CN112882806A

CN112882806A - Management method, management apparatus, workstation, and readable storage medium

Info

Publication number: CN112882806A
Application number: CN202110139602.5A
Authority: CN
Inventors: 左海成; 杨鹏程; 秦宝星; 程昊天
Original assignee: Shanghai Gaussian Automation Technology Development Co Ltd
Current assignee: Shanghai Gaussian Automation Technology Development Co Ltd
Priority date: 2021-02-01
Filing date: 2021-02-01
Publication date: 2021-06-01
Anticipated expiration: 2041-02-01
Also published as: CN112882806B

Abstract

The application discloses a management method, which comprises the following steps: receiving reservation information sent by one or more intelligent robots; calculating a queuing number of each intelligent robot according to the reservation information; and calling the intelligent robots in sequence according to the queuing number. The application also discloses a management device, a workstation and a computer readable storage medium, and the management device, the workstation and the computer readable storage medium can realize that one workstation can manage a plurality of intelligent robots, and the workstation can call the corresponding intelligent robots according to a certain sequence to supply to the workstation, so that the utilization rate of the workstation is improved.

Description

Management method, management apparatus, workstation, and readable storage medium

Technical Field

The present application relates to the field of workstation management technologies, and more particularly, to a management method, a management apparatus, a workstation, and a non-volatile computer-readable storage medium.

Background

The robot needs to consume electric quantity, water and the like when in work and can generate garbage at the same time, so that a work station is needed to ensure that the robot can continuously and efficiently work under the unattended condition. Generally, one work station is matched with one robot, when a plurality of robots are used in one field, a corresponding number of work stations are required to be provided, under the condition, the work stations occupy more fields, the utilization rate is low, and the use and maintenance cost is improved. Therefore, a method is needed to allow one workstation to manage multiple robots simultaneously.

Disclosure of Invention

In view of the above, the present invention is directed to solving, at least to some extent, one of the problems in the related art. To this end, the embodiment of the application provides a management method, a management device, a workstation and a nonvolatile computer readable storage medium.

The management method of the embodiment of the application comprises the following steps: receiving reservation information sent by one or more intelligent robots; calculating a queuing serial number of each intelligent robot according to the reservation information; and calling the intelligent robot in sequence according to the queuing sequence number.

In the management method of the embodiment of the application, the workstation can calculate the queuing number of each intelligent robot according to the reservation information sent by one or more intelligent robots, and then sequentially calls the intelligent robots according to the queuing numbers. Therefore, one workstation can manage a plurality of intelligent robots, the workstation can call the corresponding intelligent robots according to a certain sequence to supply the intelligent robots, and the utilization rate of the workstation is improved.

In some embodiments, the calculating a queuing number of each of the intelligent robots according to the reservation information includes: calculating the queuing priority of the intelligent robot according to the reservation information; and calculating the queuing sequence number of the intelligent robot in a queuing queue according to the queuing priority.

In the embodiment, the queuing priority of the intelligent robot is calculated according to the reservation information sent by the intelligent robot, and then the queuing number of the intelligent robot in the queuing queue is calculated according to the queuing priority, so that the actual requirements of different intelligent robots can be considered to be different, and the calculated queuing number is more reasonable.

In some embodiments, the calculating the priority of queuing of the intelligent robot according to the reservation information includes: acquiring service content required by the intelligent robot according to the reservation information; and calculating the queuing priority according to the service content required by the intelligent robot.

In the embodiment, the service content required by the intelligent robot is acquired according to the reservation information sent by the intelligent robot, and then the queuing priority is calculated according to the service content required by the intelligent robot, so that the calculated queuing priority is associated with the service content required by the intelligent robot, and the calculated queuing priority is more reasonable.

In some embodiments, when the service content includes a plurality of service sub-contents, different service sub-contents take different time, and the calculating the queuing priority according to the service content required by the intelligent robot includes: judging whether the service contents have the service sub-contents which can be performed simultaneously; and if so, calculating the queuing priority by the service sub-content which consumes the longest time in the service sub-contents which can be simultaneously performed.

In the embodiment, when the service subcontent which can be simultaneously performed exists in the service content required by the intelligent robot, the queuing priority is calculated according to the service subcontent which consumes the longest time in the service subcontent which can be simultaneously performed, so that the queuing priority calculated when calculating the queuing priority is higher than the actual queuing priority of the intelligent robot, and the accuracy of the queuing number of the intelligent robot obtained by calculation is improved.

In some embodiments, the calculating the queuing number of the intelligent robot in a queuing queue according to the queuing priority includes: comparing the queuing priority of each intelligent robot; and determining the queuing sequence number of the intelligent robot in the queuing according to the comparison result.

In the embodiment, the queuing priority of the intelligent robot is compared, and then the queuing serial number of the intelligent robot in the queuing queue is determined according to the obtained comparison result, so that the queuing serial number of the intelligent robot is more reasonable, and the intelligent robot is favorably managed by a workstation.

In some embodiments, the management method further comprises: and acquiring the reservation information of each intelligent robot in the queuing queue again at intervals of preset time.

In the embodiment, the reservation information of each intelligent robot in the queuing queue is obtained again every preset time, so that the queuing serial number of the intelligent robot can be updated in time when the service content of the intelligent robot is changed greatly, and the intelligent robot which needs the service most can be provided with the service in time.

In some embodiments, after the reservation information of each intelligent robot in the queuing queue is obtained again, the calculating a queuing number of each intelligent robot according to the reservation information includes: calculating the real-time queuing priority of each intelligent robot according to the obtained reservation information; calculating the difference value between the real-time queuing priority levels of the adjacent intelligent robots in the queuing queue; when the difference value is larger than a preset difference value, the queuing number is kept unchanged; and when the difference value is smaller than a preset difference value, adjusting the queuing number.

In the embodiment, after the reservation information of each intelligent robot in the queuing queue is obtained again each time, the real-time queuing priority of each intelligent robot is calculated according to the obtained reservation information, and the queuing number is adjusted when the difference value between the real-time queuing priority of adjacent intelligent robots in the queuing queue is larger than the preset difference value, so that the situation that the intelligent robots are managed by a workstation due to frequent change of the queuing number is avoided, and the queuing number in the queuing queue is adjusted in time.

In some embodiments, said calling said intelligent robots in sequence according to said queuing numbers comprises: inquiring whether the intelligent robot corresponding to the most front queuing serial number in the queuing queue uses a workstation or not; waiting for the intelligent robot to use when the intelligent robot replies that the workstation needs to be used; and when the intelligent robot replies that the workstation is not needed to be used; or after the preset time is exceeded and the reply of the intelligent robot is not received, calling the intelligent robot corresponding to the next queuing serial number in the queuing queue.

In the embodiment, when the intelligent robot corresponding to the most front queuing serial number in the queuing queue replies that the workstation is not needed to be used or the reply of the intelligent robot is not received after the preset time, the intelligent robot corresponding to the next queuing serial number in the queuing queue is called, so that the situation that the rest intelligent robots cannot go to the workstation for replenishment due to the fact that the intelligent robot corresponding to the most front queuing serial number in the queuing queue is abnormal or the workstation is not needed to be used and the workstation still calls the intelligent robot all the time is avoided, and the robustness of the workstation when managing a plurality of intelligent robots is improved.

In some embodiments, the inquiring whether the intelligent robot corresponding to the queue serial number at the top in the queue uses a workstation further includes: judging whether the workstation is in an idle state or not; and inquiring the intelligent robot when the workstation is in an idle state.

In the embodiment, the intelligent robot is inquired when the workstation is in the idle state, so that the condition that the intelligent robot cannot be replenished after the intelligent robot reaches the workstation due to the fact that the workstation inquires the intelligent robot at the work is avoided.

The management device comprises a receiving module, a calculating module and a first calling module, wherein the receiving module is used for receiving reservation information sent by one or more intelligent robots; the calculation module is used for calculating the queuing serial number of each intelligent robot according to the reservation information; and the first calling module is used for calling the intelligent robot in sequence according to the queuing sequence number.

In the management device according to the embodiment of the application, the workstation can calculate the queuing number of each intelligent robot according to the reservation information sent by one or more intelligent robots, and then sequentially calls the intelligent robots according to the queuing numbers. Therefore, one workstation can manage a plurality of intelligent robots, the corresponding intelligent robots can be called according to a certain sequence to supply to the workstation, and the utilization rate of the workstation is improved.

In certain embodiments, the computing module is further configured to: calculating the queuing priority of the intelligent robot according to the reservation information; and calculating the queuing sequence number of the intelligent robot in the queuing according to the queuing priority.

In certain embodiments, the computing module is further configured to: acquiring service content required by the intelligent robot according to the reservation information; and calculating the queuing priority according to the service content required by the intelligent robot.

In some embodiments, when the service content includes a plurality of service sub-contents, different service sub-contents take different time, and the calculation module is further configured to: judging whether the service contents have the service sub-contents which can be performed simultaneously; and if so, calculating the queuing priority by the service sub-content which consumes the longest time in the service sub-contents which can be simultaneously performed.

In certain embodiments, the computing module is further configured to: comparing the queuing priority of each intelligent robot; and determining the queuing sequence number of the intelligent robot in the queuing according to the comparison result.

In some embodiments, the management apparatus further includes an obtaining module, where the obtaining module is configured to obtain the reservation information of each intelligent robot in the queuing queue again every preset time period.

In some embodiments, each time the reservation information for each of the intelligent robots in the queue is retrieved, the computing module is further configured to: calculating the real-time queuing priority of each intelligent robot according to the obtained reservation information; calculating the difference value between the real-time queuing priority levels of the adjacent intelligent robots in the queuing queue; when the difference value is larger than a preset difference value, the queuing number is kept unchanged; and when the difference value is smaller than a preset difference value, adjusting the queuing number.

In some embodiments, the call module is further configured to: inquiring whether the intelligent robot corresponding to the most front queuing serial number in the queuing queue uses a workstation or not, and waiting for the intelligent robot to use before when the intelligent robot replies that the workstation needs to be used; when the intelligent robot replies that the workstation is not needed to be used; or after the preset time is exceeded, the reply of the intelligent robot is not received, and the intelligent robot corresponding to the next queuing serial number in the queuing queue is called.

In some embodiments, the call module is further configured to: judging whether the workstation is in an idle state or not; and inquiring the intelligent robot when the workstation is in an idle state.

The workstation of an embodiment of the present application includes one or more processors, memory, and one or more programs, where the one or more programs are stored in the memory and executed by the one or more processors, the programs including instructions for performing the management method of any of the above embodiments.

In the workstation of the embodiment of the application, the workstation can calculate the queuing number of each intelligent robot according to the reservation information sent by one or more intelligent robots, and then sequentially calls the intelligent robots according to the queuing numbers. Therefore, one workstation can manage a plurality of intelligent robots, the corresponding intelligent robots can be called according to a certain sequence to supply to the workstation, and the utilization rate of the workstation is improved.

A non-transitory computer-readable storage medium containing a computer program according to an embodiment of the present application, when the computer program is executed by one or more processors, causes the processors to implement the management method according to any one of the above embodiments.

In the non-volatile computer-readable storage medium according to the embodiment of the application, the workstation can calculate the queuing number of each intelligent robot according to reservation information sent by one or more intelligent robots, and then sequentially calls the intelligent robots according to the queuing numbers. Therefore, one workstation can manage a plurality of intelligent robots, the workstation can call the corresponding intelligent robots according to a certain sequence to supply the intelligent robots, and the utilization rate of the workstation is improved.

Additional aspects and advantages of embodiments of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of embodiments of the present application.

Drawings

The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 2 is a block schematic diagram of a workstation according to an embodiment of the present application;

FIG. 3 is a block diagram of a management device according to an embodiment of the present application;

FIG. 4 is a schematic view of a workstation and an intelligent robot according to an embodiment of the present application;

FIG. 5 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 6 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 7 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 8 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 9 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 10 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 11 is a schematic flow chart of a management method according to an embodiment of the present application;

FIG. 12 is a schematic flow chart of a management method according to an embodiment of the present application;

fig. 13 is a schematic diagram illustrating a connection relationship between a computer-readable storage medium and a processor according to an embodiment of the present application.

Detailed Description

Embodiments of the present application will be further described below with reference to the accompanying drawings. The same or similar reference numbers in the drawings identify the same or similar elements or elements having the same or similar functionality throughout. In addition, the embodiments of the present application described below in conjunction with the accompanying drawings are exemplary and are only for the purpose of explaining the embodiments of the present application, and are not to be construed as limiting the present application.

Referring to fig. 1 to 4, a management method according to an embodiment of the present disclosure includes the following steps:

010: receiving reservation information sent by one or more intelligent robots 200;

020: calculating a queuing number of each intelligent robot 200 according to the reservation information; and

030: and calling the intelligent robot 200 in sequence according to the queuing number.

The management device 300 according to the embodiment of the present application includes a receiving module 310, a calculating module 320, and a calling module 330, and the receiving module 310, the calculating module 320, and the calling module 330 may be respectively configured to implement step 010, step 020, and step 030. That is, the receiving module 310 may be configured to receive reservation information sent by one or more intelligent robots 200, the calculating module 320 may be configured to calculate a queuing number of each intelligent robot 200 according to the reservation information, and the calling module 330 may be configured to sequentially call the intelligent robots 200 according to the queuing number.

The workstation 100 of the embodiments of the present application includes one or more processors 10, a memory 20, and one or more programs, where the one or more programs are stored in the memory 20 and executed by the one or more processors 10, the programs including instructions for performing the management methods described in the embodiments of the present application. Processor 10, when executing the program, processor 10 may implement

steps

010, 020, and 030. That is, the processor 10 may be configured to: receiving reservation information sent by one or more intelligent robots 200; calculating a queuing number of each intelligent robot 200 according to the reservation information; and sequentially calling the intelligent robot 200 according to the queuing number.

In the management method, the management apparatus 300, and the workstation 100 according to the embodiment of the present invention, the workstation 100 can calculate the queue number of each intelligent robot 200 based on the reservation information transmitted from one or more intelligent robots 200, and then sequentially call the intelligent robots 200 based on the queue numbers. Therefore, one workstation 100 can manage a plurality of intelligent robots 200, and the workstation 100 can call the corresponding intelligent robots 200 according to a certain sequence to replenish the workstation 100, so that the utilization rate of the workstation 100 is improved.

Specifically, the intelligent robot 200 may be an industrial robot, an agricultural robot, a home robot, a service robot, and a cleaning robot, and further, the cleaning robot may be an intelligent robot such as a floor sweeping robot, a floor washing robot, a crystallizing robot, and a polishing robot. In the embodiment of the present application, the intelligent robot 200 is taken as an example of a cleaning robot, and it is understood that the intelligent robot 200 may be other robots, and is not limited herein.

In the process of executing the task, the intelligent robot 200 will be continuously consumed along with the working time, for example, the intelligent robot 200 needs to consume electric power and water during working, and simultaneously generates waste water, if the intelligent robot 200 is manually charged, water is added, waste water is discharged, and the like, the working efficiency is seriously affected, and more human resources are needed. Therefore, the workstation 100 needs to be configured to provide services for the intelligent robot 200, so that the intelligent robot 200 can continuously and efficiently work under the unattended condition.

It can be understood that the workstation 100 can provide services such as charging, water adding, waste water discharging and the like for the intelligent robot 200, so that the intelligent robot 200 can go to the workstation 100 at any time for replenishment during work, and the problem that the work efficiency of the workstation 100 is low due to frequent participation of people is avoided. Currently, an intelligent robot 200 needs a dedicated workstation 100 to provide services for the intelligent robot, so that when a plurality of intelligent robots 200 work in an area, a plurality of workstations 100 need to be arranged, and the use cost and the occupied area are increased.

Therefore, the management method provided by the present application can be used for the workstation 100 to manage at least one intelligent robot 200, please refer to fig. 4, the workstation 100 can be simultaneously in communication connection with a plurality of intelligent robots 200, so that the workstation 100 can simultaneously manage a plurality of intelligent robots 200, when a plurality of intelligent robots 200 are required to simultaneously work, only one workstation 100 needs to be set to simultaneously provide service for the plurality of intelligent robots 200, thereby reducing the use cost and the occupied area. Among other things, the workstation 100 may be used to manage 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or even more intelligent robots 200.

The water used in the embodiments of the present invention may be a liquid such as tap water, river water, cleaning liquid, or disinfectant, and may be not only tap water. The service provided by the workstation 100 to the intelligent robot 200 is not limited to charging, adding water, discharging waste water, etc., but may be other services, such as adding oil, adding workpieces, etc.

In step 010, reservation information transmitted by one or more intelligent robots 200 is received. Specifically, when the intelligent robot 200 needs to use the workstation 100 or is about to need to use the workstation 100, the intelligent robot 200 transmits reservation information to the workstation 100 to make a reservation to the workstation 100, and the workstation 100 can receive the reservation information transmitted by one or more intelligent robots 200. The reservation information may include, but is not limited to, charging, adding water, draining waste water, a distance from the workstation 100, and the like, and further, the reservation information may further include a remaining power, a remaining water amount, a stored waste water amount, and the like of the current intelligent robot 200.

In step 020, a queuing number of each intelligent robot 200 is calculated according to the reservation information. When the workstation 100 receives reservation information transmitted by one or more intelligent robots 200, the workstation 100 may calculate a queuing number of each intelligent robot 200 according to the received reservation information. If five intelligent robots 200 initially transmit reservation information to the workstation 100, the workstation 100 calculates queuing numbers of the five intelligent robots 200 according to the reservation information transmitted by the five intelligent robots 200; after a period of time, the sixth intelligent robot 200 transmits reservation information to the workstation 100, and the workstation 100 needs to recalculate the queue numbers of the six intelligent robots 200 after receiving the reservation information transmitted by the sixth intelligent robot 200.

In one example, the intelligent robots 200 are sorted according to the transmission time in the reservation information. In another example, the ordering is performed according to the time spent by the service contents required by the intelligent robot 200 in the reservation information, and the ordering is performed in a short time. In another example, the ordering is performed according to the time consumed by the service contents required by the intelligent robot 200 and the transmission time of the reservation information, so as to avoid that a part of the intelligent robot 200 waits too long. By reasonably calculating the queuing number of each intelligent robot 200, each intelligent robot 200 can arrive at the workstation 100 for replenishment in good order.

In step 030, the intelligent robot 200 is sequentially called according to the queuing number. Specifically, each intelligent robot 200 has a queuing number, and the intelligent robots 200 are called in sequence from small to large according to the queuing number to come to the workstation 100 for replenishment, so that each intelligent robot 200 can arrive at the workstation 100 to complete replenishment. Of course, the workstation 100 may choose whether to call the intelligent robot 200 according to its own actual situation. Or the workstation 100 may adjust the queuing number of the intelligent robot 200 according to the actual situation of the workstation, for example, the workstation 100 finds that the water of the workstation 100 is less than the requirement of the intelligent robot 200 with the most serial number, and the workstation 100 may adjust the serial number of the intelligent robot 200 that can meet the requirement to the front so as to meet the requirement of one or more intelligent robots 200 as much as possible. Meanwhile, the idle time of the workstation 100 is short, the workstation 100 is fully utilized, and the problem that the idle time of the workstation 100 is long due to the fact that a plurality of workstations 100 are used is avoided.

Referring to fig. 5, in some embodiments, step 020 includes the following steps:

021: calculating the queuing priority of the intelligent robot according to the reservation information; and

022: and calculating the queuing sequence number of the intelligent robot in the queuing queue according to the queuing priority.

In some embodiments, the calculation module 320 may also be configured to calculate a queuing priority of the intelligent robot according to the reservation information; and calculating the queuing sequence number of the intelligent robot in the queuing queue according to the queuing priority. That is, computing module 320 may also be used to implement

steps

021 and 022.

In some embodiments, the processor 10 may be further configured to calculate a queuing priority of the intelligent robot based on the reservation information; and calculating the queuing sequence number of the intelligent robot in the queuing queue according to the queuing priority. That is, the processor 10 can also be used to implement step 021 and step 022.

Specifically, after the workstation 100 receives the reservation information of the intelligent robot, the workstation 100 may calculate the queuing priority of the intelligent robot according to the reservation information and a predetermined rule, and then may calculate the queuing number of the intelligent robot in the queuing queue according to the calculated queuing priority, for example, the smaller the queuing priority, the higher the queuing number; or the queuing priority is high, the queuing serial number is high, and then the intelligent robot is added into the queuing queue for queuing. Therefore, the intelligent robot is sequenced, and the queuing sequence number obtained by calculation is reasonable.

For example, the reservation information may include the time it takes for the intelligent robot to complete the replenishment, the greater the queuing priority if the time it takes is longer, and the lesser the queuing priority if the time it takes is shorter. Alternatively, the workstation 100 may extract predetermined contents in the reservation information and then calculate a value of the predetermined contents according to a predetermined calculation formula, which may be regarded as a queuing priority of the intelligent robot.

For example, the smaller the queuing priority, the higher the queuing number, the more water needs to be supplied to the workstation 100 by the intelligent robot a, the more water needs to be supplied to the workstation 100 by the intelligent robot B, and the water supply amounts of the intelligent robot a and the intelligent robot B are the same, the queuing priority of the intelligent robot a and the intelligent robot B can be calculated according to the distance between the workstation 100 and the intelligent robot a, and the queuing priority of the intelligent robot a and the intelligent robot B close to the workstation 100 is lower than the queuing priority of the intelligent robot far from the workstation 100, and correspondingly, the queuing number of the intelligent robot close to the workstation 100 is smaller than the queuing number of the intelligent robot far from the workstation 100.

Referring to FIG. 6, in some embodiments, step 021 includes the following steps:

0211: acquiring service content required by the intelligent robot according to the reservation information; and

0212: and calculating the queuing priority according to the service content required by the intelligent robot.

In some embodiments, the calculation module 320 may also be configured to: acquiring service content required by the intelligent robot according to the reservation information; and calculating the queuing priority according to the service content required by the intelligent robot. That is, the computing module 320 can also be used to implement step 0211 and step 0212.

In some embodiments, the processor 10 may be further configured to: acquiring service content required by the intelligent robot according to the reservation information; and calculating the queuing priority according to the service content required by the intelligent robot. That is, the processor 10 can also be used to implement the

steps

0211 and 0212.

Specifically, different intelligent robots may require different service contents, and the time spent by the different intelligent robots will also be different, which may cause unreasonable queuing priority of the intelligent robots if the queuing priorities of the intelligent robots are calculated according to the reserved time, thereby reducing the work efficiency of the workstation 100. Therefore, when calculating the queuing priority of the intelligent robot, the service content required by the intelligent robot should be considered, so that the calculated queuing priority is more reasonable.

Further, the workstation 100 may set a corresponding value according to the amount of time spent by the service contents. The reservation information sent by the intelligent robot may include required service contents, and the workstation 100 may extract the service contents required by the intelligent robot from the reservation information, and then calculate values corresponding to the service contents according to a preset correspondence, so as to obtain a queuing priority of the intelligent robot.

For example, when the intelligent robot uses the workstation 100, the two processes of adding water and discharging wastewater are performed faster, the charging is performed for a longer time, the queuing priority value corresponding to the adding water and the discharging wastewater is smaller, the queuing priority value corresponding to the charging is larger, when the workstation 100 identifies that the intelligent robot a only needs to add water according to the reservation information, the intelligent robot B needs to be charged, the queuing priority of the intelligent robot a calculated by the workstation 100 is smaller than the queuing priority of the intelligent robot B, the workstation 100 can preferentially arrange the intelligent robot a for use, so that the intelligent robot a can complete the water adding operation faster and then continue to execute the work task, and the work efficiency is higher. On the contrary, if the intelligent robot B is preferentially arranged to come from the workstation 100 before and the intelligent robot a is arranged to come from the workstation 100 after the intelligent robot B, the intelligent robot a will wait for a long time, which affects the working efficiency of the intelligent robot a.

More specifically, the service content may include a plurality of service sub-contents, each service sub-content is correspondingly provided with a reference value, and the queuing priority of the intelligent robot may be calculated according to a preset calculation formula and the service sub-contents. For example, the service content includes water addition, wastewater discharge, and charging, the preset queuing priority calculation formula may be t ═ ax + by + cz + ds, where a denotes a reference value of water addition, x denotes an amount of water addition, b denotes a reference value of wastewater discharge, y denotes an amount of wastewater discharge, c denotes a reference value of charging, z denotes a charge amount, d denotes a reference value of distance, and s denotes a distance between the intelligent robot and the workstation 100, the reservation information may include a required amount of water addition, an amount of wastewater discharge, a charge amount, and a distance from the workstation 100, and if the value of x, y, and z in the reservation information is 0, it denotes that the service is not required.

Further, the queuing priorities of the plurality of intelligent robots can be calculated, then the queuing serial number of each intelligent robot can be determined according to the queuing priorities, the queuing serial number corresponding to the intelligent robot with the small value of the queuing priority is obtained by calculation and is prior to the queuing serial number corresponding to the intelligent robot with the large value of the queuing priority, and when the calculated queuing priority values are equal, the intelligent robots can be sorted according to the order of reservation. Therefore, a plurality of intelligent robots can be reasonably managed according to the queuing number. Wherein the reference value may be determined according to a time consumed by a specific intelligent robot to averagely execute the corresponding service sub-content.

Referring to fig. 7, in some embodiments, when the service content includes a plurality of service sub-contents, and different service sub-contents take different time, there may be a situation that some service sub-contents may be simultaneously performed, which if not considered in calculating the queuing priority may cause unreasonable calculated queuing priority and affect the work efficiency of the workstation 100, and therefore, the step 0212 may include the following steps:

2121: judging whether the service contents have the service sub-contents which can be performed simultaneously; and

2122: and if so, calculating the queuing priority by the service sub-content which consumes the longest time in the service sub-contents which can be simultaneously performed.

In some embodiments, the calculation module 320 may also be configured to: judging whether the service contents have the service sub-contents which can be performed simultaneously; and if so, calculating the queuing priority by the service sub-content which consumes the longest time in the service sub-contents which can be simultaneously performed. That is, the calculation module 320 may also be used to implement step 2121 and step 2122.

In some embodiments, the processor 10 may be further configured to: judging whether the service contents have the service sub-contents which can be performed simultaneously; and if so, calculating the queuing priority by the service sub-content which consumes the longest time in the service sub-contents which can be simultaneously performed. That is, the processor 10 may also be used to implement step 2121 and step 2122.

Specifically, in order to avoid the situation that the calculated queuing priority is unreasonable due to the service sub-content that can be performed simultaneously, the workstation 100 needs to determine whether there is a service sub-content that can be performed simultaneously in the service content in the reservation information, and if there is a service sub-content that can be performed simultaneously, when calculating the queuing priority, the queuing priority is calculated according to the service sub-content that consumes the longest time among the service sub-contents, because the service sub-content that consumes the longest time is completed, other service sub-contents are also already completed.

More specifically, in an embodiment, the water adding, the waste water discharging, and the charging may be performed simultaneously, and when the intelligent robot needs to add water, discharge waste water, and charge simultaneously, the calculation formula of the queuing priority in the above embodiment may be simplified to t ═ 0+0+ cz + ds, so that the calculated queuing priority and queuing number are more reasonable.

For example, in one example, the intelligent robot a needs to perform three services of water adding, waste water discharging and charging, the workstation 100 initially calculates the queuing priority t1 of the intelligent robot a to be 48+60+720+0.125 to 300 to 865.5, the intelligent robot B only needs to perform the charging service, the workstation 100 initially calculates the queuing priority t2 of the intelligent robot B to be 780+0.125 to 250 to 811.25, and if the water adding, waste water discharging and charging are not considered to be performed simultaneously, the queuing priority of the intelligent robot B is smaller than that of the intelligent robot a, and the queuing number of the intelligent robot B is earlier than that of the intelligent robot a. However, if it is considered that water addition, wastewater discharge, and charging are performed simultaneously, the queuing priority t1 'of the intelligent robot a is 720+ 0.125-300-757.5, and the queuing priority t 2' of the intelligent robot B is 780+ 0.125-250-811.25, and at this time, the calculated queuing priority of the intelligent robot B is greater than that of the intelligent robot a, and the queuing number of the intelligent robot B is later than that of the intelligent robot a.

Referring to fig. 8, in certain embodiments, step 022 comprises the steps of:

0221: comparing the queuing priority of each intelligent robot; and

0222: and determining the queuing serial number of the intelligent robot in the queuing according to the comparison result.

In some embodiments, the calculation module 320 may also be configured to: comparing the queuing priority of each intelligent robot; and determining the queuing number of the intelligent robot in the queuing according to the comparison result. That is, computing module 320 may also be used to implement step 0221 and step 0222.

In some embodiments, the processor 10 may be further configured to: comparing the queuing priority of each intelligent robot; and determining the queuing number of the intelligent robot in the queuing according to the comparison result. That is, processor 10 may also be used to implement step 0221 and step 0222.

Specifically, the queuing priority of each intelligent robot is calculated in step 021, in order to obtain the queuing serial number of the intelligent robot, the queuing priority of each intelligent robot needs to be compared respectively, and then the queuing serial number of the intelligent robot in the queuing queue can be obtained according to the comparison result, so that the obtained queuing serial number is more accurate.

More specifically, in one embodiment, a plurality of intelligent robots are already present in the queue of the workstation 100 before the intelligent robot C transmits the reservation information. When the intelligent robot C sends the reservation information, the workstation 100 may calculate a corresponding queuing priority according to the reservation information sent by the intelligent robot C, then compare the calculated queuing priority of the intelligent robot C with the queuing priority of each intelligent robot in the current queuing queue, and determine the queuing number of the intelligent robot C according to the comparison result.

For example, in one example, 10 intelligent robots have been queued in the queue of the workstation 100, the workstation 100 calculates the queuing priority of the intelligent robot C according to the received reservation information sent by the intelligent robot C, and finds that the queuing priority of the intelligent robot C is between the seventh intelligent robot and the eighth intelligent robot by comparing the queuing priority of the intelligent robot C with the queuing priorities of the 10 intelligent robots in the current queue, it may be determined that the queuing number of the intelligent robot C is eight, and then the queuing numbers of the eighth to tenth intelligent robots in the original queue are adjusted to be nine to eleven.

Referring to fig. 9, in some embodiments, the management method further includes the following steps:

040: and acquiring the reservation information of each intelligent robot in the queue again every preset time.

In some embodiments, the management apparatus 300 further includes an obtaining module 340, and the obtaining module 340 may be configured to obtain the reservation information of each intelligent robot in the queue again at preset time intervals. That is, the obtaining module 340 may also be used to implement step 040.

In some embodiments, the processor 10 may be further configured to retrieve the reservation information of each intelligent robot in the queue every preset time period. That is, the processor 10 may also be configured to implement step 040.

Specifically, after the intelligent robot sends the reservation information to the workstation 100, and the workstation 100 determines a queuing serial number for the intelligent robot, part or all of the intelligent robots in the queuing queue will continue to work, and state data such as the remaining power, the remaining water amount, the included waste water amount, the distance from the workstation 100, and the like of the intelligent robot in the working process will change in real time, so that the reservation information of the intelligent robot may change greatly, for example, part of the intelligent robots work less or not after reservation, and part of the intelligent robots work more after reservation, resulting in the intelligent robots in the original queuing queue, and if queuing is performed according to the original queuing serial number, the working efficiency of the workstation 100 and the intelligent robots may be low.

Therefore, the reservation information of each intelligent robot in the queuing queue is obtained again every preset time, and then the queuing serial number of each intelligent robot in the queuing queue can be adjusted according to the obtained reservation information, so that the queuing serial number of each intelligent robot is more reasonable. For example, the intelligent robots in the queue actively resend the reservation information to the workstation 100 every preset time period, or the workstation 100 sends a command to the intelligent robots in the queue every preset time period to request the intelligent robots to resend the reservation information, and the intelligent robots can resend new reservation information to the workstation 100 when receiving the command.

The preset time period may be a fixed time period, such as 0 second, 30 seconds, 60 seconds, 2 minutes, 5 minutes, 10 minutes, 15 minutes or more, which is not listed here. The preset time duration can also be dynamically adjusted according to the number of the intelligent robots in the queuing queue, when the number of the intelligent robots in the queuing queue is small (for example, 1, 2, 3, 4, and the like), the preset time duration can be set longer or infinity is set, and when the number of the intelligent robots in the queuing queue is large (for example, 8, 9, 10, and the like), the preset time duration can be set shorter, so that the queuing sequence number can be dynamically adjusted better.

Referring to fig. 10, in some embodiments, after retrieving the reservation information of each intelligent robot in the queue, step 020 further includes the following steps:

023: calculating the real-time queuing priority of each intelligent robot according to the newly acquired reservation information;

024: calculating the difference value between the real-time queuing priority levels of the adjacent intelligent robots in the queuing queue;

025: when the difference value is larger than the preset difference value, the queuing number is kept unchanged; and

026: and when the difference value is smaller than the preset difference value, adjusting the queuing number.

In some embodiments, the calculation module 320 may also be configured to: calculating the real-time queuing priority of each intelligent robot according to the newly acquired reservation information; calculating the difference value between the real-time queuing priority levels of the adjacent intelligent robots in the queuing queue; when the difference value is larger than the preset difference value, the queuing number is kept unchanged; and when the difference value is smaller than the preset difference value, adjusting the queuing number. That is, the calculation module 320 may also be used to implement step 023, step 024, step 025, and step 026.

In some embodiments, the processor 10 may be further configured to: calculating the real-time queuing priority of each intelligent robot according to the newly acquired reservation information; calculating the difference value between the real-time queuing priority levels of the adjacent intelligent robots in the queuing queue; when the difference value is larger than the preset difference value, the queuing number is kept unchanged; and when the difference value is smaller than the preset difference value, adjusting the queuing number. That is, the processor 10 may also be used to implement step 023, step 024, step 025 and step 026.

Specifically, the work abnormality of the workstation 100 or the disorder of the queue caused by frequent changing of the queue number can be avoided, and the workstation 100 can not manage the intelligent robot. Therefore, the queuing number of the intelligent robot is adjusted only when the real-time queuing priority of the intelligent robot in the queuing queue changes greatly.

More specifically, after the workstation 100 reacquires the reservation information of the intelligent robots in the queuing queue, the workstation 100 recalculates the real-time queuing priority of each intelligent robot and calculates the difference between the real-time queuing priorities of the adjacent intelligent robots in the queuing queue, when the difference is greater than the preset difference, the queuing serial number of each intelligent robot is not modified, and when the difference is less than or equal to the preset difference, the queuing serial number of each intelligent robot is modified, so that the queuing serial number of the intelligent robot can be adjusted in time when the demand of the intelligent robot is greatly changed.

For example, in one embodiment, there are four intelligent robots in the queue of the workstation 100, which are the intelligent robot R1, the intelligent robot R2, the intelligent robot R3, and the intelligent robot R4, respectively, when sorting for the first time, the queue numbers of the intelligent robot R1, the intelligent robot R2, the intelligent robot R3, and the intelligent robot R4 are 1, 2, 3, and 4, respectively, the queue priority difference between the intelligent robot R1 and the intelligent robot R2 is 0.5, the queue priority difference between the intelligent robot R2 and the intelligent robot R3 is 1, and the queue priority difference between the intelligent robot R3 and the intelligent robot R4 is 2. It should be noted that the difference value refers to the queuing priority of the following intelligent robot minus the queuing priority of the preceding intelligent robot.

After the reservation information is obtained again, the real-time queuing priorities of the intelligent robot R1, the intelligent robot R2, the intelligent robot R3 and the intelligent robot R4 are recalculated, wherein the difference between the real-time queuing priorities of the intelligent robot R1 and the intelligent robot R2 is 0.5, the difference between the queuing priorities of the intelligent robot R2 and the intelligent robot R3 is-1, the difference between the priorities of the intelligent robot R3 and the intelligent robot R4 is-0.3, the queuing number between the intelligent robot R2 and the intelligent robot R3 is required to be adjusted on the assumption that the preset difference is-0.6 and only-1 is smaller than-0.6, and further the difference between the real-time queuing priority of the intelligent robot R3 and the real-time queuing priority of the intelligent robot R1 is-0.5, -0.5 > -0.6, and then the intelligent robot R3 is behind the intelligent robot R1, the adjusted intelligent robot R1, intelligent robot R2, intelligent robot R3 and intelligent robot R4 are 1, 3, 2 and 4, respectively.

In another embodiment, after the reservation information is obtained again, the real-time queuing priority of each intelligent robot is recalculated, the change difference between the real-time queuing priority of each intelligent robot and the corresponding queuing priority calculated last time (namely, the change difference of the queuing priority of each intelligent robot per se) is calculated, when the change difference is greater than the difference threshold, the difference between the change difference and the change difference of the queuing priority of the intelligent robot of the previous serial number is calculated, and if the difference is smaller than the preset difference, the queuing serial numbers of the intelligent robot and the intelligent robot of the previous serial number are modified; and if the difference value is larger than the preset difference value, not modifying the queuing serial numbers of the intelligent robot and the intelligent robot with the previous serial number.

Referring to FIG. 11, in some embodiments, step 030 includes the steps of:

031: inquiring whether the intelligent robot corresponding to the most front queuing serial number in the queuing queue uses the workstation 100;

032: when the intelligent robot replies that the workstation 100 needs to be used, the intelligent robot waits for use; and

033: when the intelligent robot replies that the workstation 100 is not needed to be used; or after the reply of the intelligent robot is not received after the preset time, calling the intelligent robot corresponding to the next queuing serial number in the queuing queue.

In some embodiments, the calling module 330 may also be configured to: inquiring whether the intelligent robot corresponding to the most front queuing serial number in the queuing queue uses the workstation 100; when the intelligent robot replies that the workstation 100 needs to be used, the intelligent robot waits for use; and when the intelligent robot replies that the workstation 100 is not needed to be used; or after the reply of the intelligent robot is not received after the preset time, calling the intelligent robot corresponding to the next queuing serial number in the queuing queue. That is, the calling module 330 can also be used to implement step 031, step 032, and step 033.

In some embodiments, the processor 10 may be further configured to query whether the intelligent robot corresponding to the top queue number in the queue uses the workstation 100; when the intelligent robot replies that the workstation 100 needs to be used, the intelligent robot waits for use; and when the intelligent robot replies that the workstation 100 is not needed to be used; or after the reply of the intelligent robot is not received after the preset time, calling the intelligent robot corresponding to the next queuing serial number in the queuing queue. That is, the processor 10 may also be used to implement step 031, step 032, and step 033.

After the intelligent robot sends the reservation information, the intelligent robot continues to execute the work task, if the intelligent robot finishes the work task in the queuing period and other factors do not need to be supplemented any more, for example, after the task of the intelligent robot is modified, the original work resource can enable the intelligent robot to finish the work task; alternatively, the work task of the intelligent robot is suspended or stopped, so that the intelligent robot does not need to perform the work task for a while. If the workstation 100 waits for the intelligent robot to go to use, the following intelligent robot cannot go to the workstation 100 for replenishment, and the working efficiency of the workstation 100 is directly affected. Therefore, by inquiring whether the intelligent robot uses the workstation 100 and not replying after the intelligent robot exceeds a predetermined time, the situation that the work efficiency of the workstation 100 is affected because the intelligent robot does not go to the workstation 100 can be avoided.

Specifically, after the workstation 100 recognizes that the intelligent robot currently using the workstation 100 uses the finished workstation 100, the workstation 100 will immediately call the intelligent robot with the highest queue number in the waiting queue to use the workstation 100. Firstly, the workstation 100 sends a request command to the intelligent robot with the most advanced queuing number, and inquires whether the intelligent robot uses the workstation 100 in the future, if the workstation 100 receives the reply of the intelligent robot and needs to use the workstation 100, the workstation 100 waits for the intelligent robot to use in the future and does not call the intelligent robot corresponding to the next queuing number; if the workstation 100 receives the reply of the intelligent robot and does not need to use the workstation 100, the workstation 100 calls the intelligent robot corresponding to the next queuing number for use, and the scheduling capability and the working efficiency of the workstation 100 are improved.

Further, the intelligent robot may be automatically shut down after the work is completed, or the intelligent robot may crash, which may cause the intelligent robot to fail to receive the request command sent by the workstation 100 and to reply to the workstation 100, and if the workstation 100 waits for the reply of the intelligent robot at this time, the work efficiency of the workstation 100 may be seriously affected. Therefore, the timing is started after the workstation 100 issues the request command, and if the reply of the intelligent robot is not received after the predetermined time period, the intelligent robot may be considered to be abnormal or not to use the workstation 100, and the workstation 100 calls the intelligent robot corresponding to the next queuing number to use the workstation 100.

The predetermined time period may be a fixed time period, such as a fixed time period of 30 seconds, 1 minute, 2 minutes, 3 minutes, 4 minutes, and the like. The predetermined time period may also be dynamically adjusted according to the distance between the intelligent robot and the workstation 100, for example, when the distance between the intelligent robot and the workstation 100 is short, the predetermined time period may be short, and when the distance between the intelligent robot and the workstation 100 is long, the predetermined time period may be long, so as to avoid that the workstation 100 makes an erroneous judgment due to a long time for data transmission that is too far away.

Referring to FIG. 12, in some embodiments, step 031 further includes the steps of:

0311: judging whether the workstation 100 is in an idle state; and

0312: while the workstation 100 is in the idle state, the intelligent robot is interrogated.

In some embodiments, the calling module 330 may also be configured to: judging whether the workstation 100 is in an idle state; and calls the intelligent robot while the workstation 100 is in an idle state. That is, the call module 330 may also be used to implement step 0311 and step 0312.

In some embodiments, the processor 10 may also be configured to determine whether the workstation 100 is in an idle state; and calls the intelligent robot while the workstation 100 is in an idle state. That is, the processor 10 may also be configured to implement step 0311 and step 0312.

Specifically, if the workstation 100 is not in an idle state, calling the intelligent robot for use before the intelligent robot is likely to result in the intelligent robot being unable to use after arriving, and having to wait, which will affect the working efficiency of the intelligent robot. Even if the current intelligent robot uses up the workstation 100, a user may insert another robot into the workstation 100 by hand, forcing the workstation 100 to enter a used state, and if the intelligent robot is called at the moment, the current intelligent robot cannot use the workstation 100, which affects the normal work of the current intelligent robot.

Therefore, before inquiring about the intelligent robot, it may be determined whether the workstation 100 is currently in an idle state, if the workstation 100 is in the idle state, it is inquired whether the intelligent robot uses the workstation 100, and if the workstation 100 is not currently in the idle state, it is not inquired whether the intelligent robot uses the workstation 100, until the workstation 100 is in the idle state, it is inquired whether the intelligent robot uses the workstation 100.

In some embodiments, the workstation 100 includes a plurality of different operating states, and the management method may further include: identifying the working state of the workstation; acquiring interactive data with the intelligent robot; and updating the working state according to the working state and the interactive data.

In some embodiments, the workstation 100 includes an idle state, a call state, a waiting state, and a use state, where the idle state of the workstation 100 may be a default state after the workstation 100 is powered on, the workstation 100 may switch to the waiting state and the use state in the idle state, and in the idle state, if the workstation 100 receives a first smart robot subscription, the workstation 100 may switch to the waiting state and then wait for the smart robot to use; if the user manually supplies the intelligent robot through the workstation 100 while in the idle state, the workstation 100 is switched to the use state.

Further, the workstation 100 calls the intelligent robot in the queue for use in the calling state, and enters the waiting state when the workstation 100 receives the reply from the intelligent robot and determines that the workstation 100 needs to be used. If the calling is overtime and no other waiting intelligent robot exists in the queue, the intelligent robot enters an idle state, and if the calling is overtime and other waiting intelligent robot exists in the queue, the next intelligent robot is continuously called.

When the workstation 100 waits for the intelligent robot to come into use in a waiting state, a waiting time is set, and if the workstation 100 does not wait for the intelligent robot after waiting for the waiting time and no other intelligent robot waiting in the queue exists, the workstation enters an idle state; if the workstation 100 does not wait for the intelligent robot after waiting for the waiting time and there are other waiting intelligent robots in the queue, the next intelligent robot is called in a calling state.

After the intelligent robot replies that the workstation 100 needs to use the workstation 100, the workstation 100 waits for the intelligent robot to come for use, however, the intelligent robot may accidentally come to the workstation 100 in the process of going to the workstation 100, and if the workstation 100 cannot know the abnormality of the intelligent robot in time and continues to wait for the coming of the intelligent robot, the coming supply of other intelligent robots in the queue is seriously affected. The waiting time can be calculated according to the feedback data sent to the workstation 100 by the intelligent robot; then, when the intelligent robot starts to send information that the intelligent robot starts to go to the workstation 100, elements such as a timing module in the workstation 100 may start to time, and if the intelligent robot does not reach the workstation 100 within the waiting time, it may be considered that the intelligent robot has an accident in the process of coming to the workstation 100 and cannot go to the workstation 100 any more

Specifically, the feedback data sent by the intelligent robot to the workstation 100 may include data such as a distance between the intelligent robot and the workstation 100, a driving speed of the intelligent robot, and the like, and then the workstation 100 may calculate a driving time required for the intelligent robot to drive to the workstation 100 according to the acquired distance information and the driving speed, so that the calculated waiting time is more accurate, and the workstation 100 can accurately judge whether the intelligent robot is abnormal.

Further, in the process that the intelligent robot travels to the workstation 100, the intelligent robot may need time to avoid an obstacle due to factors such as an additional obstacle, so that the intelligent robot cannot reach the workstation 100 within the calculated travel time, and if the travel time is taken as the waiting time, misjudgment is easy to occur, so that the replenishment efficiency of the intelligent robot is affected. Therefore, a predetermined time period can be set to provide a remaining time for unexpected factors which may occur when the intelligent robot goes to the workstation 100, so as to reduce the probability of misjudgment and further improve the accuracy of judgment. The waiting time can be obtained by adding a preset time length on the basis of the driving time length.

The use state, which may be triggered automatically or by human intervention, indicates that the workstation 100 is being used by the intelligent robot. When the workstation 100 is used by human intervention, after the intelligent robot is detected to leave the workstation 100 and other intelligent robots waiting in the queue are detected, the intelligent robot enters a calling state to call the next intelligent robot; and after detecting that the intelligent robot leaves the workstation 100 and no other intelligent robot waiting in the queue enters an idle state. Specifically, when the workstation 100 is manually intervened to enter the third state to supply supplies to the intelligent robot, the workstation 100 may detect whether the intelligent robot leaves the workstation 100 in real time or at certain intervals, so that the working state may be adjusted in time to provide services for other intelligent robots.

When the intelligent robot is automatically triggered to enter a use state, when the intelligent robot is detected to leave the workstation 100 and simultaneously receives an occupation canceling instruction sent by the intelligent robot, if no other intelligent robot waiting in a queue exists, the intelligent robot enters an idle state; and if other intelligent robots waiting in the queue exist, entering a calling state to call the next intelligent robot. The workstation 100 needs to detect whether the intelligent robot leaves the workstation 100 in real time or at a certain time interval in the replenishment process of the intelligent robot, and if it is detected that the intelligent robot has left the workstation 100 and simultaneously receives an instruction for canceling occupancy sent by the intelligent robot, it indicates that the intelligent robot has finished using the workstation 100, and the workstation 100 can release occupied resources.

However, it may happen that the intelligent robot does not send an instruction to cancel occupation to the workstation 100 after using the completion workstation 100, and if the workstation 100 considers that the intelligent robot does not use the completion workstation 100 at this time and does not call the next robot in the queue, time is wasted, thereby causing inefficiency in the work of the workstation 100. When the intelligent robot leaves the workstation 100 and does not receive an occupation canceling instruction sent by the intelligent robot, the intelligent robot enters a waiting state, the overtime duration is set, whether other intelligent robots waiting in the queuing queue exist or not is judged after the overtime duration, and if no other intelligent robots waiting in the queuing queue exist, the intelligent robot enters an idle state; and if other intelligent robots waiting in the queue exist, entering a calling state to call the next intelligent robot. By switching the state of the workstation 100, the stability of the workstation 100 during operation is improved

Referring to fig. 1 and fig. 2 again, the memory 20 is used for storing a computer program that can run on the processor 10, and the processor 10 executes the computer program to implement the management method in any of the above embodiments.

The memory 20 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory. Further, the workstation 100 may also comprise a communication interface 30, the communication interface 30 being used for communication between the memory and the processor 10.

If the memory 20, the processor 10 and the communication interface 30 are implemented independently, the communication interface 30, the memory 20 and the processor 10 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 2, but it is not intended that there be only one bus or one type of bus.

Optionally, in a specific implementation, if the memory 20, the processor 10, and the communication interface 30 are integrated on a chip, the memory 20, the processor 10, and the communication interface may complete communication with each other through an internal interface.

The processor 10 may be a Central Processing Unit (CPU) 1, or an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present Application.

Referring to fig. 13, a non-transitory computer-readable storage medium 400 according to an embodiment of the present application includes a computer program 401, which, when executed by one or more processors 500, causes the processors 500 to perform a management method according to any embodiment of the present application.

For example, referring to fig. 1 and fig. 4, when the computer program 401 is executed by the processor 500, the processor 500 is configured to perform the following steps:

For another example, referring to fig. 10, when the computer program 401 is executed by the processor 500, the processor 500 is configured to perform the following steps:

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.

The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium. The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.

In the description herein, reference to the description of the terms "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present application, "a plurality" means at least two, e.g., two, three, unless specifically limited otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.

Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations of the above embodiments may be made by those of ordinary skill in the art within the scope of the present application, which is defined by the claims and their equivalents.

Claims

1. A method of management, comprising:

receiving reservation information sent by one or more intelligent robots;

calculating a queuing serial number of each intelligent robot according to the reservation information; and

and calling the intelligent robots in sequence according to the queuing serial numbers.

2. The management method according to claim 1, wherein the calculating a queuing number of each of the intelligent robots according to the reservation information includes:

calculating the queuing priority of the intelligent robot according to the reservation information; and

and calculating the queuing sequence number of the intelligent robot in a queuing queue according to the queuing priority.

3. The method of managing of claim 2, wherein said calculating a priority of queuing of the intelligent robot based on the reservation information comprises:

acquiring service content required by the intelligent robot according to the reservation information; and

and calculating the queuing priority according to the service content required by the intelligent robot.

4. The management method according to claim 3, wherein when the service content includes a plurality of service sub-contents, different service sub-contents take different time, and the calculating the queuing priority according to the service content required by the intelligent robot includes:

judging whether the service contents have the service sub-contents which can be performed simultaneously; and

and if so, calculating the queuing priority by the service sub-content which consumes the longest time in the service sub-contents which can be simultaneously performed.

5. The management method according to claim 2, wherein the calculating the queuing number of the intelligent robot in a queuing queue according to the queuing priority comprises:

comparing the queuing priority of each intelligent robot; and

and determining the queuing sequence number of the intelligent robot in the queuing according to the comparison result.

6. The management method according to claim 2, wherein the management method further comprises:

and acquiring the reservation information of each intelligent robot in the queuing queue again at intervals of preset time.

7. The method according to claim 6, wherein calculating a queuing number of each of the intelligent robots according to the reservation information each time the reservation information of each of the intelligent robots in the queuing queue is retrieved comprises:

calculating the real-time queuing priority of each intelligent robot according to the obtained reservation information;

calculating the difference value between the real-time queuing priority levels of the adjacent intelligent robots in the queuing queue;

when the difference value is larger than a preset difference value, the queuing number is kept unchanged; and

and when the difference value is smaller than a preset difference value, adjusting the queuing number.

8. The management method according to claim 1, wherein said calling the intelligent robots in sequence according to the queuing number comprises:

inquiring whether the intelligent robot corresponding to the most front queuing serial number in the queuing queue uses a workstation or not;

waiting for the intelligent robot to use when the intelligent robot replies that the workstation needs to be used; and

when the intelligent robot replies that the workstation is not needed to be used; or after the preset time is exceeded and the reply of the intelligent robot is not received, calling the intelligent robot corresponding to the next queuing serial number in the queuing queue.

9. The method for managing according to claim 1, wherein said inquiring whether the intelligent robot corresponding to the top queuing number in the queuing queue uses a workstation further comprises:

judging whether the workstation is in an idle state or not; and

and inquiring the intelligent robot when the workstation is in an idle state.

10. A management device, comprising:

the receiving module is used for receiving reservation information sent by one or more intelligent robots;

the calculating module is used for calculating the queuing serial number of each intelligent robot according to the reservation information; and

and the first calling module is used for calling the intelligent robot in sequence according to the queuing sequence number.

11. A workstation, characterized in that it comprises:

one or more processors, memory; and

one or more programs, wherein the one or more programs are stored in the memory and executed by the one or more processors, the programs comprising instructions for performing the management method of any of claims 1 to 9.

12. A non-transitory computer-readable storage medium containing a computer program which, when executed by one or more processors, causes the processors to implement the management method of any one of claims 1 to 9.