CN114415610A

CN114415610A - Robot scheduling method and device, electronic equipment and storage medium

Info

Publication number: CN114415610A
Application number: CN202111630996.0A
Authority: CN
Inventors: 康昊
Original assignee: Shenzhen Ubtech Technology Co ltd
Current assignee: Shenzhen Ubtech Technology Co ltd
Priority date: 2021-12-28
Filing date: 2021-12-28
Publication date: 2022-04-29
Anticipated expiration: 2041-12-28
Also published as: CN114415610B

Abstract

The application is applicable to the technical field of robots and provides a robot scheduling method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring task data of a target task to be executed by a robot, wherein the task data comprises site information of an approach site; determining a target robot to be scheduled based on the station information; controlling the target robot to perform the target task. The target robot is determined by the path site information, so that the advantages of different types of paths different from the path site information can be fully exerted, and the running efficiency of the robot is improved.

Description

Robot scheduling method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of robot technologies, and in particular, to a robot scheduling method and apparatus, an electronic device, and a storage medium.

Background

In the field of storage logistics, more and more adopt the robot to realize work such as letter sorting, transportation, loading and unloading that acquire. Due to the limitation of storage environment and field and the increase of the number and the types of the robots, how to control the coordinated work of the robots and improve the operation efficiency of the robots becomes the problem to be solved

Disclosure of Invention

The embodiment of the application provides a robot scheduling method and device, electronic equipment and a storage medium, which can solve at least part of the problems.

In a first aspect, an embodiment of the present application provides a control method for a robot, including:

acquiring task data of a target task to be executed by a robot, wherein the task data comprises site information of an approach site;

determining a target robot to be scheduled based on the station information;

controlling the target robot to perform the target task.

It should be understood that, by determining the target robot through the station information, different types of advantages on paths differentiated from the station information can be fully exerted, and therefore, the operation efficiency of the robot is improved.

In a second aspect, an embodiment of the present application provides a control apparatus for a robot, including:

the robot comprises a task data acquisition module, a task data processing module and a task data processing module, wherein the task data acquisition module is used for acquiring task data of a target task to be executed by the robot, and the task data comprises site information of an approach site;

the target robot determining module is used for determining a target robot to be scheduled based on the station information;

and the target task execution module is used for controlling the target robot to execute the target task.

In a third aspect, an embodiment of the present application provides an electronic device, including:

a memory, a processor and a computer program stored in the memory and executable on the processor, the computer program, when executed by the processor, implementing the method steps of the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, including: the computer readable storage medium stores a computer program which, when executed by a processor, performs the method steps of the first aspect described above.

In a fifth aspect, embodiments of the present application provide a computer program product, which, when run on an electronic device, causes the electronic device to perform the method steps of the first aspect.

It is understood that the beneficial effects of the second aspect to the fifth aspect can be referred to the related description of the first aspect, and are not described herein again.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

FIG. 1 is a schematic illustration of a storage logistics system provided by an embodiment of the present application;

fig. 2 is a schematic flowchart of a scheduling method for a robot according to an embodiment of the present disclosure;

fig. 3 is a schematic flowchart of a scheduling method for a robot according to another embodiment of the present application;

fig. 4 is a schematic structural diagram of a scheduling apparatus of a robot according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".

Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.

Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.

Before describing the scheduling method of the robot provided in the embodiment of the present application, to facilitate understanding of the embodiment of the present application, the following describes the principle of the scheduling method of the robot provided in the embodiment of the present application and related concepts involved in the embodiment of the present application with reference to fig. 1.

Fig. 1 illustrates a robot scheduling system 10 according to an embodiment of the present disclosure. The system 10 includes: a central control device 110, a plurality of different types of robots 120.

Wherein the central control apparatus 110 communicates with a plurality of robots 120 of different types through a wireless communication network.

The central control device 110 may be a computer, including but not limited to a desktop computer, a notebook, a palm computer, and a cloud server.

Wherein a plurality of different types of robots 120, including but not limited to a roller-fed robot and a jack-up robot. The roller send the robot of type robot for containing the roller and send the robot of subassembly, jacking type robot is the robot that contains the jacking subassembly.

In the field of storage logistics, more and more adopt the robot to realize work such as letter sorting, transportation, loading and unloading that acquire. Different types of robots can often accomplish the task of transporting goods from point a to point B. Such as a roll-type robot and a jack-type robot, can perform the task of transporting the cargo from point a to point B. However, the two robots have the characteristics that the roller conveying robot has high automation degree and large conveying capacity because the roller conveying robot comprises the roller conveying assembly. Therefore, the lovers find out how to fully exert the working characteristics of the robots of different types, thereby improving the running efficiency of the robots.

In order to solve at least part of the above problems, embodiments of the present application provide a robot scheduling method, apparatus, electronic device, and storage medium.

Fig. 2 illustrates a method for scheduling a robot according to an embodiment of the present application, which is applied to the central control device 110 in the scheduling system of a robot illustrated in fig. 1, and can be implemented by software and/or hardware of the central control device 110. As shown in fig. 2, the method includes steps S110 to S130. The specific realization principle of each step is as follows:

s110, task data of a target task needing to be executed by the robot are obtained, and the task data comprise site information of an approach site.

In some embodiments, a warehouse management system is provided, and the warehouse management system is used for performing data collection management on the quantity of the goods in the warehouse and the logistics information, so that the state in the warehouse can be known clearly, and the goods can be supplemented in time. On the basis, the warehouse management system generates a task of carrying the goods and sends the task to the central control equipment. After receiving the task of carrying the goods, the central control equipment dispatches the task of carrying the goods to a corresponding robot to execute according to the robot scheduling strategy. The task that the robot is required to perform is called a target task.

In some embodiments, site information for the via site may be included in the task data, but is not limited to it. The station can be a pickup station or a put station, and the station information can not only include the station position, but also include the attribute of the station, that is, whether the action performed by the robot at the station is pickup or put, and the information of the specific goods performing the action; the station may also be a robotic energy supply station such as a hydrogen fueling point for a fuel cell robot, or a charging point for a rechargeable battery robot; the station can also be a temporary avoiding point which is temporarily used for preventing the temporary stop point arranged by collision between the robots when the robots are dispatched. The site information may include location information of the site, and the location information may be location information of the site in a map.

And S120, determining a target robot to be scheduled based on the station information.

In some embodiments, the central control apparatus may determine the target robot that needs to be scheduled based on the number of stations in the station information.

In a specific example, determining a target robot to be scheduled according to the station information includes steps S121 and S122.

And S121, determining the task type based on the station number in the station information, and determining the target robot type to be scheduled based on the task type.

The central control equipment determines a task type based on the number of the stations in the station information, and determines a target robot type to be scheduled based on the task type, and the method comprises the following steps: if the station information comprises more than two stations, the task type is a multi-point picking and placing task, and the type of the target robot needing to be scheduled is determined to be a roller conveying type robot; and if the station information only comprises two stations, the task type is an in-out warehouse task, and the target robot type needing to be scheduled is determined to be a jacking type robot.

Since the roller transfer robot includes the roller transfer module, if a plurality of stations are involved in a target task, for example, when goods at a loading/unloading station are transferred to a plurality of different warehouses, the multi-point transfer task can be completed by utilizing the characteristic of the roller transfer module of the roller transfer robot that the degree of automation is high.

If only two stations are involved in the target task, the characteristic that the jacking type robot has a large cargo carrying capacity can be utilized to finish the carrying of a large amount of cargos between the two stations at one time.

And S122, selecting the robot with the minimum cost for executing the target task from the target robot types as the target robot based on the station information.

In some embodiments, a robot that is less costly from the starting station in the station information may be selected as the target robot.

In other embodiments, the robot with the smallest total cost from the origin to the starting station, and through all stations in the station information, and finally back to the origin, may be selected as the target robot.

Where the minimum cost includes, but is not limited to, shortest distance, shortest time, or a weighted sum of time and distance.

In a specific example, the central control apparatus selects, as the target robot, a robot having a smallest cost for performing the target task among the target robot types based on the station information, including: determining an initial site according to the site information; a recursive calling mode is adopted, the starting station is used as a center, the searching range is gradually expanded by preset step length, and the candidate robot of the target robot type is searched; calculating the cost of each candidate robot for reaching the starting station; and taking the candidate robot with the minimum cost as the target robot.

The central control device uses the initial station as a center in a recursion calling mode, gradually enlarges the search range by using a preset step length, and searches for the candidate robot of the target robot type, and the method can comprise the following steps: searching candidate robots within the radius range by taking the initial station as a center and a preset step length as a radius; if the target robot is not found, increasing a preset step length by the original radius to serve as a new search radius, searching the candidate robot within the radius range, and gradually expanding the search range in a recursive increase mode until the map is completely covered or the target robot is found, and stopping searching.

In the embodiment of the application, if a task to be executed is received, the logic of a 'task point selection robot' is adopted, that is, a recursion calling mode is adopted, the task point is taken as a circle center, for example, a starting point, small robots which accord with the state of executing the task in a diffusion checking range are adopted, the actual path cost of the small robots reaching the task point is calculated, and the small robot with the minimum cost is selected, so that the condition that the small robot empty robot goes to a target point is reduced.

S130, controlling the target robot to execute the target task.

In some embodiments, the central control apparatus controls the target robot to perform the target task. Specifically, the central control device may control the target robot to approach each station in the task data from a start point of the task data according to the task data of the target task, and complete the loading and unloading operation indicated by the task data.

In some specific examples, if the target robot type is a roll-fed robot, controlling the target robot to perform the target task includes: according to the station information, determining a goods taking station and a goods placing station in the target task; generating a task string according to the position information of the picking station and the putting station, wherein the task string comprises a path sequence of the picking station and the putting station which enables the power loss of the target robot to be minimum; and controlling the target robot to execute the target tasks according to the path sequence in the task string.

The central control device distributes the multi-point picking and placing tasks to the robots in the form of task strings. For example, when two goods need to be fetched at A, B, two goods are placed at C and two goods are placed at D, the central control device will automatically generate a task string as [ a, B, D, C ] according to the mapping relationship of the goods.

It should be noted that the task string arrangement should result in low robot power consumption. Specifically, the task strings may be combined by using an optimization algorithm, so that the sum of the length of each route multiplied by the cargo load is minimized, and each route refers to a route between two stations. Of course, other optimization algorithms that minimize robot power consumption may be used to combine task strings.

The central control equipment selects the roller-type robot with the roller-type conveying assembly to carry out tasks, and can preferentially go to a local roller-type conveying object which needs to put down the goods at the earliest in order to avoid power loss caused by load goods transportation, so that the load is reduced, and the endurance is prolonged. After the task string is generated, the central control equipment also completes the functions of path planning, traffic control and the like so as to guide the target robot to complete the task.

In some specific examples, if the target robot type is a jack-up type robot, the pathway station includes a first station and a second station; controlling the target robot to perform the target task, comprising: controlling the target robot to go to the first station and keeping the target robot in a jacking idle state; and if the target robot stays at the first station for more than a preset time or the picking state reaches a preset threshold value, controlling the target robot to move to the second station.

When the task is a jacking task from a point A to a point B, the actual scene of the task is generally an in-out warehouse task. For example, the robot goes to point a when empty, jacks up the goods shelf, and then goes to point B to get out of the warehouse for loading. Namely, the storeroom at the point A is loaded with goods, and the loaded goods are transferred to the freight car for delivery from the storeroom at the point B.

Taking the robot to execute the warehouse-out task as an example, after the robot arrives at the point B and finishes the shipment, the central control device enables the robot to slightly wait at the point B. Because the general warehouse entry and exit task is tidal, warehouse entry is usually performed when warehouse exits. Since the warehousing task has a tidal effect, that is, such tasks are concentrated in a specific time period. If the robot goes to the storage area with a small amount of goods, the robot may receive the next storage task in the middle.

In some embodiments, the robot needs to complete loading at point B, and the central control device keeps the robot in a jacking idle state, that is, in a jacking waiting state. The robot stays at the position, and the robot goes to the point A only when the preset time is exceeded or the picking state reaches the preset threshold value. The picking state reaches a preset threshold value, including but not limited to the weight of goods borne by the robot exceeding a preset weight, or the occupied number of shelves borne by the robot exceeding a preset occupied number. I.e. the robot has been loaded with sufficient goods.

According to the embodiment of the application, the robot is kept in the jacking idle state at the first station until enough goods are loaded or the preset time is exceeded, so that the situation that the robot is on the way when the goods need to be put in storage can be avoided. Therefore, the robot is prevented from running in a road network in an idle mode.

It should be understood that the above example can also be implemented in the warehousing task from point B to point a, i.e. from the ex-warehouse to the warehouse, and will not be described in detail. Since the point of departure is a centralized dispatch point for robots and vehicles, in some embodiments, the robot waits at the point of departure and no longer waits at the garage area.

On the basis of the above embodiment of the robot scheduling method shown in fig. 2, step S130 is to control the target robot to perform the target task, as shown in fig. 3, further comprising steps S310 to S340:

and S310, acquiring the operation information of the target robot, wherein the operation information comprises the position information and the speed information of the robot.

In some embodiments, each robot reports operation information to the central control device during operation, where the operation information includes, but is not limited to, position information, speed information, and other operation information. The central control equipment acquires the running information reported by the robot through a wireless communication network.

S320, estimating a time window of each station of the target robot occupation path based on the operation information and the station information, wherein the starting point of the time window enters the station for the first time, and the end point of the time window is the second time of leaving the station

In some embodiments, the central control device performs route finding according to the start point position of each robot and the position of the relevant task target point during path planning, and according to the road-network communication relationship and the dynamic obstacles on the road network, and through an improved a-star route finding algorithm, obtains an initial running path of the robot.

The central control equipment estimates the running speed of the robot and the time required for reaching each station so as to obtain the time node of each station occupied by the target robot; that is, by obtaining such data for all robots, the time nodes at which all robots enter and leave the respective stations are known. Of course, the time nodes of the respective stations where the target robot enters and leaves its way, i.e. the time windows of the respective stations where it occupies the way, are included.

The A star path finding algorithm is used as the path planning algorithm. The central control equipment can plan the moving path of each robot according to the current position and the target position of each robot and the improved A star road finding algorithm.

The improved A-star path finding algorithm provided by the embodiment of the application does not improve the algorithm processing flow, and the improved A-star path finding algorithm still uses the algorithm processing flow of the existing A-star path finding algorithm. In fact, the improved a-star way finding algorithm improves the calculation of the total mobile cost for the application scenario of the present application. Or the improved A star path finding algorithm specifically changes the path score calculation formula.

The improved calculation formula of the total moving cost of the A satellite routing algorithm is as follows: f ═ G + H.

Wherein F represents the total movement cost, or path score; g represents the sum of products of actual consumption of each road section and a corresponding road section coefficient in an actual path of the currently judged point from the current position, wherein the road section coefficient is used for representing the current occupied condition of the road section; h represents the estimated cost of the currently determined point and the target position of the robot, or the cost of the estimated path of the currently determined point from the target position. For example, when a road segment is unoccupied, its road segment coefficient may be equal to 1; when a road segment is occupied, its road segment coefficient may be greater than 1, for example, may be 1.5.

S330, in the process of the target robot moving, whether a conflict robot exists in the time window of the next station is detected, and the conflict robot is a robot with a time period overlapping the time window of the next station and the time window of the target robot.

In some embodiments, the target task being performed by the target robot includes 2 or more stations, and the station to which the target robot is about to arrive during the traveling process is the next station.

In some embodiments, multiple robots perform different tasks in a warehouse, sometimes these tasks may involve the same site, e.g., a stock site with a sudden increase in sales. If multiple robots enter and exit the station in the same time slot, that is, the time slots of the multiple robots entering and leaving the station are completely or partially overlapped, congestion is easily caused.

In the embodiment of the application, the central control device detects whether a conflict robot exists in a time window for entering the next station or not in the process of the target robot traveling, and the conflict robot is a robot with a time window having a time period coinciding with that of the target robot.

And S340, if the conflict robot exists, determining the sequence of entering the next station according to the priority of the target robot and the conflict robot.

In some implementations, the central control device may assign priorities to the various robots based on the importance of the tasks. The importance degree of the tasks can be sorted according to the time limit of the tasks and also according to the quantity of goods related in the tasks, and the application is not particularly limited.

In a specific example, the central control device judges that time windows of more than two robots occupying the same station overlap, in order to avoid congestion of the station, according to the priority of each robot, the station with high priority is indicated to enter the station first, and the robot with low priority waits at the previous station, or stops along the way to wait or waits at a reduced speed.

It will be appreciated that if a robot with a low priority is waiting at an upper station, or is waiting at a stop along the way or is waiting at a reduced speed, its path is recalculated for that robot, and the time window that the robot occupies each station of its path is recalculated.

It can be understood that if there is no conflict robot, the target robot directly enters the next station according to the originally planned path.

It should be understood that the time windows of the robots at the same station do not overlap with each other through the embodiment, so that congestion caused by collision of routes of multiple robots is avoided.

Corresponding to the scheduling method for the robot shown in fig. 2, fig. 4 shows a scheduling apparatus M100 for a robot according to an embodiment of the present application, including:

the task data acquiring module M110 is configured to acquire task data of a target task that needs to be executed by the robot, where the task data includes site information of an approach site.

And a target robot determining module M120, configured to determine a target robot to be scheduled based on the station information.

A target task execution module M130, configured to control the target robot to execute the target task.

Optionally, the target robot determining module is configured to determine, based on the station information, a target robot to be scheduled, and specifically configured to: determining a task type based on the number of stations in the station information, and determining a target robot type to be scheduled based on the task type; and selecting the robot with the minimum cost for executing the target task from the target robot types as the target robot based on the station information.

Optionally, the target robot determining module is configured to select, based on the station information, a robot with a minimum cost for executing the target task from among target robot types, and as the target robot, the target robot determining module is specifically configured to: determining an initial site according to the site information; a recursive calling mode is adopted, the starting station is used as a center, the searching range is gradually expanded by preset step length, and the candidate robot of the target robot type is searched; calculating the cost of each candidate robot for reaching the starting station; and taking the candidate robot with the minimum cost as the target robot.

Optionally, the target robot determining module is configured to determine a task type based on the number of stations in the station information, and determine a target robot type to be scheduled based on the task type, and is specifically configured to: if the station information comprises more than two stations, the task type is a multi-point picking and placing task, and the type of the target robot needing to be scheduled is determined to be a roller conveying type robot; and if the station information only comprises two stations, the task type is an in-out warehouse task, and the target robot type needing to be scheduled is determined to be a jacking type robot.

Optionally, the target task execution module is configured to control the target robot to execute the target task if the target robot is a roller-type robot, and specifically configured to: according to the station information, determining a goods taking station and a goods placing station in the target task; generating a task string according to the positions of the picking station and the putting station, wherein the task string comprises a path sequence of the picking station and the putting station which enables the power loss of the target robot to be minimum; and controlling the target robot to execute the target tasks according to the path sequence in the task string.

Optionally, the target task execution module is configured to, if the target robot is a jacking robot, the approach station includes a first station and a second station; controlling the target robot to perform the target task, in particular for: controlling the target robot to go to the first station and keeping the target robot in a jacking idle state; and if the target robot stays at the first station for more than a preset time or the picking state reaches a preset threshold value, controlling the target robot to move to the second station.

Optionally, the target task execution module is further configured to: acquiring operation information of the target robot, wherein the operation information comprises position information and speed information of the robot; estimating a time window of each station of the target robot occupation route based on the operation information and the station information, wherein the starting point of the time window enters the station for the first time, and the end point of the time window is the second time of leaving the station; detecting whether a conflict robot exists in a time window of entering a next station or not in the process of the target robot moving, wherein the conflict robot is a robot of which the time window of entering the next station and the time window of the target robot have a superposition time period; and if the conflict robot exists, determining the sequence of entering the next station according to the priority of the target robot and the priority of the conflict robot.

It is understood that various embodiments and combinations of the embodiments in the above embodiments and their advantages are also applicable to this embodiment, and are not described herein again.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device is used to implement the central control device 110 described above. As shown in fig. 5, the electronic device D10 of this embodiment includes: at least one processor D100 (only one is shown in fig. 5), a memory D101, and a computer program D102 stored in the memory D101 and operable on the at least one processor D100, wherein the processor D100 implements the steps of any of the method embodiments described above when executing the computer program D102.

The electronic device D10 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The electronic device may include, but is not limited to, a processor D100, a memory D101. Those skilled in the art will appreciate that fig. 5 is merely an example of the electronic device D10 and does not constitute a limitation of the electronic device D10, and may include more or fewer components than those shown, or some components in combination, or different components, such as input output devices, network access devices, etc.

Processor D100 may be a Central Processing Unit (CPU), and Processor D100 may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The storage D101 may be an internal storage unit of the electronic device D10 in some embodiments, such as a hard disk or a memory of the electronic device D10. In other embodiments, the memory D101 may also be an external storage device of the electronic device D10, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device D10. Further, the memory D101 may also include both an internal storage unit and an external storage device of the electronic device D10. The memory D101 is used for storing an operating system, an application program, a BootLoader (BootLoader), data, and other programs, such as program codes of the computer programs. The memory D101 may also be used to temporarily store data that has been output or is to be output.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments may be implemented.

Embodiments of the present application provide a computer program product, which when executed on an electronic device, enables the electronic device to implement the steps in the above method embodiments.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signal, telecommunication signal, and software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

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, may be located in one place, or may be 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.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims

1. A method for scheduling a robot, comprising:

determining a target robot to be scheduled based on the station information;

controlling the target robot to perform the target task.

2. The scheduling method of claim 1 wherein determining the target robot to be scheduled based on the station information comprises:

determining a task type based on the number of stations in the station information, and determining a target robot type to be scheduled based on the task type;

and selecting the robot with the minimum cost for executing the target task from the target robot types as the target robot based on the station information.

3. The scheduling method of claim 2 wherein selecting, as a target robot, a robot having a smallest cost for performing the target task among target robot types based on the station information comprises:

determining an initial site according to the site information;

a recursive calling mode is adopted, the starting station is used as a center, the searching range is gradually expanded by preset step length, and the candidate robot of the target robot type is searched;

calculating the cost of each candidate robot for reaching the starting station;

and taking the candidate robot with the minimum cost as the target robot.

4. The scheduling method of claim 2 wherein determining a task type based on the number of stations in the station information and determining a target robot type to be scheduled based on the task type comprises:

if the station information comprises more than two stations, the task type is a multi-point picking and placing task, and the type of the target robot needing to be scheduled is determined to be a roller conveying type robot;

and if the station information only comprises two stations, the task type is an in-out warehouse task, and the target robot type needing to be scheduled is determined to be a jacking type robot.

5. The scheduling method of claim 4 wherein if the target robot type is a roll-fed robot, controlling the target robot to perform the target task comprises:

according to the station information, determining a goods taking station and a goods placing station in the target task;

generating a task string according to the positions of the picking station and the putting station, wherein the task string comprises a path sequence of the picking station and the putting station which enables the power loss of the target robot to be minimum;

and controlling the target robot to execute the target tasks according to the path sequence in the task string.

6. The scheduling method of claim 4 wherein if the target robot type is a jack-up type robot, the approach station comprises a first station and a second station; controlling the target robot to perform the target task, comprising:

controlling the target robot to go to the first station and keeping the target robot in a jacking idle state;

and if the target robot stays at the first station for more than a preset time or the picking state reaches a preset threshold value, controlling the target robot to move to the second station.

7. The scheduling method of claim 4 wherein controlling the target robot to perform the target task further comprises:

acquiring operation information of the target robot, wherein the operation information comprises position information and speed information of the robot;

estimating a time window of each station of the target robot occupation route based on the operation information and the station information, wherein the starting point of the time window is the first time of entering the station, and the end point of the time window is the second time of leaving the station;

detecting whether a conflict robot exists in a time window of entering a next station or not in the process of the target robot moving, wherein the conflict robot is a robot of which the time window of entering the next station and the time window of the target robot have a superposition time period;

and if the conflict robot exists, determining the sequence of entering the next station according to the priority of the target robot and the priority of the conflict robot.

8. A robot scheduling apparatus, comprising:

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the scheduling method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the scheduling method according to any one of claims 1 to 7.