CN110084471B - Sorting scheduling method and device, warehousing system and readable storage medium - Google Patents
Sorting scheduling method and device, warehousing system and readable storage medium Download PDFInfo
- Publication number
- CN110084471B CN110084471B CN201910199759.XA CN201910199759A CN110084471B CN 110084471 B CN110084471 B CN 110084471B CN 201910199759 A CN201910199759 A CN 201910199759A CN 110084471 B CN110084471 B CN 110084471B
- Authority
- CN
- China
- Prior art keywords
- robot
- station
- stations
- candidate
- site
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Quality & Reliability (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
Abstract
The embodiment of the invention provides a sorting scheduling method, a device, a warehousing system and a readable storage medium, wherein the sorting scheduling method comprises the following steps: determining a plurality of stations to which the robot needs to go, determining a target station from the plurality of stations as a next station to which the robot goes according to the distance between the current position of the robot and the plurality of stations and the states of the respective private queues of the plurality of stations, and scheduling the robot to the target station. The problem of among the prior art through artifical the selecting and cause consume time long, inefficiency is solved, very big improvement select the operating efficiency.
Description
Technical Field
The invention belongs to the technical field of intelligence, and particularly relates to a sorting scheduling method, a sorting scheduling device, a warehousing system and a readable storage medium.
Background
With the popularization of e-commerce, online shopping is more and more convenient, and people can quickly shop online almost at any time and any place through the Internet. The rapid development of electricity merchants is accompanied by a great impact and pressure on the logistics industry. The three major links of logistics are the cargo feeding, the warehousing operation and the express delivery, and the most important and complex link is the warehousing operation link.
The warehousing operation comprises three major links of warehousing, sorting and ex-warehouse, and also comprises operation flows of warehouse location management, replenishment, inventory, allocation, rechecking and the like, wherein a small warehouse has hundreds of commodities, a large warehouse can reach tens of thousands of commodities, even hundreds of thousands of commodities, and the inventory is different from thousands of commodities to millions of commodities. Picking up tens of thousands of large quantities of items is absolutely not a simple matter. The traditional warehousing mode of operation is by manual picking.
In the manual picking mode, a worker firstly arrives at a list making room to pick a picking list, then pushes a trolley to pick order boxes with proper sizes and place the order boxes on the trolley, then holds the picking list by hand, and picks the order boxes along a goods position roadway according to the picking list indication, so that the problems of long time consumption and low efficiency are caused.
Disclosure of Invention
The embodiment of the invention provides a sorting scheduling method, a sorting scheduling device, a warehousing system and a readable storage medium, and aims to solve the problems of long work consumption time and low efficiency caused by manual sorting in the prior art.
In a first aspect of the embodiments of the present invention, a method for sorting scheduling is provided, including:
determining a plurality of stations to which the robot needs to go;
determining a target station from the plurality of stations as a next station for the robot to go to according to the distance between the current position of the robot and the plurality of stations and the state of the private queue of each station;
dispatching the robot to the target site.
In a second aspect of the embodiments of the present invention, there is provided a warehousing system including:
the system comprises a plurality of rows of goods shelves, wherein a roadway is formed between two adjacent rows of goods shelves;
at least one robot for handling racks and/or items;
the system comprises stations at the road junction, at least one private queue area is arranged near each station, and the private queue areas are parking areas of robots reaching the stations;
at least one shared buffer area, wherein each shared buffer area is a temporary parking area shared by robots of stations in the warehousing system; and the number of the first and second groups,
a scheduling system to schedule the at least one robot to handle the racks and/or items.
In a third aspect of the embodiments of the present invention, there is provided a sorting scheduling apparatus, including:
the determining module is used for determining a plurality of stations to which the robot needs to go;
the determining module is further configured to determine a target station from the multiple stations as a next station to which the robot moves according to distances between the current position of the robot and the multiple stations and states of private queues of the multiple stations;
and the scheduling module is used for scheduling the robot to the target station.
In a fourth aspect of embodiments of the present invention, there is provided a computer-readable storage medium, including:
the computer readable storage medium has stored thereon a computer program which, when executed by a processor, carries out the steps of the picking scheduling method of any one of the above.
In a fifth aspect of the embodiments of the present invention, there is provided a sorting scheduling apparatus, including:
comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the pick scheduling method of any one of the above.
According to the picking scheduling method, the picking scheduling device, the warehousing system and the readable storage medium, a plurality of stations to which the robot needs to go are determined, and according to the distance between the current position of the robot and the stations and the states of the private queues of the stations, a target station is determined from the stations to serve as the next station to which the robot goes, and the robot is scheduled to the target station. The problem of among the prior art through artifical the picking the consumption time that causes long, inefficiency is solved, the operation efficiency of picking of very big improvement.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a diagram illustrating a storage system according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps of a method for dispatch scheduling according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating specific steps of a picking scheduling method according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating specific steps of another picking scheduling method according to an embodiment of the present invention;
FIG. 5 is a flow chart of steps of another pick scheduling method provided by an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a picking scheduling apparatus according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of another picking scheduling apparatus according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
To more clearly describe the embodiment of the present invention, first, a warehousing system according to an embodiment of the present invention is described, and fig. 1 is an architecture diagram of a warehousing system according to an embodiment of the present invention, the warehousing system including: the system comprises a plurality of rows of shelves, at least one robot, a station located at the road junction, at least one shared buffer area and a dispatching system. A roadway is formed between two adjacent rows of shelves, each roadway opening is provided with a station, or partial roadway openings are provided with stations. At least one private queue area is arranged near each station, the private queue area is a parking area of the robot reaching the station, namely the private queue is used for caching the robot of which the target station is the station.
Each private queue may include one or more nodes, each of which may accommodate a robot dock. In some embodiments, the floor area of the warehousing system is divided into a plurality of cells, and each node may occupy a particular number of cells on the floor area, e.g., each node may occupy one or more cells, depending on the respective sizes of the robot and the cells.
The shared buffer area is a temporary parking area shared by all stations in the warehousing system, that is, the shared buffer area can be used for caching the robot of any station in the warehousing system. Each shared buffer area may simultaneously accommodate temporary parking of one or more robots. For example, the ground area of the warehousing system is divided into a plurality of cells, and the shared buffer area may be composed of one or more cells. If the private queue of the next station where one robot goes to does not have free, the robot can move to the shared buffer area which is closest to the station and has a free position for temporary parking so as to wait for the private queue of the station to be free. For example, if the private queue of the next station to which the robot goes is not free, the scheduling system may select one shared buffer area closest to the robot from the shared buffer areas that have free positions at present, and schedule the robot into the shared buffer area.
Whether the shared buffer area with the free position exists can be determined through the state information of each shared buffer area in the warehousing system stored in the storage medium (such as a memory). The scheduling system can update the stored state information in time according to the actual occupation condition of each shared buffer area.
By setting the shared buffer area, the problem that the queue of the station robot overflows can be effectively solved. The shared buffer areas in this embodiment may be distributed in a plurality of reachable spaces of the working space (e.g., warehouse, workshop or job room) of the warehousing system, so that not only is the field deployment simple to implement, but also the limited warehouse area can be effectively utilized.
The scheduling system is used for scheduling at least one robot in the warehousing system to carry the goods shelf and/or the articles, and particularly can be used for executing the picking scheduling method provided by the embodiment of the invention. The scheduling system can be implemented by a picking scheduling device, and the picking scheduling device can be specifically implemented as a transfer robot (such as an AGV), a computer, a server (such as a backend server or a cloud server), a terminal device (such as a mobile phone, a tablet, a notebook computer), a wearable device or a portable device, and the like.
Referring to fig. 1, A, B, C, D, E, F, G, H respectively represent shelves for storing goods in a warehouse, a, b, c, d, e, f respectively represent stations, each square in fig. 1 represents a node, a square grid represented by a dotted line represents a private queue area provided near a station, and 102 represents a shared buffer area, for example, two grids represented by reference numeral 101 may be the private queue area of a station a.
Under the operation system, the main road is divided into grids, so that the robot can conveniently navigate and run, a picking worker only needs to stand at the road junction of a lane and is in charge of one or a plurality of adjacent lanes, after the robot reaches the road junction of the lane, the picking worker delivers picked commodities to a robot shelf, and the robot goes to the next target station to continue picking till all commodities are picked completely. It should be noted that each tunnel plans a station, and a private queue is also bound to the station, and the private queue is a parking area of a robot reaching the station, and meanwhile, in order to solve the problem of insufficient private queue, a shared buffer area is also planned in a partial area of the site.
The robot may be a lifting robot, which moves to a position below the shelf, lifts the shelf off the ground, and moves the shelf to carry the shelf; the robot can also be a dragging robot, and the robot can be connected with a movable goods shelf to drag the goods shelf to move; the robot may also be a forklift robot, which uses a pallet fork to carry items, such as cargo containers; the robot may also be a robot with a container that can place items in its own container to carry the items.
Fig. 2 is a flowchart of steps of a picking scheduling method according to an embodiment of the present invention, where the method is performed by a picking scheduling apparatus, and the picking scheduling apparatus is typically implemented in hardware and/or software. As shown in fig. 2, the method may include:
and step S210, determining a plurality of stations to which the robot needs to go.
For example, a plurality of stations to which the robot needs to go are determined based on the locations of items in a pick list corresponding to the robot. A robot may be bound to at least one pick list, and a picking task for the at least one pick list is completed by the robot, where the pick list corresponds to the robot. For example, the robot carries a rack to a corresponding station, the picking staff places or takes the items corresponding to the picking list on or off the rack, and then the robot carries the rack to go on to the next station until all the items in the picking list corresponding to the robot are picked.
The picking scheduling device determines the stations to which the robot needs to go, and for example, in fig. 1, it is assumed that the stations to which the robot needs to go are station a, station c, and station e.
Step S220, according to the distance between the current position of the robot and the plurality of stations and the states of the respective private queues of the plurality of stations, determining a target station from the plurality of stations as a next station for the robot to go to.
Since the distance from the current position of the robot to each station is different and the state of the private queue of each station may also be different, one station may be determined from the plurality of stations as the next station for the robot to go to according to the distance from the current position of the robot to the plurality of stations and the state of the private queue of each station. According to the distance from the robot to each station and the state of the private queue of each station, one station can be determined from the plurality of stations as a next station for the robot to go to.
And step S230, dispatching the robot to a target station.
According to the picking scheduling method provided by the embodiment, the goods shelves and/or articles are automatically transported among stations by the robot, so that the problems of long time consumption and low efficiency caused by manual picking in the prior art are solved, and the picking operation efficiency is greatly improved; meanwhile, the method of the embodiment determines the next station to go to according to the distance between the robot and each station and the state of the private queue of each station, and effectively reduces the occurrence of local congestion through global scheduling.
Optionally, fig. 3 is a flowchart of specific steps of a picking scheduling method according to an embodiment of the present invention, as shown in fig. 3, step S220 is to determine a target station from a plurality of stations as a next station for the robot to go to according to distances between a current position where the robot is located and the plurality of stations and states of respective private queues of the plurality of stations, and may include:
s310, calculating the distance from the idle station in the private queue in the plurality of stations to the current position of the robot.
In this embodiment, the state of the private queue is divided into idle and non-idle: if all nodes in the private queue of one station park the organic robot, the state of the private queue is non-idle; if at least one node in a private queue is idle, the state of the private queue is idle.
Taking the determination of a plurality of stations which the robot needs to go to as a station a, a station c and a station e as an example for introduction, the states of the private queues of the station a, the station c and the station e are determined firstly, and if the state of the private queue of a certain station is idle, the distance from the station to the current position of the robot is calculated. And if the states of the private queues of the station a, the station c and the station e are idle, respectively calculating the distances from the station a, the station c and the station e to the current position of the robot.
And S320, taking the station closest to the robot in the stations with the idle private queues as a target station.
And if the distance from the station a to the current position of the robot is the shortest, taking the station a as a target station.
According to the picking scheduling method provided by the embodiment, the distance from a station with idle stations in a private queue to the current position of the robot is calculated by determining the plurality of stations to which the robot needs to go, the station closest to the robot is taken as a target station, and the robot is scheduled to the target station.
Optionally, fig. 4 is a flowchart of specific steps of another picking scheduling method according to an embodiment of the present invention, as shown in fig. 4, step S220 is to determine, according to a distance between a current position of the robot and the multiple stations and states of respective private queues of the multiple stations, a target station from the multiple stations as a next station for the robot to go to, and may include:
s410, if the states of the private queues of the plurality of sites are all non-idle, taking the site closest to the robot in the plurality of sites as a candidate site, and determining a first shared buffer area according to the candidate site.
The shared buffer area can be preset, or can be temporarily set according to the current road condition in the warehouse and the path of the robot for transporting goods in the warehouse, so that the interference of the setting of the shared buffer area on the normal carrying of the robot is avoided. For example, a reserved area may be provided near a plurality of stations, which reserved area does not affect the movement of the robot in the warehouse.
A shared buffer area closest to the candidate station may be selected from among the shared buffer areas having no free locations as the first shared buffer area.
To describe the present embodiment in more detail, it is illustrated here that, if the states of the private queues of the station a, the station c, and the station e are all non-idle, and the station a is closest to the robot, the station a is taken as a candidate station, and a first shared buffer area is determined according to the station a, and the first shared buffer area may be a shared buffer area closest to the station a.
And S420, dispatching the robot to a first shared buffer area to wait.
And S430, evaluating the waiting cost of the candidate station and the waiting costs of other stations in the plurality of stations.
The waiting cost of the candidate station is determined according to the distance from the candidate station to the robot and the number of occupied nodes of the private queue of the candidate station, and the waiting cost of other stations is determined according to the distance from the other stations to the robot.
Optionally, the waiting cost of the candidate station and the waiting costs of other stations in the plurality of stations may be evaluated by using the following expression:
Costc＝Nc*Dc，Costj＝Dj
among them, CostcRepresents the waiting cost, N, of the candidate stationcNumber of nodes occupied in the private queue representing candidate sites, DcRepresents the distance from the shared buffer position where the robot is located to the candidate station, CostjRepresents the jth site M of the other sitesjWaiting cost of, DjIndicating the shared buffer position of the robot to the jth station MjThe distance of (c).
Alternatively, the waiting costs of the candidate sites and the waiting costs of other sites in the plurality of sites may be evaluated using the following expression:
Costc＝Nc*Dc，Costj＝Nj*Dj
among them, CostcRepresents the waiting cost of the candidate site, NcNumber of nodes occupied in the private queue representing candidate sites, DcIndicating the distance, Cost, from the position of the robot to the candidate stationjRepresents the jth site M among the other sitesjWaiting cost of (D)jIndicating the position of the robot to the jth station MjDistance of (1), NjIndicating the number of nodes occupied by the private queue of the jth site.
And S440, if the waiting cost of the candidate station is less than or equal to the waiting costs of other stations, taking the candidate station as a target station.
And if the waiting cost of the candidate sites is greater than the waiting cost of at least part of the other sites, taking the site with the minimum waiting cost in at least part of the sites as a target site.
To describe the present embodiment in more detail, as exemplified in connection with step S410, if the waiting cost of station a is less than or equal to the waiting costs of station b and station c, station a is taken as the target station. And if the waiting cost of the site a is greater than that of the site b and the site c, taking the site with the minimum waiting cost in the site b and the site c as a target site, namely, if the waiting cost of the site b is less than that of the site c, taking the site b as the target site.
It should be noted that, by evaluating the waiting cost of the candidate station and the waiting costs of other stations in the plurality of stations, the target station can be dynamically changed, so that global scheduling is realized, the problem of local congestion is reduced, and the picking operation efficiency is improved.
Optionally, the dispatching the robot to the target station may include the following steps:
determining a second shared buffer area according to the target station; dispatching the robot to a second shared buffer area to wait; and if the private queue of the target station is idle, scheduling the robot to the target station. For describing the embodiment in more detail, a station a is also taken as an example, if the station a is a target station, a shared buffer area may be determined according to the station a, the robot is scheduled to the shared buffer area to wait, and if a station a private queue is idle, the robot is scheduled to the station a.
The second shared buffer area is the shared buffer area closest to the target station in the shared buffer areas with the current free position.
The method comprises the steps of firstly determining the state of a private queue of a lower target station before the robot is dispatched to the target station, dispatching the robot to a buffer area to wait if the robot is not idle, and dispatching the robot only when the state of the private queue of the target station is idle, so that the condition of station congestion can be avoided, and the picking operation efficiency is improved.
Optionally, fig. 5 is a flowchart of steps of another picking scheduling method provided in the embodiment of the present invention, and as shown in fig. 5, the picking scheduling method provided in the embodiment may include:
and S510, determining a plurality of stations to which the robot needs to go.
S520, if the states of the private queues of the plurality of stations are all non-idle, the station closest to the robot in the plurality of stations is used as a target station, and the shared buffer area is determined according to the target station.
And if the states of the private queues of the plurality of stations are all non-idle, taking the station closest to the robot in the plurality of stations as a target station, and determining a shared buffer area according to the target station.
And S530, dispatching the robot to a shared buffer area for waiting.
And S540, when the state of the private queue of the target station is idle, scheduling the robot to the target station.
In the picking scheduling method provided by this embodiment, by determining a plurality of stations to which the robot needs to go, if states of private queues of the plurality of stations are all non-idle, a station closest to the robot among the plurality of stations is taken as a target station, a shared buffer area is determined according to the target station, the robot is scheduled to the shared buffer area to wait, and when the state of the private queue of the target station is idle, the robot is scheduled to the target station.
Optionally, before determining a plurality of stations to which the robot needs to go in step S210, the method may further include:
receiving a picking list sent by a warehousing management system; determining a highest priority picking list from the picking lists, and binding the highest priority picking list to the robot, wherein a plurality of stations that the robot needs to go to are determined according to the highest priority picking list.
For example, the picking list may be prioritized based on the order time, destination, customer type, item type, courier type, etc. of the items in the picking list.
Optionally, orders in the picking list have similar attributes, where the similar attributes include the same/adjacent locations (e.g., same/adjacent shelves or lanes) of the items in the orders, the same picking path, and/or the same partial picking path. Orders with similar attributes are combined into a picking list, so that the number of times of robot carrying is reduced, and the picking efficiency is improved.
Fig. 6 is a schematic structural diagram of a picking scheduling apparatus according to an embodiment of the present invention. The pick scheduler is typically implemented in hardware and/or software. The pick scheduling apparatus 600 includes the following modules: a determination module 610 and a scheduling module 620.
The determining module 610 is used for determining a plurality of stations to which the robot needs to go; the determining module 610 is further configured to determine a target station from the multiple stations as a next station for the robot to go to according to distances between the current position where the robot is located and the multiple stations and states of private queues of the multiple stations; the scheduling module 620 is used to schedule the robot to the target site.
The picking scheduling device provided in this embodiment determines, by determining a plurality of stations to which the robot needs to go, one target station from the plurality of stations as a next station to which the robot goes according to distances between a current position where the robot is located and the plurality of stations and states of respective private queues of the plurality of stations, and schedules the robot to the target station. The problem of among the prior art through artifical the picking the consumption time that causes long, inefficiency is solved, the operation efficiency of picking of very big improvement.
Based on the embodiment shown in fig. 6, further, the determining module 610 is specifically configured to calculate a distance from a station in a private queue of the multiple stations that is free to the current position where the robot is located; and taking the station closest to the robot as a target station.
Optionally, the determining module 610 is specifically configured to, if the states of the private queues of the multiple sites are all non-idle, take a site closest to the robot among the multiple sites as a candidate site, and determine the first shared buffer area according to the candidate site; dispatching the robot to a first shared buffer area for waiting; evaluating the waiting cost of the candidate station and the waiting costs of other stations in the plurality of stations; if the waiting cost of the candidate site is less than or equal to the waiting costs of other sites, taking the candidate site as a target site; if the waiting cost of the candidate sites is greater than the waiting cost of at least part of the other sites, taking the site with the minimum waiting cost in at least part of the sites as a target site;
optionally, the scheduling module 620 is specifically configured to determine a second shared buffer area according to the target station; dispatching the robot to a second shared buffer area for waiting; and if the private queue of the target station is idle, scheduling the robot to the target station.
Optionally, the waiting cost of the candidate station is determined according to the distance from the candidate station to the robot and the number of occupied nodes in the private queue of the candidate station, and the waiting cost of other stations is determined according to the distance from other stations to the robot.
Optionally, the waiting cost of the candidate station and the waiting costs of other stations in the multiple stations are evaluated by using the following expression:
Costc＝Nc*Dc，Costj＝Dj
among them, CostcRepresents the waiting cost, N, of the candidate stationcNumber of occupied nodes in private queue representing candidate site, DcIndicating the distance, Cost, from the position of the robot to the candidate stationjRepresents the jth site M among the other sitesjWaiting cost of, DjIndicating the position of the robot to the jth station MjThe distance of (c).
Optionally, the determining module 610 is specifically configured to, if the states of the private queues of the multiple stations are all non-idle, take a station closest to the robot among the multiple stations as a target station, and determine the shared buffer area according to the target station; and dispatching the robot to a shared buffer area for waiting.
The scheduling module 620 is specifically configured to schedule the robot to the target station when the state of the private queue of the target station is idle.
The device can also comprise a receiving module, wherein the receiving module is used for receiving the picking list sent by the warehousing management system. Accordingly, the determination module 610 may also determine a highest priority pick list from the pick lists and bind the highest priority pick list to the bot.
The number of stations that the robot needs to go to is determined from the highest priority pick list.
Optionally, orders in the picking list have similar attributes, including the same/adjacent locations of items in the orders, the same picking paths, and/or the same partial picking paths.
In addition, an embodiment of the present invention further provides a picking scheduling device, as shown in fig. 7, fig. 7 is a schematic structural diagram of another picking scheduling device provided in the embodiment of the present invention. The picking scheduling device 700 includes a processor 710, a memory 720 and a computer program stored in the memory 720 and capable of running on the processor 710, wherein when the computer program is executed by the processor 710, the computer program implements the processes of the embodiments of the picking scheduling method described in the above embodiments, and can achieve the same technical effects, and in order to avoid repetition, the details are not repeated here.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned picking scheduling method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
The embodiment of the invention also provides a computer program, and the computer program can be stored on a cloud or a local storage medium. When being executed by a computer or a processor, for performing the respective steps of the pick scheduling method according to an embodiment of the present invention and for implementing the respective modules in the pick scheduling apparatus according to an embodiment of the present invention.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (13)
1. A pick scheduling method, comprising:
determining a plurality of stations to which the robot needs to go currently;
determining a target station from the plurality of stations as a next station for the robot to go to according to the distance between the current position of the robot and the plurality of stations and the state of the private queue of each station; the method comprises the following steps:
taking a station which is idle in a private queue in the plurality of stations and has the closest distance to the robot as the target station; when the states of the private queues of the plurality of sites are all non-idle, taking the site with the closest distance as a candidate site, evaluating the waiting cost of the candidate site and the waiting costs of other sites in the plurality of sites, and taking the candidate site as the target site if the waiting cost of the candidate site is less than or equal to the waiting costs of the other sites; if the waiting cost of the candidate sites is greater than the waiting costs of at least part of the other sites, taking the site with the minimum waiting cost in the at least part of the sites as the target site;
dispatching the robot to the target site;
the waiting cost of the candidate station is determined according to the distance from the candidate station to the shared buffer area where the robot is located and the number of nodes occupied by the private queue of the candidate station, and the waiting cost of other stations is determined according to the distance from the other stations to the robot.
2. The method of claim 1, wherein determining a target station from the plurality of stations as a next station for the robot to travel to according to the distances from the current position of the robot to the plurality of stations and the status of the private queues of the plurality of stations comprises:
calculating the distance from the station with idle stations in the private queue in the plurality of stations to the current position of the robot;
and taking the station closest to the robot in the stations with the idle private queues as the target station.
3. The method of claim 1, further comprising:
scheduling the robot to a first shared buffer area to wait; wherein the first shared buffer region is determined according to the candidate station.
4. The method of claim 3, wherein said dispatching the robot to the target site comprises:
determining a second shared buffer area according to the target station;
dispatching the robot to the second shared buffer area to wait;
and if the private queue of the target station is idle, scheduling the robot to the target station.
5. The method of claim 1, wherein the waiting costs of the candidate stations and the waiting costs of other stations in the plurality of stations are evaluated using the following expression:
Costc=Nc*Dc，Costj=Dj
among them, CostcRepresenting the waiting cost, N, of the candidate stationcRepresenting the number of occupied nodes in the private queue of the candidate site, Dc Representing the distance, Cost, of the robot's location to the candidate stationjRepresents the jth site M of the other sitesjWaiting cost of, DjRepresenting the position of said robot to said jth station MjThe distance of (c).
6. The method according to any one of claims 1 to 4,
the determining, according to distances from a first current position where the robot is located to the plurality of stations and states of private queues of the plurality of stations, a target station from the plurality of stations as a next station to which the robot moves includes:
if the states of the private queues of the sites are all non-idle, taking the site closest to the robot in the sites as the target site, and determining a shared buffer area according to the target site;
dispatching the robot to the shared buffer area to wait;
the scheduling the robot to the target site includes:
and when the state of the private queue of the target station is idle, the robot is dispatched to the target station.
7. The method of any of claims 1 to 4, wherein prior to said determining a plurality of stations to which the robot currently needs to travel, the method further comprises:
receiving a picking list sent by a warehousing management system;
determining a highest priority pick list from the pick lists and binding the highest priority pick list to the bot;
wherein the plurality of stations to which the robot needs to go are determined from the highest priority pick list.
8. The method of claim 7, wherein orders in the pick list have similar attributes including the same/adjacent location of items in the order, the same picking path, and/or the same partial picking path.
9. A warehousing system, comprising:
the system comprises a plurality of rows of goods shelves, wherein a roadway is formed between two adjacent rows of goods shelves;
at least one robot for handling racks and/or items;
the system comprises stations at the road junction, at least one private queue area is arranged near each station, and the private queue areas are parking areas of robots reaching the stations;
at least one shared buffer area, wherein each shared buffer area is a temporary parking area shared by robots of stations in the warehousing system; and the number of the first and second groups,
a scheduling system to schedule the at least one robot to handle the racks and/or items.
10. The system of claim 9, wherein the scheduling system is configured to perform the method of any one of claims 1 to 8.
11. A pick scheduling apparatus, comprising:
the determining module is used for determining a plurality of stations to which the robot needs to go currently;
the determining module is further configured to determine a target station from the multiple stations as a next station to which the robot moves according to distances between the current position of the robot and the multiple stations and states of private queues of the multiple stations; the method comprises the following steps:
taking a station which is idle in a private queue in the plurality of stations and has the closest distance to the robot as a target station; when the states of the private queues of the plurality of sites are all non-idle, taking the site with the closest distance as a candidate site, evaluating the waiting cost of the candidate site and the waiting costs of other sites in the plurality of sites, and taking the candidate site as the target site if the waiting cost of the candidate site is less than or equal to the waiting costs of the other sites; if the waiting cost of the candidate sites is greater than the waiting costs of at least part of the other sites, taking the site with the minimum waiting cost in the at least part of the sites as the target site; the waiting cost of the candidate station is determined according to the distance from the candidate station to the shared buffer area where the robot is located and the number of occupied nodes of the private queue of the candidate station, and the waiting cost of other stations is determined according to the distance from other stations to the robot;
and the scheduling module is used for scheduling the robot to the target station.
12. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the pick scheduling method according to any one of claims 1 to 8.
13. A pick scheduling apparatus comprising a processor, a memory and a computer program stored on the memory and operable on the processor, the computer program when executed by the processor implementing the steps of the pick scheduling method as claimed in any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910199759.XA CN110084471B (en) | 2019-03-15 | 2019-03-15 | Sorting scheduling method and device, warehousing system and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910199759.XA CN110084471B (en) | 2019-03-15 | 2019-03-15 | Sorting scheduling method and device, warehousing system and readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110084471A CN110084471A (en) | 2019-08-02 |
| CN110084471B true CN110084471B (en) | 2022-06-21 |
Family
ID=67412556
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910199759.XA Active CN110084471B (en) | 2019-03-15 | 2019-03-15 | Sorting scheduling method and device, warehousing system and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110084471B (en) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111099232B (en) * | 2019-12-13 | 2021-05-04 | 北京极智嘉科技股份有限公司 | Self-driven mobile device and warehouse system |
| CN111160831B (en) * | 2019-12-26 | 2024-01-23 | 北京旷视机器人技术有限公司 | Task generation method and device for intensive warehouse and electronic equipment |
| CN113205288A (en) * | 2020-02-03 | 2021-08-03 | 北京京东乾石科技有限公司 | Method and device for warehousing articles |
| CN113537654A (en) * | 2020-04-13 | 2021-10-22 | 北京京东乾石科技有限公司 | Task allocation method, device and system |
| CN113522755A (en) * | 2020-04-15 | 2021-10-22 | 北京旷视机器人技术有限公司 | Sorting scheduling method, sorting transportation method, sorting device and sorting system |
| CN111496788A (en) * | 2020-04-17 | 2020-08-07 | 南京协辰电子科技有限公司 | Scheduling method, device and system for mechanical arm |
| CN112099491A (en) * | 2020-08-20 | 2020-12-18 | 上海姜歌机器人有限公司 | Robot queuing method, robot and computer readable storage medium |
| CN112830147B (en) * | 2020-12-31 | 2022-09-20 | 深圳市海柔创新科技有限公司 | Cargo handling method, warehouse management equipment, warehousing system, medium and product |
| CN112465439B (en) * | 2021-02-02 | 2021-05-11 | 红石阳光（北京）科技股份有限公司 | Logistics distribution method and system based on intelligent brain control robot |
| CN113093763B (en) * | 2021-04-13 | 2023-04-07 | 塔米智能科技（北京）有限公司 | Mobile robot scheduling system and method |
| WO2024095122A1 (en) * | 2022-11-02 | 2024-05-10 | G.D S.P.A. | Process for the automated handling of products to be stored in a storage warehouse |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102014115579A1 (en) * | 2014-10-27 | 2016-04-28 | SSI Schäfer PEEM GmbH | Method and system for progressive picking |
| CN108357886A (en) * | 2017-01-26 | 2018-08-03 | 菜鸟智能物流控股有限公司 | Item sorting method and related apparatus |
| CN108858179B (en) * | 2017-05-09 | 2020-11-24 | 北京京东尚科信息技术有限公司 | Method and device for determining traveling path of sorting robot |
-
2019
- 2019-03-15 CN CN201910199759.XA patent/CN110084471B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN110084471A (en) | 2019-08-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110084471B (en) | Sorting scheduling method and device, warehousing system and readable storage medium | |
| Enright et al. | Optimization and coordinated autonomy in mobile fulfillment systems | |
| CN111344726B (en) | Method and system for dynamic truck routing between automated facilities | |
| Merschformann et al. | Decision rules for robotic mobile fulfillment systems | |
| US11593756B2 (en) | Automated guided vehicle control and organizing inventory items using predictive models for slow item types | |
| CN109878959B (en) | Sorting scheduling method and device, warehousing system and readable storage medium | |
| Vis et al. | Sequencing two cooperating automated stacking cranes in a container terminal | |
| CN110908381B (en) | Robot scheduling method and device | |
| US7751928B1 (en) | Method and system for agent exchange-based materials handling | |
| US7774243B1 (en) | Method and system for predestination item transfer among agents within a materials handling facility | |
| CN110245890A (en) | Kinds of goods method for sorting and kinds of goods sorting system | |
| CN110059926B (en) | Sorting scheduling method and device, warehousing system and readable storage medium | |
| JP2019526513A (en) | Optimize warehouse layout based on customizable goals | |
| CN109835651A (en) | Goods sorting method, server and system | |
| WO2022095835A1 (en) | Warehousing management system and method | |
| CN111144825A (en) | RFID storage logistics inventory method and system based on AGV trolley | |
| CN111409997A (en) | Transfer robot picking task scheduling method for mobile shelf warehousing system | |
| Jiang et al. | Picking-replenishment synchronization for robotic forward-reserve warehouses | |
| Dotoli et al. | A coloured Petri net model for automated storage and retrieval systems serviced by rail-guided vehicles: a control perspective | |
| Ferrara et al. | Fleet sizing of laser guided vehicles and pallet shuttles in automated warehouses | |
| Heimfarth et al. | A mixed truck and robot delivery approach for the daily supply of customers | |
| CN114415610A (en) | Robot scheduling method and device, electronic equipment and storage medium | |
| Giglio | Task scheduling for multiple forklift AGVs in distribution warehouses | |
| Zhu et al. | Workstation layout strategies in Robotic Mobile Fulfillment Systems considering carbon emissions | |
| CN115660551A (en) | Multi-AGV scheduling optimization method and system for power grid measurement material unattended warehouse |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |