis is carried out on the service demand information to generate a task element list, and a unit service list is constructed, specifically:

s201, respectively acquiring public service demand information and resident service demand information in communities;

s202, extracting demand category information, service content information, demand duration information and service period demand information according to service demand information of public and households;

s203, carrying out information bar data analysis on the demand category information, the service content information, the demand duration information and the service period demand information to respectively obtain public service information bar data and resident service information bar data;

s204, respectively and correspondingly generating a public service task element list and a resident service task element list according to the public service information strip data and the resident service information strip data;

s205, obtaining a unit service list according to the resident service task element list set of each unit resident.

It should be noted that, for better realizing resource allocation and management of the community robot, firstly, the requirements of public service and resident service in the community are required to be clarified, the requirement category information, service content information, requirement duration information and service period requirement information are extracted according to the collected service requirement information of the public and resident, then information strip data analysis is performed according to the information, namely, data extraction is performed on each piece of service requirement information, such as community sanitation, and information data of daily child care, cooking clean service content, service duration and execution time period of the resident are extracted, and then a service task element list is generated according to the service information strip data corresponding to the service requirement information, wherein the service task element list comprises element data such as content, time, duration and difficulty of each piece of service requirement information and service item.

Referring to fig. 3, fig. 3 is a flowchart of a method for generating a robot community task organization tree according to an intelligent coordination control method of a community robot according to some embodiments of the present application. According to the embodiment of the application, task information data analysis is performed according to the task element list and the unit service list, service robots of corresponding categories are allocated according to the task information data, and a robot community task organization tree is generated, specifically:

S301, extracting service requirement information strips according to the public service task element list and the resident service task element list, and extracting service item data comprising service item data, item category data, service difficulty coefficients and service time data according to the service requirement information strips;

s302, analyzing service data according to the service item data, the item category data, the service difficulty coefficient and the service time data to obtain task information data;

S303, obtaining unit task package data according to a task information data set of a unit resident corresponding to the unit service list;

s304, comparing the task information data with a preset robot task allocation threshold value;

S305, carrying out service robot type distribution on various service requirements of public and households according to a threshold comparison range;

s306, generating a robot community task organization tree according to the service item data and task information data of public and households and corresponding service robot information;

s307, the robot community task organization tree further comprises service robot information sets of each unit resident corresponding to the unit task package data.

It should be noted that, in order to obtain the robot type information matched with public service or household service, so as to determine the requirement condition of robot resources, extract service requirement information according to public and household service task element list, namely each item information of the service requirement of the robot, extract service item data according to the service requirement information, analyze according to service data analysis program to obtain task information data reflecting the evaluation data of the task information, wherein the task information data of each household unit is collected into unit task package data, namely the whole service requirement data reflecting a certain household in a certain preset time period, the task information data is threshold value compared with the preset robot task allocation threshold value, and the matched robot types are obtained according to the corresponding matching of the threshold value comparison range, in this embodiment, the community service robots are divided into I guide illumination robots, II intelligent strain robots and III qualitative task robots, the corresponding task allocation threshold value ranges of the three robots are respectively corresponding to I (0.7,1), II corresponds to [0,0.35], if the household unit task information data of each household is collected into unit task package data, i.e.3, 0.7 corresponds to the household unit is collected into the unit task information corresponding to the household tree, the public service task is further corresponding to the task tree robot, the community service information is generated by the cleaning robot, and the community service request is further corresponding to the task information is corresponding to the public robot, the task tree-based on the task information, the task information is matched with the task information, and the community is clearly organized according to the task information, and the community is clear, and the service information is a user-based on the task, namely, the demand condition of the whole robot of each resident in a preset time period; the service data analysis program for obtaining the task information data comprises the following steps: r _s＝ρ_f (ηJ+γK+δT); wherein R _s is task information data, ρ _f is service difficulty coefficient, J is service item data, K is item class data, T is service time data, η, γ and δ are preset coefficients (obtained by inquiring a preset community robot service management platform).

According to the embodiment of the invention, the robot task density statistics is performed according to the robot community task organization tree, and a community robot task data image is generated according to a robot task density data set of a task period, specifically:

In order to evaluate and optimize the robot resource allocation situation of each service requirement, a community robot task data image of a community robot resource requirement frequency and a requirement distribution situation is required to be obtained so as to further judge and evaluate, according to a robot community task organization tree, the robot task bar data of public and households in each preset time period, namely, task item data matched with robots in each time period are extracted, then calculation processing is carried out by combining the service difficulty coefficient and service time data with the robot allocation quantity and the robot category coefficient of each task bar, so as to obtain the robot task density data in each preset time period, aggregation statistics is carried out according to the robot task density data and community service requirement time so as to obtain a robot task density data set, finally, community robot task data images of preset robot service time periods are generated, the robot task density statistics is realized, the requirement quantity change of community service robot resources in different time periods and the time period requirement density situation are reflected, and the task data image reflects the conditions such as the quantity distribution of the use types, the use frequency, the robot requirement quantity distribution and the like in the community task time;

The calculation program formula of the robot task density data is as follows:

Wherein, P _m is the robot task density data, S _ei is the robot task bar data in the ith preset time period, T _i is the service time data in the ith preset time period, ρ _f is the service difficulty coefficient, ν is the robot identification coefficient, N _ei is the robot distribution number in the ith preset time period, and N is the preset time period number.

According to the embodiment of the invention, the robot project service data is extracted according to the community robot task data image, and the robot project service data is processed according to a preset robot task allocation model to obtain the robot task response data, specifically:

It is to be noted that, each item of data in the extracted robot project service data is processed in a preset robot task allocation model to obtain robot task response data, the response data reflects allocation response conditions for overall allocation of community service robot requirements, so as to clean and screen out community requirement information according to the task response data, remove unnecessary or abnormal or invalid robot requirement information, and realize optimization of community robot resource utilization;

The method for performing program calculation on the robot task response data through the robot task allocation model comprises the following steps:

B₀＝λM_σ+ζU_d+μG_Fc/ρ_f；

wherein B ₀ is robot task response data, M _σ is robot task execution data, U _d is robot task amount data, G _F is robot operation difficulty data, c is robot cooperative quantity, lambda, Μ is a preset coefficient (obtained by querying a preset community robot service management platform).

According to the embodiment of the invention, the robot task data instruction bar of a preset time period is generated according to the robot task response data and the priority coefficient of the task information data, specifically:

Acquiring a corresponding priority coefficient of task information data;

It should be noted that, multiplication is performed according to a preset priority coefficient corresponding to task information data and combining with robot task response data to obtain a robot task dispatching index, mapping is performed with a corresponding service requirement information strip to generate a robot task data instruction strip of each preset time period, the instruction strip and the robot task dispatching index are used for reflecting the evaluation of the effectiveness, importance and necessity of task dispatching on the robot service requirement, and cleaning and screening invalid or unnecessary or abnormal robot service requirement information can be performed to optimize the utilization rate of community robot resources.

According to the embodiment of the invention, a community robot task allocation list is generated according to the robot task data instruction bar of each time period, and the task allocation is carried out on the robot according to the list and a task instruction is generated, specifically:

It should be noted that, in order to achieve the priority of response dispatch of the service requirements of the community robots, the robot task dispatch indexes corresponding to the robot task data instruction bars in each preset time period are ordered according to the preset requirements, so as to generate a community robot task allocation list, the ordering of the allocation list is the allocation ordering of the robot tasks in the corresponding time period, the allocation tasks of the allocation list are used for generating corresponding task instructions and transmitting the corresponding task instructions to the robots, so that the optimal allocation of the community robot resources is achieved, and the accuracy of the community robot resource management application is improved.

According to an embodiment of the present invention, further comprising:

Acquiring dynamic characteristic data of a robot executing community service tasks in real time;

calibrating according to the dynamic characteristic data and the robot task response data to obtain robot performance dynamic identification data;

comparing the dynamic robot performance identification data with a preset robot demand performance identification value corresponding to a service task;

Judging whether the robot executing the task meets the service requirement of the service task or not through the comparison of the identification values;

If the service requirement is met, not triggering task forwarding response;

if the service requirement cannot be met, triggering task dispatch response, and carrying out proportional correction according to the residual task quantity data and the task information data executed by the robot to obtain residual task information data;

And carrying out threshold comparison according to the residual task information data and a preset robot task allocation threshold value, and selecting a robot meeting the threshold comparison requirement to carry out task transfer.

It should be noted that, for monitoring the state of the service task executed by the dispatched robot in real time, to ensure that the robot has no abnormality in the execution command, and to ensure the use effect and efficiency of the robot by the user, monitor and evaluate the performance state of the robot by collecting the dynamic characteristic data of the robot for executing the task in real time, calibrate and correct the dynamic characteristic data and the response data of the robot task to obtain the dynamic performance identification data of the robot, compare the dynamic performance identification data with the preset performance identification value corresponding to the service task, judge whether the robot for executing the task meets the service requirement of the service task by comparing the identification values, if the service requirement is met, the task dispatch response is not triggered, otherwise, the task dispatch response is triggered, the residual task information data is obtained by proportional correction of the residual task quantity data executed by the robot and the task information data, and then the task allocation threshold value of the preset robot is compared with the threshold value, for task dispatch is selected for task dispatch by comparing the robot with the threshold value, for example, if the residual task information data of a certain model X is 45%, the residual task information data of the robot is 45% is corrected according to the preset task allocation threshold value, and the task performance of the robot is compared with the task allocation threshold value, and the task performance is continuously performed by comparing the task performance of the robot with the task is met, if the task performance is met, and the task performance is continuously met, and the task performance is compared with the task performance is required by the task is continuously.

According to an embodiment of the present invention, further comprising:

Performing dynamic self-checking on a robot executing community service tasks;

Acquiring real-time task execution information and performance state information of the robot;

judging whether the task execution information meets service inspection standard data of service demand information or not;

If not, a recall instruction is sent to the robot for recall;

judging whether the residual performance state information obtained by making a difference between the preset performance state data and the state data corresponding to the performance state information of the robot meets the residual operation information of the service demand information;

If not, a recall instruction is sent to the robot for recall.

It should be noted that, to monitor the performance state of the robot to dynamically evaluate whether the robot can successfully continue to execute the task, by dynamically self-checking the robot executing the community service task and acquiring the real-time task execution information and performance state information of the robot, respectively judging the task execution information and the performance state information, judging whether the task execution information meets the service inspection standard data of the service requirement information, identifying whether to send a recall instruction, and according to the difference between the state data corresponding to the preset state data of the robot and the performance state information, obtaining the residual performance state information, judging whether to meet the residual operation information of the service requirement information, if not, sending a recall instruction to recall the robot, for example, if the task execution information data of a certain robot Z is lower than 80% of the preset value of the service inspection standard data, then recall the robot Z is needed; and if the residual performance state information of the certain robot A is not lower than the 90% preset value of the minimum required value of the residual job information, the robot A can continue to execute the task without recall.

As shown in fig. 4, the invention also discloses a community robot intelligent coordination control system, which comprises a memory 41 and a processor 42, wherein the memory comprises a community robot intelligent coordination control method program, and the community robot intelligent coordination control method program when executed by the processor realizes the following steps:

In order to realize comprehensive, adaptive and reasonable allocation management of public service demands of communities and individual service demands of households by utilizing various robot resources of communities, so as to adapt to community public services such as material distribution, community sanitation and the like, and individual services of households such as cooking cleaning, child care, aged care, purchasing distribution and the like, task information analysis is required to be carried out on the service demands of the public and households, a task element list and a unit service list are established according to information content, task data analysis is carried out on the list so as to define information such as types, duration, content and difficulty of service tasks, corresponding service robots are matched according to service task data, a robot community task organization tree is generated according to community service task data information and corresponding matched robot information so as to define the data detail condition of community service content and robot resources, carrying out robot task density statistics according to an organization tree to obtain demand change of community service robot resources in different time periods and time period demand density conditions, generating community robot task data portraits according to a density data set of task time periods, reflecting conditions of robot use type quantity distribution, use frequency, robot demand distribution and the like in community task time, extracting robot project service data, processing according to a preset robot task allocation model to obtain robot task response data, namely response allocation conditions of demands of the community service robot, cleaning demand information, screening important and secondary, urgent and non-urgent robot demand tasks, and generating a robot task data instruction bar in the preset time period by combining priority coefficients of task information data, the command strip effectively evaluates the requirements of the robots to generate effective task commands in each period, screens out invalid or abnormal or non-important urgent robot requirements, generates a community robot task allocation list according to the robot task data command strip in each period, allocates tasks to the robots and generates task commands, so that robot resources are effectively, maximally and preferentially allocated and applied, optimal allocation of community robot resources is realized, and the community robot management application is intelligent and accurate.

According to the embodiment of the invention, the public service demand information and the resident service demand information in the community are collected, task quantity analysis is carried out on the service demand information to generate a task element list, and a unit service list is constructed, specifically:

According to the embodiment of the invention, task information data analysis is performed according to the task element list and the unit service list, service robots of corresponding categories are allocated according to the task information data, and a robot community task organization tree is generated, specifically:

The calculation program formula of the robot task density data is as follows:

Acquiring a corresponding priority coefficient of task information data;

According to an embodiment of the present invention, further comprising:

If the service requirement is met, not triggering task forwarding response;

According to an embodiment of the present invention, further comprising:

Performing dynamic self-checking on a robot executing community service tasks;

If not, a recall instruction is sent to the robot for recall;

If not, a recall instruction is sent to the robot for recall.

A third aspect of the present invention provides a readable storage medium, where the readable storage medium includes a community robot intelligent coordination control method program, where the community robot intelligent coordination control method program, when executed by a processor, implements the steps of the community robot intelligent coordination control method according to any one of the above.

The invention discloses a community robot intelligent coordination control method, a system and a readable storage medium, which are characterized in that task element lists are generated by analyzing task quantity of community service demand information, task information data are analyzed, robots of corresponding types are distributed to generate a robot community task organization tree, task density data sets are obtained through statistics and community robot task data images are generated, then robot project service data are extracted and processed to obtain robot task response data, and then task allocation lists are generated according to robot task data instruction bars in a generated time period to allocate tasks for robots; therefore, information acquisition and data processing are carried out on community services based on big data and intelligent robot technology so as to optimize allocation of type robots, function matching is carried out on the community service demand information and robot resources, optimal allocation of the community robot resources is achieved, and intelligence and accuracy of community robot management application are improved.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.

The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or optical disk, or the like, which can store program codes.

Or the above-described integrated units of the invention may be stored in a readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.

Claims

1. The community robot coordination control method is characterized by comprising the following steps of:

Generating a community robot task allocation list according to the robot task data instruction bar of each time period, allocating tasks to the robots according to the list and generating task instructions;

The task information data analysis is performed according to the task element list and the unit service list, service robots of corresponding categories are distributed according to the task information data, and a robot community task organization tree is generated, and the task information data analysis method comprises the following steps:

The robot community task organization tree further comprises a service robot information set of each unit resident corresponding to the unit task package data;

the service data analysis program for obtaining the task information data comprises the following steps: ; wherein, For task information data,/>Is a service difficulty coefficient,/>For service item data,/>For item category data,/>For service time data,/>、/>、/>Is a preset coefficient.

2. The method for coordinated management and control of a community robot according to claim 1, wherein the collecting public service requirement information and resident service requirement information in the community, performing task amount analysis on the service requirement information to generate a task element list, and constructing a unit service list, includes:

3. The method for coordinated management and control of a community robot according to claim 2, wherein the performing robot task density statistics according to the robot community task organization tree and generating a community robot task data image according to a robot task density data set of a task period comprises:

4. The method for coordinated management and control of a community robot according to claim 3, wherein the extracting the robot project service data according to the community robot task data image and processing the robot project service data according to a preset robot task deployment model to obtain the robot task response data comprises:

5. The method for coordinated control of a community robot according to claim 4, wherein the generating a robot task data command bar for a preset period of time according to the robot task response data in combination with the priority coefficient of the task information data comprises:

Acquiring a corresponding priority coefficient of task information data;

6. The method for coordinated management and control of a community robot according to claim 5, wherein generating a community robot task allocation list according to the robot task data command bar of each time period, performing task allocation on a robot according to the list, and generating a task command, comprises:

7. A community robot coordination management and control system, the system comprising: the system comprises a memory and a processor, wherein the memory comprises a program of a community robot coordination control method, and the program of the community robot coordination control method realizes the following steps when being executed by the processor:

8. The system of claim 7, wherein the collecting the public service requirement information and the resident service requirement information in the community, performing task volume analysis on the service requirement information to generate a task element list, and constructing a unit service list, comprises:

9. A computer readable storage medium, wherein a community robot coordination control method program is included in the computer readable storage medium, and when the community robot coordination control method program is executed by a processor, the steps of the community robot coordination control method according to any one of claims 1 to 6 are implemented.