CN115860366A

CN115860366A - Community robot intelligent coordination control method and system and readable storage medium

Info

Publication number: CN115860366A
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: 2023-03-28
Anticipated expiration: 2042-11-17
Also published as: CN115860366B

Abstract

The embodiment of the application provides a community robot intelligent coordination control method and 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, allocating robots of corresponding categories to generate a robot community task organization tree, performing statistics to obtain a task density data set and generate a community robot task data image, extracting robot project service data to process to obtain robot task response data, and then generating a task allocation list according to a robot task data instruction bar in a generated time period to allocate tasks for the robots; therefore, based on big data and intelligent robot technology, information acquisition and data processing are carried out on community service to optimize the distribution of the type robot, the purpose matching is carried out on the community service demand information and robot resources, the optimal distribution of the community robot resources is achieved, and the intellectualization and the accuracy of community robot management application are improved.

Description

Community robot intelligent coordination control method and system and readable storage medium

Technical Field

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

Background

At present, the development of the robot technology is rapid, the application of the robot is widened to the aspects of production and living, the research and development and the application of household small and miniature multifunctional robots and community robots are more and more extensive, but the development and the application of community robot service resources aiming at the whole field, the whole system and the whole dimension of community service are weak, and the robot management application technology and the allocation system which can be adapted to the requirements of multiple functions of communities and users are lacked, for example, the scientific management and the allocation of the community robot resources for caring, cooking and cleaning, epidemic prevention and distribution service of the elderly and children living alone are realized, and the community robot service resources do not have a comprehensive, multi-system and multi-dimension scientific management system at present.

Therefore, how to establish a comprehensive, multi-directional and systematic robot resource intelligent management application technology and system capable of meeting the community service requirements is a main development direction of the community service robot resources in the future, and the technology is vacant at present.

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

Disclosure of Invention

An object of the embodiment of the application is to provide a management and control method, a system and a readable storage medium for intelligent coordination of community robots, which can perform information acquisition and data processing on community services through big data and intelligent robot technology to optimize the distribution of the type robots, realize function matching with robot resources according to community service demand information, realize optimal distribution of community robot resources, and improve the intelligence and accuracy of management and application of the community robots.

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

collecting public service demand information and resident service demand information in a community, carrying out task quantity analysis on the service demand information to generate a task element list, and constructing a unit service list;

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;

carrying out 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 in a task time 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 strip in a preset time period according to the robot task response data and the priority coefficient of the task information data;

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

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

respectively collecting public service demand information and resident service demand information in a community;

extracting requirement category information, service content information, requirement duration information and service time interval requirement information according to the service requirement information of the public and residents;

carrying out information piece data analysis on the demand type information, the service content information, the demand duration information and the service time interval demand information to respectively obtain public service information piece data and household service information piece data;

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

and acquiring a unit service list according to the resident service task element list set of each unit resident.

Optionally, in the method for intelligent coordination and management and control of community robots according to the embodiment of the present application, the analyzing task information data according to the task element list and the unit service list, allocating service robots of corresponding categories according to the task information data, and generating a robot community task organization tree includes:

extracting service requirement information pieces according to the public service task element list and the resident service task element list, and extracting service item data according to the service requirement information pieces, wherein the service item data comprises service item data, item category data, a service difficulty coefficient and service time data;

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;

acquiring unit task packet data according to a task information data set of a unit resident corresponding to the unit service list;

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

performing service robot type distribution on various service requirements of the public and residents according to the threshold comparison range;

generating a robot community task organization tree according to the service project data and the task information data of the public and the residents in combination with the corresponding service robot information;

the robot community task organization tree further comprises a service robot information set of each unit household corresponding to the unit task package data.

Optionally, in the method for intelligently coordinating and controlling a community robot 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 data set at a task time interval includes:

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

calculating according to the robot task bar data, the service difficulty coefficient and the service time data and the robot distribution quantity and the robot category coefficient of each task bar to obtain robot task density data in each preset time period;

performing 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 method for managing and controlling intelligent coordination of community robots in an embodiment of the present application, the 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 deployment 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 comprises robot task execution data, robot task quantity data, robot operation difficulty data and robot cooperation quantity of all service requirement projects of public and residents;

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 management and control method according to the embodiment of the present application, the generating a robot task data instruction strip of a preset time period according to the robot task response data in combination with the priority coefficient of the task information data includes:

acquiring a corresponding priority coefficient of the task information data;

performing product calculation according to the robot task response data and the priority coefficient to obtain a robot task dispatching index;

and mapping the robot task dispatching index and the corresponding service requirement information strip to obtain a robot task data instruction strip in each preset time period.

Optionally, in the method for managing and controlling intelligent coordination of community robots in an embodiment of the present application, the generating a community robot task allocation list according to the robot task data instruction bars in each time period, performing task allocation on the robots according to the list, and generating task instructions includes:

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

carrying out task allocation on the robots according to corresponding time periods according to the community robot task allocation list;

and generating a corresponding task instruction according to the allocation tasks of the community robot task allocation list and transmitting the corresponding 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 intelligent community robot coordination control method comprises a memory and a processor, wherein the memory comprises a program of the intelligent community robot coordination control method, and the program of the intelligent community robot coordination control method realizes the following steps when executed by the processor:

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 in a task period;

Optionally, in the system for managing and controlling intelligent coordination of community robots in the embodiment of the present application, the method includes collecting public service demand information and resident service demand information in a community, analyzing task quantity of the service demand information to generate a task element list, and constructing a unit service list, including:

extracting requirement category information, service content information, requirement duration information and service time interval requirement information according to service requirement information of public and residents;

and acquiring a unit service list according to the household service task element list set of each unit household.

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 program of a community robot intelligent coordination control method, and when the program of the community robot intelligent coordination control method is executed by a processor, the method implements the steps of the community robot intelligent coordination control method as described in any one of the above.

According to the method, the system and the readable storage medium for intelligent coordination management and control of the community robot, provided by the embodiment of the application, the community service demand information is subjected to task quantity analysis to generate the task element list, the task information data is analyzed, the corresponding type of robot is distributed to generate the community task organization tree of the robot, then the task density data set is obtained through statistics, the community robot task data picture is generated, the robot project service data is extracted to be processed, the robot task response data is obtained, and then the task allocation list is generated according to the robot task data instruction bar in the generated time period to allocate tasks for the robot; therefore, based on big data and intelligent robot technology, information acquisition and data processing are carried out on community service to optimize the distribution of the type robot, the purpose matching is carried out on the community service demand information and robot resources, the optimal distribution of the community robot resources is achieved, and the intellectualization and the accuracy of community robot management application are improved.

Additional features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof 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 required to be used 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 therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.

Fig. 1 is a flowchart of a community robot intelligent coordination control method according to an embodiment of the present disclosure;

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

fig. 3 is a flowchart of generating a robot community task organization tree in the community robot intelligent coordination management and control method according to the embodiment of the present 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 disclosure.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection 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, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.

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

s101, collecting public service demand information and resident service demand information in a community, 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 a community robot task data image according to a robot task density data set in a task time 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 strip in a preset time period according to the robot task response data and the priority coefficient of the task information data;

and S106, generating a community robot task allocation list according to the robot task data instruction bars in all time periods, performing task allocation on the robots according to the list and generating task instructions.

It is to be noted that, in order to realize comprehensive, adaptive and reasonable allocation management of community public service demands and resident individual service demands by using various types of robot resources in the community to adapt to community public services and resident individual services such as cooking cleaning, child care, old person nursing, purchasing delivery and the like, it is necessary to analyze task information of the public and resident service demands, establish a task element list and a unit service list according to information contents, analyze task data in the list to clarify information such as the kind, duration, content, difficulty and the like of service tasks, match corresponding service robots according to service task data, generate a robot community task organization tree according to community service task data information and corresponding matched robot information to clarify detailed data conditions of community service contents and robot resources, perform robot task density statistics according to the organization tree to obtain required quantity changes and time interval required density conditions of the service robot resources in different time intervals, generate community robot task data according to a set of community service task density data to reflect the data types of community use frequency images, extract effective task data of robot resources in the community, extract important robot data of robot service data, and perform task allocation on the robot task data of robot demand and task data of robot, and perform effective task data processing on the robot response to the robot data of the robot and task data of the robot. The method comprises the steps of screening out invalid or abnormal or non-important urgent robot demands, generating a community robot task allocation list according to robot task data instruction bars of all time periods, allocating tasks to the robots and generating task instructions, enabling the robot resources to be effectively, maximally and definitely allocated and applied, achieving optimal allocation of the community robot resources, and achieving intellectualization and precision of community robot management application.

Referring to fig. 2, fig. 2 is a flowchart illustrating a method for intelligently coordinating and controlling community robots 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 invention, the public service demand information and the resident service demand information in the community are collected, the task quantity of the service demand information is analyzed to generate the task element list, and the unit service list is constructed, which specifically comprises the following steps:

s201, respectively collecting public service demand information and resident service demand information in a community;

s202, extracting requirement category information, service content information, requirement duration information and service time interval requirement information according to service requirement information of public and residents;

s203, analyzing information data of the demand type information, the service content information, the demand duration information and the service time interval demand information to respectively obtain public service information data and household service information 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 data and the resident service information data;

and S205, acquiring a unit service list according to the household service task element list set of each unit household.

It should be noted that, in order to better implement resource allocation and management of the community robot, first, the demand condition of the public service and each resident service in the community needs to be clarified, the demand category information, the service content information, the demand duration information and the service time interval demand information are extracted according to the collected public and resident service demand information, then, information data analysis is performed according to the information, that is, data extraction is performed on each piece of service demand information, for example, information data of the community sanitation, the daily child care, clean meal making service content, the service duration and the execution time interval of the resident is extracted, and then, a service task element list is generated according to the correspondence between the service information piece data and the service demand information, wherein the service task element list comprises the service demand information and the element data of the content, time, duration, difficulty and the like of the service items.

Referring to fig. 3, fig. 3 is a flowchart illustrating a method for intelligently coordinating and controlling community robots to generate a robot community task organization tree according to some embodiments of the present application. According to the embodiment of the invention, the task information data analysis is performed according to the task element list and the unit service list, the service robots of corresponding categories are distributed according to the task information data, and a robot community task organization tree is generated, specifically:

s301, extracting service requirement information pieces according to the public service task element list and the resident service task element list, and extracting service item data according to the service requirement information pieces, wherein the service item data comprises service item data, item category data, a service difficulty coefficient and service time data;

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, acquiring unit task packet data according to the task information data set of the unit resident corresponding to the unit service list;

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

s305, performing service robot type distribution on various service requirements of the public and residents according to the threshold comparison range;

s306, generating a robot community task organization tree according to the service project data and the task information data of the public and the residents in combination with corresponding service robot information;

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

It should be noted that, in order to obtain robot type information matched with public service or household service so as to clarify the requirement condition of robot resources, service requirement information bars, i.e. item information of each item required for robot service, are extracted according to the service requirement information bars, and then service project data are extracted according to the service data analysis program, and then task information data are obtained by analyzing according to the service data analysis program, and the task information data reflect the evaluation data of the task information, wherein the task information data of each household unit are aggregated into unit task packet data, i.e. reflect the integral service requirement data of a certain household in a certain preset time period, and then threshold value comparison is performed between the task information data and the preset robot task allocation threshold value, and according to the robot type allocation of which the threshold value comparison belongs to the corresponding matched service requirements, the matched robot type is obtained, in this embodiment, the service community robots are divided into I-guided care robots, II intelligent strain robots and III qualitative task robots, and the corresponding task allocation threshold value ranges of the three types of robots are I-correspond (0.7,1) respectively (3242 zxft)]II corresponds to (0.3,0.7)]III corresponds to [0,0.35]E.g. for cooking clean by a residentIf the threshold value of the task information data is 0.63, the cooking cleaning service project allocation robot is an intelligent strain robot II; generating a robot community task organization tree according to service project data and task information data of the public and the residents and combining corresponding service robot information, wherein the organization tree defines service contents of the public and the residents in the community and information and data details of corresponding robot resources, and simultaneously comprises a service robot information set of each unit resident, namely the whole robot demand condition 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 (η J + γ K + δ T); wherein R is _s For task information data, p _f And J is service item data, K is item category data, T is service time data, and eta, gamma and delta are preset coefficients (obtained by inquiring through a preset community robot service management platform).

According to the embodiment of the invention, the robot task density statistics is carried out according to the robot community task organization tree, and the community robot task data portraits are generated according to the robot task density data sets in the task time period, which specifically comprises the following steps:

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

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

The method comprises the steps that for evaluating and optimizing robot resource distribution conditions of service requirements, community robot task data portraits of demand frequency and demand distribution conditions of the community robot resource requirements are required to be obtained so as to be further judged and evaluated, robot task bar data of public and residents in each preset time period are extracted according to a robot community task organization tree, namely task item data matched with robots in each time period are calculated and processed by combining service difficulty coefficients and service time data with robot distribution quantity and robot category coefficients of each task bar, robot task density data in each preset time period are obtained, a robot task density data set is obtained by carrying out aggregation statistics according to the robot task density data and community service demand time, and finally, the community robot task data portraits of preset robot service time periods are generated, so that the robot task density statistics is realized, the demand quantity change and period demand density portraits conditions of the community service robot resources in different time periods are reflected, and the robot use type quantity distribution, use frequency, robot demand distribution conditions and the like in the community task data within the task time period are reflected by the task data;

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

/>

wherein, P _m For robot task density data, S _ei Data of a task bar of the robot in the ith preset time period, T _i For service time data, rho, in the ith preset time period _f V is a robot-to-robot coefficient, N _ei And distributing the number of the robots in the ith preset time period, wherein n is the number of the preset time periods.

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

The method includes the steps that various items of data in extracted robot project service data are processed in a preset robot task allocation model to obtain robot task response data, the response data reflect distribution response conditions of overall distribution of community service robot requirements, community requirement information is cleaned and screened out according to the task response data, unnecessary or abnormal or invalid robot requirement information is removed, and optimization of community robot resource utilization is achieved;

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

B ₀ ＝λM _σ +ζU _d +μG _F c/ρ _f ；

wherein, B ₀ Responding data for a robot task, M _σ Performing data for robot tasks, U _d For robot task volume data, G _F C is the robot cooperation number, lambda, B,

Mu is a preset coefficient (obtained by inquiring through a preset community robot service management platform).

According to the embodiment of the invention, the generating of the robot task data instruction strip in the preset time period according to the robot task response data and the priority coefficient of the task information data specifically comprises:

acquiring a corresponding priority coefficient of the task information data;

The method includes the steps of multiplying by combining robot task response data according to a preset priority coefficient corresponding to task information data to obtain a robot task dispatching index, mapping the robot task dispatching index with a corresponding service requirement information bar to generate a robot task data instruction bar in each preset time period, wherein the instruction bar and the robot task dispatching index reflect evaluation of effectiveness, importance and necessity of task dispatching on robot service demands, invalid or unnecessary or abnormal robot service demand information can be cleaned and screened, and utilization rate of community robot resources is optimized.

According to the embodiment of the invention, the generating of the community robot task allocation list according to the robot task data instruction strip of each time period, the task allocation of the robot according to the list and the generation of the task instruction specifically comprise:

according to the community robot task allocation list, allocating tasks to the robots according to corresponding time periods;

It should be noted that, in order to implement the priority of dispatching in response to the service requirements of the community robots, the robot task dispatching indexes corresponding to the robot task data instruction bars in each preset time period are sorted according to preset requirements to generate a community robot task dispatching list, the sorting of the dispatching list is the robot task dispatching sorting of the corresponding time period, corresponding task instructions are generated according to the dispatching tasks of the dispatching list and transmitted to the robots, so that the optimal distribution of community robot resources is achieved, and the accuracy of community robot resource management application is improved.

According to the embodiment of the invention, the method further comprises the following steps:

acquiring dynamic characteristic data of a robot executing a community service task 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 robot performance dynamic identification data with a preset robot required performance identification value corresponding to the service task;

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

if the service requirement is met, not triggering task dispatching response;

if the service requirements cannot be met, triggering task dispatching response, and performing proportion correction according to the residual task amount data and the task information data executed by the robot to obtain residual task information data;

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

The method includes the steps of monitoring the state of a dispatched robot executing a service task in real time to ensure that the robot is free from abnormality in an execution command and ensure the use effect and efficiency of the robot of a user, monitoring and evaluating the performance state of the robot executing the task by acquiring dynamic characteristic data of the robot executing the task in real time, calibrating and correcting the dynamic characteristic data and robot task response data to obtain dynamic robot performance identification data, comparing the dynamic characteristic data with a preset robot requirement performance identification value corresponding to the service task, judging whether the robot executing the task meets the service requirement of the service task or not by comparing the identification values, if the service requirement is met, not triggering task dispatching response, otherwise triggering task dispatching response, performing proportional correction according to the residual task amount data and task information data executed by the robot to obtain residual task information data, comparing the residual task information data with a preset robot task allocation threshold value to select the robot meeting the threshold value comparison requirement to perform task dispatching, for example, if the dynamic performance identification data of a model robot X is smaller than the requirement performance identification value, performing threshold value comparison according to 45% of the residual task amount data executed by the robot, performing task dispatching task, and displaying the residual task information, and performing task dispatching if the residual task is 45%, and the task is continued.

carrying out dynamic self-inspection on a robot executing a community service task;

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;

if not, sending a recall instruction to the robot for recall;

judging whether the residual performance state information obtained by subtracting the preset robot performance state data from the corresponding state data of the performance state information meets the residual operation information of the service demand information or not;

and if not, sending a recall instruction to the robot for recall.

It should be noted that, in order to monitor the performance state of the robot itself, to dynamically evaluate whether the robot can continue to execute the task smoothly, the robot executing the community service task is dynamically self-checked, and real-time task execution information and performance state information of the robot are obtained, the task execution information and the performance state information are respectively judged, whether the task execution information meets the service inspection standard data of the service requirement information is judged, whether a recall instruction is sent out or not, and whether the residual performance state information meets the residual operation information of the service requirement information is judged according to the difference between the preset state data of the robot performance and the corresponding state data of the performance state information, if the residual operation information does not meet the service requirement information, a recall instruction is sent out 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, the robot Z needs to be recalled; and if the residual performance state information of the certain robot A is not lower than 90% of the preset value of the lowest required value of the residual operation information, the robot A can continue to execute the task without recalling.

As shown in fig. 4, the present invention further discloses a community robot intelligent coordination management and control system, which includes a memory 41 and a processor 42, wherein the memory includes a community robot intelligent coordination management and control method program, and when the community robot intelligent coordination management and control method program is executed by the processor, the following steps are implemented:

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

and generating a community robot task allocation list according to the robot task data instruction bars in all time periods, and performing task allocation on the robots according to the list and generating task instructions.

It is to be noted that, in order to realize comprehensive, adaptive and reasonable allocation management of public service requirements of communities and individual service requirements of residents by using various types of robot resources of communities to adapt to community public services such as material distribution, community sanitation and the like, and individual services of residents such as cooking cleanness, child care, old people nursing, purchasing distribution and the like, task information analysis is required to be carried out on the service requirements of the public and residents, a task element list and a unit service list are established according to information content, then task data analysis is carried out on the list to clarify information such as the type, duration, content, difficulty and the like of service tasks, corresponding service robots are matched according to service task data, a robot task organization tree is generated according to community service data information and corresponding matched robot information to clarify detailed conditions of data of community service content and robot resources, robot task density statistics is carried out according to the organization tree, demand variation and time period demand density conditions of community service robot resources in different time periods are obtained, robot service data collection of communities is generated according to density data of community service data of communities, robot task data, usage frequency of robot service data collection of communities is obtained, robot service data is obtained, and robot response data of robot is obtained according to the robot response to the robot, robot service data of robot, and important robot service data of robot is obtained, robot response of robot, robot is obtained by using robot, robot. The command bar effectively evaluates the robot requirements to generate effective task commands in each time period, invalid or abnormal or non-important urgent robot requirements are screened out, a community robot task allocation list is generated according to the robot task data command bar in each time period to allocate tasks for the robots and generate the task commands, so that the robot resources are effectively, maximally and definitely distributed and applied, optimal distribution of the community robot resources is realized, and intellectualization and precision of community robot management application are realized.

According to the embodiment of the invention, the public service demand information and the resident service demand information in the community are collected, the task quantity of the service demand information is analyzed to generate the task element list, and the unit service list is constructed, which specifically comprises the following steps:

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

acquiring unit task packet data according to a task information data set of the unit resident corresponding to the unit service list;

It should be noted that, in order to obtain robot type information matched with public service or household service so as to clarify the demand situation of robot resources, a service requirement information bar, i.e. entry information of each item of service demand for the robot, is extracted according to a public and household service task element list, service item data is extracted according to the service requirement information bar, task information data is obtained by analyzing according to a service data analysis program, the task information data reflects evaluation data of the task information, wherein the task information data of each household unit is aggregated into unit task packet data, i.e. reflects the integral service demand data of a certain household within a certain preset time period, the task information data is compared with a preset robot task allocation threshold value by a threshold value, and a matched robot type is obtained according to robot type allocation of each item of service demand corresponding to the threshold value comparison rangeThe robot comprises an I-guide care robot, an II intelligent strain robot and a III qualitative task robot, wherein the corresponding task allocation threshold ranges of the three robots are respectively I corresponding (0.7,1)]II corresponds to (0.3,0.7)]III corresponds to [0,0.35]If the threshold value of the task information data of cooking cleaning of a certain resident is 0.63, the cooking cleaning service project distribution robot is an intelligent strain robot II; generating a robot community task organization tree according to service project data and task information data of the public and the residents and combining corresponding service robot information, wherein the organization tree defines service contents of the public and the residents in the community and information and data details of corresponding robot resources, and simultaneously comprises a service robot information set of each unit resident, namely the whole robot demand condition of each resident in a preset time period; the service data analysis program for obtaining the task information data comprises the following steps: r is _s ＝ρ _f (η J + γ K + δ T); wherein R is _s For task information data, p _f And J is service item data, K is item category data, T is service time data, and eta, gamma and delta are preset coefficients (obtained by inquiring through a preset community robot service management platform).

According to the embodiment of the invention, the robot task density statistics is carried out according to the robot community task organization tree, and the community robot task data portraits are generated according to the robot task density data sets in the task time period, and the method specifically comprises the following steps:

calculating according to the robot task bar data, the service difficulty coefficient and the service time data in combination with the robot distribution quantity and the robot category coefficient of each task bar to obtain robot task density data in each preset time period;

wherein, B ₀ Responding data for a robot task, M _σ Performing data for a robot task, U _d For robot task volume data, G _F C is robot operation difficulty data, and c is robot cooperation quantity, lambda,

acquiring a corresponding priority coefficient of the task information data;

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

if the service requirement is met, not triggering task dispatching response;

if not, sending a recall instruction to the robot for recall;

judging whether the residual performance state information obtained by subtracting the preset robot performance state data from the corresponding state data of the performance state information meets the residual operation information of the service requirement information or not;

and if not, sending a recall instruction to the robot for recall.

It should be noted that, in order to monitor the performance state of the robot itself, to dynamically evaluate whether the robot can continue to execute the task smoothly, the robot executing the community service task is dynamically self-checked, and obtain the real-time task execution information and performance state information of the robot, respectively judge the task execution information and the performance state information, judge whether the task execution information meets the service inspection standard data of the service requirement information, to identify whether to send a recall instruction, and obtain the remaining performance state information according to the difference between the preset state data of the robot performance and the corresponding state data of the performance state information, to judge whether the remaining operation information meets the service requirement information, if not, send 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, the robot Z needs to be recalled; and if the residual performance state information of the certain robot A is not lower than the preset value of 90 percent of the minimum required value of the residual operation information, the robot A does not need to recall and can continue to execute the task.

The third aspect of the present invention provides a readable storage medium, where the readable storage medium includes a program of a community robot intelligent coordination control method, and when the program of the community robot intelligent coordination control method is executed by a processor, the steps of the community robot intelligent coordination control method described in any one of the above are implemented.

The invention discloses a community robot intelligent coordination management and control method, a system and a readable storage medium.A task element list is generated by analyzing the task quantity of community service demand information, task information data is analyzed, robots of corresponding categories are distributed to generate a robot community task organization tree, then a task density data set is obtained through statistics, a community robot task data image is generated, robot project service data is extracted and processed to obtain robot task response data, and then a task allocation list is generated according to a robot task data instruction bar in a generated time period to allocate tasks for the robots; therefore, based on big data and intelligent robot technology, information acquisition and data processing are carried out on community service to optimize the distribution of the type robot, the purpose matching is carried out on the community service demand information and robot resources, the optimal distribution of the community robot resources is achieved, and the intellectualization and the accuracy of community robot management application are improved.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or in other forms.

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

In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various media capable of storing program codes.

Alternatively, the integrated unit of the present invention may be stored in a readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) 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, a ROM, a RAM, a magnetic or optical disk, or various other media capable of storing program code.

Claims

1. A community robot intelligent coordination control method is characterized by comprising the following steps:

2. The intelligent coordination management and control method for community robots as claimed in claim 1, wherein the method comprises the steps of collecting public service demand information and resident service demand information in a community, analyzing task quantity of the service demand information to generate a task element list, and constructing a unit service list, and comprises the following steps:

3. The community robot intelligent coordination management and control method according to claim 2, wherein 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 method comprises the following steps:

4. The community robot intelligent coordination management and control method according to claim 3, wherein the performing 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 at a task time interval comprises:

5. The community robot intelligent coordination control method according to claim 4, wherein the steps of 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 deployment model to obtain robot task response data include:

6. The community robot intelligent coordination management and control method according to claim 5, wherein the step of generating a robot task data instruction strip of a preset time period according to the robot task response data and the priority coefficient of the task information data comprises:

acquiring a corresponding priority coefficient of the task information data;

7. The community robot intelligent coordination management and control method according to claim 6, wherein the generating of the community robot task allocation list according to the robot task data instruction pieces of each time period, the task allocation of the robot according to the list and the generation of the task instruction comprise:

8. The utility model provides a management and control system is coordinated to community robot wisdom which characterized in that, this system includes: the intelligent community robot coordination control method comprises a memory and a processor, wherein the memory comprises a program of the intelligent community robot coordination control method, and the program of the intelligent community robot coordination control method realizes the following steps when executed by the processor:

9. The community robot intelligent coordination management and control system according to claim 8, wherein the collecting public service demand information and resident service demand information in the community, performing task quantity analysis on the service demand information to generate a task element list, and constructing a unit service list comprises:

10. A computer-readable storage medium, comprising a program of a community robot intelligent coordination management and control method, wherein when the program of the community robot intelligent coordination management and control method is executed by a processor, the steps of the community robot intelligent coordination management and control method according to any one of claims 1 to 7 are implemented.