CN114415610B

CN114415610B - Scheduling method and device for robot, electronic equipment and storage medium

Info

Publication number: CN114415610B
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: 2023-08-15
Anticipated expiration: 2041-12-28
Also published as: CN114415610A

Abstract

The application is suitable for the technical field of robots, and provides a scheduling method and device for robots, 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 a path site; determining a target robot to be scheduled based on the site information; and controlling the target robot to execute the target task. The target robot is determined through the path site information, so that the advantages of different types on the paths with different site information can be fully exerted, and the running efficiency of the robot is further improved.

Description

Scheduling method and device for robot, electronic equipment and storage medium

Technical Field

The application belongs to the technical field of robots, and particularly relates to a scheduling method and device for robots, electronic equipment and a storage medium.

Background

In the field of warehouse logistics, robots are increasingly adopted to realize the acquired sorting, transporting, loading and unloading and other works. Due to the limitation of storage environment sites and the increase of the number and the types of robots, how to control the coordinated work of the robots, the operation efficiency of the robots is improved, and the problem to be solved is solved

Disclosure of Invention

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

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

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

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

and controlling the target robot to execute the target task.

It is understood that the target robot is determined through the path site information, so that the advantages of different types on paths different from the site information can be fully exerted, and the running efficiency of the robot is improved.

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

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

the target robot determining module is used for determining a target robot to be scheduled based on the site 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, which when executed by the processor, performs the method steps of the first aspect described above.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium comprising: the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method steps of the first aspect described above.

In a fifth aspect, embodiments of the present application provide a computer program product for causing an electronic device to carry out the method steps of the first aspect described above when the computer program product is run on the electronic device.

It will be appreciated that the advantages of the second to fifth aspects may be found in the relevant description of the first aspect, and are not described here again.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of a warehouse logistics system according to an embodiment of the present application;

fig. 2 is a flow chart of a scheduling method of a robot according to an embodiment of the present application;

fig. 3 is a flow chart of a scheduling method of a robot according to another embodiment of the present application;

fig. 4 is a schematic structural diagram of a dispatching device of a robot according to an embodiment of the present application;

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 the particular system architecture, 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 should 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 the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

As used in the present description and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".

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

Reference in the 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 application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

Before explaining a scheduling method of a robot provided in an embodiment of the present application, for convenience in understanding the embodiment of the present application, a principle of the scheduling method of a robot provided in the embodiment of the present application and related concepts related to the embodiment of the present application are described below with reference to fig. 1.

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

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

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

Wherein a plurality of robots 120 of different types including, but not limited to, a roll-to-roll type robot and a lift-up type robot. The roll-feeding robot is a robot comprising a roll-feeding assembly, and the jacking robot is a robot comprising a jacking assembly.

In the field of warehouse logistics, robots are increasingly adopted to realize the acquired sorting, transporting, loading and unloading and other works. Different types of robots often can accomplish the task of transporting cargo from point a to point B. For example, both roll-on robots and lift-off robots can accomplish the task of transporting goods from point a to point B. However, the two robots are characterized in that the roller-feeding type robot has high degree of automation and large carrying capacity due to the inclusion of the roller-feeding assembly. Therefore, the inventor of the application discovers how to fully develop the working characteristics of robots of different types, thereby improving the operation efficiency of the robots.

In order to solve at least part of the problems, the embodiment of the application provides a scheduling method and device of a robot, electronic equipment and a storage medium.

Fig. 2 illustrates a method for scheduling robots according to an embodiment of the present application, which is applied to the central control device 110 in the scheduling system of the robots illustrated in fig. 1 and may 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 implementation principle of each step is as follows:

s110, task data of a target task to be executed by the robot is acquired, wherein the task data comprises site information of a path site.

In some embodiments, a warehouse management system is provided, and the warehouse management system is used for carrying out data collection management on the quantity of cargoes and logistics information in a warehouse, so that the state in the warehouse can be clearly known, and the cargoes can be timely supplemented. On the basis, the warehouse management system generates a task of carrying cargoes and transmits the tasks to the central control equipment. After receiving the task of carrying the goods, the central control equipment distributes the task of carrying the goods to the corresponding robots for execution according to the robot scheduling strategy. The task that needs to be performed by the robot is called a target task.

In some embodiments, the task data may include, but is not limited to, site information for the pathway site. The site may be a picking site or a placing site, and at this time, the site information may not only include the site location, but also include the attribute of the site, that is, the action performed by the robot at the site is picking or placing, and the information of the specific goods performing the action; the station may also be a robotic energy replenishment station such as a hydrogen fueling point of a fuel cell robot, or a charging point of a rechargeable battery robot; the stations may also be temporary avoidance points, temporary stop points that are temporarily used to prevent collision settings between robots when the robots are scheduled. The site information may include location information of the site, which may be location information of the site in a map.

S120, determining the target robot to be scheduled based on the site information.

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

In a specific example, the target robot to be scheduled is determined according to the site information, including steps S121 and S122.

S121, determining task types based on the number of stations in the station information, and determining target robot types to be scheduled based on the task types.

The central control device determines a task type based on the number of stations in the station information and determines a target robot type to be scheduled based on the task type, and the central control device comprises: if the site information contains more than two sites, the task type is a multi-point picking and placing task, and the type of the target robot to be scheduled is determined to be a roll-feeding robot; if the site information only comprises two sites, the task type is a warehouse-in and warehouse-out task, and the type of the target robot to be scheduled is determined to be a jacking type robot.

Since the roll-feeding robot includes the roll-feeding unit, if a plurality of stations are involved in a target task, for example, goods at a loading/unloading station are sent to a plurality of different warehouses, the task of multipoint conveyance can be completed by utilizing the characteristic that the roll-feeding unit of the roll-feeding robot has high automation degree.

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

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

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

In other embodiments, a robot with the smallest total cost of going back to the departure point may be selected as the target robot from the departure point to the start station, and through all stations in the station information.

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

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

The central control device adopts a recursive call mode to use the initial station as a center, enlarges the searching range step by step with a preset step length, and searches the candidate robots of the target robot type, which can comprise: searching candidate robots within the radius range by taking the initial station as a center and taking a preset step length as a radius; if the map is not found, the original radius is increased by a preset step length to serve as a new searching radius, candidate robots in the radius range are searched, the searching range is expanded step by step in a recursion growth mode, and searching is stopped until the map is completely covered or a target robot is found.

In the embodiment of the application, if the task to be executed is received, logic of 'task point selection robot' is adopted, namely, a recursion calling mode is adopted to take the task point as a circle center, for example, small robots which accord with the task executing state in the diffusion inspection range are used as starting points, 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 is driven to the target point is reduced.

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

In some embodiments, a central control device controls the target robot to perform the target task. Specifically, the central control device may control the target robot to get the loading and unloading actions indicated by the complete task data from the starting point of the task data to each site in the task data according to the task data of the target task.

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 site information, determining a picking site and a placing site in the target task; generating a task string according to the position information of the picking station and the placing station, wherein the task string comprises a path sequence of the picking station and the placing station which minimizes the power loss of the target robot; and controlling the target robot to execute target tasks according to the path sequence in the task string.

The central control device distributes the tasks of multi-point picking and placing to the robots in the form of task strings. For example, when the goods are required to be taken at two points A, B, the goods are required to be placed at the point C, the goods are required to be placed at the point B, and the goods are required to be placed at the point D, the central control device automatically generates the task string as [ A, B, D, C ] according to the mapping relation of the goods.

It should be noted that the task strings should be arranged so that the robot has a small power loss. Specifically, an optimization algorithm is adopted to combine the task strings, so that the sum of the length of each path multiplied by the cargo load is minimum, and each path refers to the path between two stations. Of course, other optimization algorithms that minimize the power loss of the robot may be used to combine the task strings.

The central control equipment selects the roll-type robot with the roll-type assembly to carry out tasks, so that power loss caused by load cargo transportation is avoided, the roll-type robot can preferentially go to a place where the cargo is required to be put down at the earliest time, and therefore 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 lift-up robot, the pathway station includes a first station and a second station; controlling the target robot to execute the target task, including: controlling the target robot to go to the first station and keeping the target robot in a lifting idle state; and if the target robot stays at the first station for more than a preset time period or the picking state reaches a preset threshold value, controlling the target robot to go to the second station.

When the task is a jacking task from the point A to the point B, the actual scene of the task is generally an in-out task. For example, the robot is unloaded to point a, jack up the shelf, and then go to point B to leave the warehouse and load. Namely, the warehouse at the point A loads cargoes, and the loaded cargoes are transported to the truck for delivery at the point B.

Taking the robot to execute the ex-warehouse task as an example, when the robot arrives at the point B and the delivery is completed, the central control equipment enables the robot to wait slightly at the point B. Because the general warehouse-in and warehouse-out task is tidal, warehouse-in and warehouse-out are generally available. Since the warehouse entry tasks have a tidal effect, that is, such tasks may occur in a concentrated manner over a particular period of time. If the robot is going to the warehouse area with a small amount of goods, it may be on the way to the next warehouse-in task.

In some embodiments, the robot needs to complete loading at point B, at which point the central control device will keep the robot in an idle state for jacking, i.e. in a state waiting for jacking. The robot stays at the position for longer than a preset time period, or the picking state reaches a preset threshold value to go to the point A. Wherein the pick status reaches a preset threshold, including but not limited to the robot bearing a weight of the load exceeding a preset weight, or the robot bearing a number of placements of the shelves exceeding a preset number of placements. That is to say that the robot has been loaded with a sufficient amount of cargo.

According to the embodiment of the application, the robot is kept in the lifting idle state at the first station until enough cargoes are loaded or the preset time is exceeded, so that the condition that the robot is still on a driving road when cargoes need to be put in storage can be avoided. Therefore, the embodiment of the application avoids the condition that the robot runs on the road network in an idle mode.

It should be understood that the above example may be implemented in the task of warehousing from point B to point a, that is, from the point of departure to the warehouse, and will not be repeated. Since the departure point is a centralized dispatch point for robots and vehicles, in some embodiments, robots wait at the departure point and no longer wait at the storage area.

On the basis of the method embodiment of robot scheduling shown in fig. 2, step S130 controls the target robot to execute the target task, as shown in fig. 3, and further includes steps S310 to S340:

s310, acquiring operation information of the target robot, wherein the operation information comprises position information and speed information of the robot.

In some embodiments, each robot reports operational information to the central control device during operation, including but not limited to, location information, speed information, etc. The central control equipment acquires operation information reported by the robot through a wireless communication network.

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

In some embodiments, when the central control device performs path planning, the central control device performs path searching according to the starting point position of each robot and the position of the related task target point, according to the road network communication relationship and the dynamic obstacle on the road network, and obtains an initial running path of the robot through the improved A star path searching algorithm.

The central control equipment obtains the time node of each station occupied by the target robot by estimating the running speed of the robot and the time required for reaching each station; that is, the time nodes of all robots at the entry and exit to the respective sites are known by obtaining such data of all robots. Of course, the time nodes of each station of the path that the target robot enters and leaves, i.e. the time windows of each station of the path that it occupies, are included therein.

The star-a routing algorithm is used as a path planning algorithm. The central control device can plan the moving path of each robot according to the current position, the target position and the improved A star routing algorithm of each robot.

The improved A star routing algorithm provided by the embodiment of the application does not improve the algorithm processing flow, and the improved A star routing algorithm still maintains the algorithm processing flow of the existing A star routing algorithm. In practice, the improved star-a road-finding algorithm improves the calculation of the total movement cost for the application scene of the application. Or, the improved A star routing algorithm specifically changes the path scoring calculation formula.

The calculation formula of the total movement cost of the improved A star 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 corresponding road section coefficients in an actual path of the currently judged point from the current position, wherein the road section coefficients are used for representing the current occupied condition of the road section; h represents the estimated cost of the currently judged point and the target position of the robot, or the estimated path cost of the currently judged point from the target position. For example, when a road segment is unoccupied, its road segment coefficient may be equal to 1; when the road section is occupied, the road section coefficient thereof may be greater than 1, for example, may be 1.5.

S330, detecting whether a conflict robot exists in a time window entering the next station in the process of moving the target robot, wherein the conflict robot is a robot with a time period of coincidence between the time window entering 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 that the target robot is about to reach during the traveling is the next station.

In some embodiments, multiple robots perform different tasks in a warehouse, which may sometimes involve the same site, e.g., a commodity site with a sudden increase in sales. If multiple robots enter and exit the station in the same time period, that is, if all or part of the time periods of entering and leaving the station overlap, congestion is easily caused.

In the embodiment of the application, the central control equipment detects whether a conflict robot exists in a time window entering the next station or not in the process of the target robot, and the conflict robot is a robot of which the time window is coincident with the time window of the target robot.

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

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

In a specific example, the central control device determines that there is an overlap between time windows when more than two robots occupy the same station currently, and in order to avoid congestion at the station, according to priorities of the robots, instructs a station with a high priority to enter the station first, and the robot with a low priority waits at the last station, or waits at a stop or waits at a slow speed along the way.

It will be appreciated that if a robot of low priority waits at a previous station, or parks down or waits at a slow down, then its path of travel is recalculated for that robot, and the time window for the robot to occupy each station of its path is recalculated.

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

It should be understood that, by the embodiment, the time windows of the robots at the same site are not overlapped, so that congestion caused by multi-robot route conflict is avoided.

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

the task data acquisition 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 a path site.

The target robot determining module M120 is configured to determine a target robot that needs to be scheduled based on the site information.

And the target task execution module M130 is used for controlling the target robot to execute the target task.

Optionally, the target robot determining module is configured to determine, based on the site information, a target robot to be scheduled, 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 a robot with the minimum cost for executing the target task from the target robot type based on the site information as a target robot.

Optionally, the target robot determining module is configured to select, based on the site information, a robot with the minimum cost for executing the target task in a target robot type as a target robot, and specifically is configured to: determining an initial site according to the site information; the recursion calling mode is adopted, the initial station is taken as the center, the searching range is gradually expanded by a preset step length, and candidate robots of the target robot type are searched; calculating the cost of each candidate robot reaching the starting site; and taking the candidate robot with the minimum cost as a 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, specifically configured to: if the site information contains more than two sites, the task type is a multi-point picking and placing task, and the type of the target robot to be scheduled is determined to be a roll-feeding robot; if the site information only comprises two sites, the task type is a warehouse-in and warehouse-out task, and the type of the target robot 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 roll-fed robot, and is specifically configured to: according to the site information, determining a picking site and a placing site in the target task; generating a task string according to the positions of the pick-up station and the put-in station, wherein the task string comprises a path sequence of the pick-in station and the put-in station for minimizing the power loss of the target robot; and controlling the target robot to execute target tasks according to the path sequence in the task string.

Optionally, the target task execution module is configured to, if the target robot type is a jacking robot, enable the route station to include a first station and a second station; the target robot is controlled to execute the target task, and the target task is specifically used for: controlling the target robot to go to the first station and keeping the target robot in a lifting idle state; and if the target robot stays at the first station for more than a preset time period or the picking state reaches a preset threshold value, controlling the target robot to go 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 path occupied by the target robot based on the operation information and the station information, wherein the starting point of the time window enters the first time of the station, and the end point of the time window is the second time leaving the station; in the process of moving the target robot, detecting whether a conflict robot exists in a time window entering the next station, wherein the conflict robot is a robot with a time period of coincidence between the time window entering the next station and the time window of the target robot; and if the conflict robot exists, determining the sequence of entering the next station according to the priorities of the target robot and the conflict robot.

It will be appreciated that various implementations and combinations of implementations and advantageous effects thereof in the above embodiments are equally applicable to this embodiment, and will not be described here 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 executable on the at least one processor D100, the processor D100 implementing the steps in any of the various method embodiments described above when executing the computer program D102.

The electronic device D10 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The electronic device may include, but is not limited to, a processor D100, a memory D101. It will be appreciated by those skilled in the art that fig. 5 is merely an example of the electronic device D10 and is not meant to be limiting of the electronic device D10, and may include more or fewer components than shown, or may combine certain components, or different components, such as may also include input-output devices, network access devices, etc.

The processor D100 may be a central processing unit (Central Processing Unit, CPU), the processor D100 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory D101 may in some embodiments be an internal storage unit of the electronic device D10, such as a hard disk or a memory of the electronic device D10. The memory D101 may also be an external storage device of the electronic device D10 in other embodiments, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the 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 boot loader (BootLoader), data, other programs, etc., such as program codes of the computer program. 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 number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.

It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein.

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

Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the respective method embodiments described above.

Embodiments of the present application provide a computer program product which, when run on an electronic device, causes the electronic device to perform the steps of the method embodiments described above.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, 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 device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

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 solution. 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 manners. For example, the apparatus/network device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims

1. A method of scheduling robots, comprising:

determining a target robot to be scheduled based on the site information; the determining the target robot to be scheduled based on the site information comprises the following steps:

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;

selecting a robot with the minimum cost for executing the target task from a target robot type based on the site information as a target robot; the selecting, as a target robot, a robot having the smallest cost of executing the target task in a target robot type based on the site information, includes:

determining an initial site according to the site information; the recursion calling mode is adopted, the initial station is taken as the center, the searching range is gradually expanded by a preset step length, and candidate robots of the target robot type are searched; calculating the cost of each candidate robot reaching the starting site; taking the candidate robot with the minimum cost as a target robot;

and controlling the target robot to execute the target task.

2. The scheduling method of claim 1, 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 site information contains more than two sites, the task type is a multi-point picking and placing task, and the type of the target robot to be scheduled is determined to be a roll-feeding robot;

if the site information only comprises two sites, the task type is a warehouse-in and warehouse-out task, and the type of the target robot to be scheduled is determined to be a jacking type robot.

3. The scheduling method of claim 2, wherein if the target robot type is a roll-fed robot, controlling the target robot to perform the target task comprises:

according to the site information, determining a picking site and a placing site in the target task;

generating a task string according to the positions of the pick-up station and the put-in station, wherein the task string comprises a path sequence of the pick-in station and the put-in station for minimizing the power loss of the target robot;

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

4. The scheduling method of claim 2, wherein if the target robot type is a lift-up robot, the pathway station comprises a first station and a second station; controlling the target robot to execute the target task, including:

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

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

5. The scheduling method of claim 2, 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 path occupied by the target robot 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;

in the process of moving the target robot, detecting whether a conflict robot exists in a time window entering the next station, wherein the conflict robot is a robot with a time period of coincidence between the time window entering the next station and the time window of the target robot;

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

6. A robot scheduling apparatus, comprising:

the target robot determining module is 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; selecting a robot with the minimum cost for executing the target task from a target robot type based on the site information as a target robot;

the selecting, as a target robot, a robot having the smallest cost of executing the target task in a target robot type based on the site information, includes: determining an initial site according to the site information; the recursion calling mode is adopted, the initial station is taken as the center, the searching range is gradually expanded by a preset step length, and candidate robots of the target robot type are searched; calculating the cost of each candidate robot reaching the starting site; taking the candidate robot with the minimum cost as a target robot;

7. An electronic device comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, characterized in that the processor implements the scheduling method of any one of claims 1 to 5 when executing the computer program.

8. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the scheduling method according to any one of claims 1 to 5.