WO2019120158A1 - Procédé de saisie d'articles, et appareil associé - Google Patents

Procédé de saisie d'articles, et appareil associé Download PDF

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Publication number
WO2019120158A1
WO2019120158A1 PCT/CN2018/121446 CN2018121446W WO2019120158A1 WO 2019120158 A1 WO2019120158 A1 WO 2019120158A1 CN 2018121446 W CN2018121446 W CN 2018121446W WO 2019120158 A1 WO2019120158 A1 WO 2019120158A1
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WIPO (PCT)
Prior art keywords
picking
subtask
item
target
subtasks
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PCT/CN2018/121446
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English (en)
Chinese (zh)
Inventor
刘衡
朱胜火
杨森
朱礼君
栾瑞鹏
童凯亮
徐渊鸿
Original Assignee
菜鸟智能物流控股有限公司
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Publication of WO2019120158A1 publication Critical patent/WO2019120158A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • 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
    • 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

Definitions

  • the present application relates to the field of warehouse management technology, and more specifically, to an item picking method and related equipment.
  • articles are usually stored in categories by region, that is, different types of articles are stored in different regions.
  • Picking is based on certain rules or requirements, taking some items out of the storage area and transporting them to a designated location.
  • the storage area may also be referred to as a picking area, and a process of picking out the required items from a picking area may be referred to as a picking subtask.
  • the item order includes 10 items of 3 types
  • 2 items of category 1 include 2 items
  • category 2 items include 4 items
  • category 3 items include 4 items
  • 2 pieces of picking areas corresponding to category 1 need to be selected.
  • the article picks four items from the picking area corresponding to the type 2, and picks four items from the picking area corresponding to the type 3.
  • the sequential execution order of the selected subtasks will affect the completion of the picking. For example, the picking area corresponding to the above category 1 is closer to the picking area corresponding to the type 2, but the picking areas corresponding to the type 3 are far away. If the item of the type 1 is selected first, the type 3 is selected, and finally the picking is performed. Type 2 items will result in longer picking distances and affect picking efficiency.
  • the execution order of the picking subtasks is arbitrary, and the completion of the picking usually cannot meet the picking target requirements.
  • the present application provides an item picking method such that the completion of the picking subtask meets the preset picking target.
  • the present application provides an item picking method, including:
  • the present application provides an item picking apparatus, comprising: a processor and a memory, the processor executing at least the data stored in the memory by running a software program stored in the memory, at least as follows step:
  • an item picking apparatus including:
  • a picking target determining unit configured to determine a picking target and an attribute item associated with the picking target
  • An attribute data determining unit configured to obtain a plurality of picking subtasks, and determine attribute data of the picking subtask corresponding to the attribute item;
  • the execution order determining unit is configured to determine an execution order of the plurality of picking subtasks according to the picking target and the attribute data of the picking subtask.
  • the item picking method provided by the present application can determine the picking target and the attribute item associated with the picking target, obtain the plurality of picking subtasks to be sorted, and determine the attribute data corresponding to the picking subtask and the attribute item, and further The attribute data of the picking target and the picking subtasks are determined to determine the execution order of the plurality of picking subtasks. It can be seen that the application can schedule the picking order of the picking subtasks according to the picking target, so that the completion of the picking subtasks meets the requirements of the specific picking target.
  • FIGS. 2A and 2B are schematic diagrams showing two execution sequences of the picking subtasks provided by the present application.
  • FIG. 3 is a schematic diagram of an execution sequence of the picking subtask provided by the present application.
  • FIG. 4A and FIG. 4B are schematic diagrams showing the execution sequence of two sorting subtasks obtained by using the optimization algorithm and the unused optimization algorithm provided by the present application;
  • FIG. 5 is a schematic structural diagram of an article sorting apparatus provided by the present application.
  • FIG. 6 is a schematic structural view of an article sorting apparatus provided by the present application.
  • the storage space of the article a plurality of storage areas are usually provided for storing different kinds of articles.
  • the process is sorted, and the storage area may also be referred to as a picking area.
  • the article carrying device and the driving device can also be arranged in the object storage space.
  • the article carrying device is configured to carry articles sorted from the picking area
  • the driving device is configured to drive the article carrying device to move to move the article carrying device from one location to another. For example, if a plurality of items need to be sorted, the drive unit needs to pull the item carrying device from one picking area to another picking area.
  • One specific form of the item carrying device is a picking cart, a specific form of which is a mobile robot.
  • the object picking method of the present application is directed to the picking subtask, and the picking subtask has an associated relationship with the picking area, and the item carrying device performing a picking subtask specifically refers to loading the item carrying device into the picking associated with the picking subtask. Items picked up in the area.
  • the item picking method can be executed only on the basis of the picking subtask.
  • the present application first describes the generation process of the sorting subtask. Specifically, a generation process of the sorting subtask includes the following steps A1 to A2.
  • A1 Obtain the order list and determine the picking target, and generate a picking order according to the picking target according to the item list.
  • the item list contains items, which need to be sorted.
  • One specific form of the item list is an order for the item generated by the buyer to purchase the item on the e-commerce platform.
  • the trigger condition signal for obtaining the item list may include: the item carrying device is idle, the driving device is idle, the vehicle that needs to take the item from the item storage space, and the like.
  • the picking target may be that the picking time of all items in the item list is the shortest, or the picking interval length of the items having the same attribute in the item list is the shortest; and the same attribute may be the same size of the item, the same packing area of the item, and the item
  • the delivery address is the same or the item's transportation is the same.
  • a plurality of picking targets are provided, and in the picking process, a picking target can be determined among the plurality of picking targets according to actual needs as the picking target used by the picking process.
  • the manner of determining may be a random selection, or may be determined according to a user's selection operation, or may be based on an attribute of the item list to determine the selection target. For example, if the attribute of the item list is expedited, the picking target can be determined to be the shortest picking time.
  • the order can be aggregated into picking orders according to the picking target, which can also be called a picking task.
  • a picking order corresponds to an item carrying tool, and an item carrying tool needs to carry all the items in a picking list to consider an item carrying tool to complete a picking task. Or it can be said that all the selected items in a picking list will be stored in the same item carrying tool. If items with the same attributes are included in the same picking order, such a picking vehicle completes the picking task, and items with the same attributes can be obtained at the same time, that is, the picking interval of the items indicating the same attribute is the shortest.
  • One way of generating a picking slip may include the following steps A11 to A14.
  • A11 Determine the attribute item associated with the picking target.
  • the picking target is associated with an attribute item
  • the attribute item is an attribute that affects the completion of the picking target.
  • the attribute item that can affect the picking time of the item includes any one or more of the following items: the location of the picking area where the item is located, and the picking area where the item is located. Work load, work efficiency of the picking area where the item is located, priority of picking of items, etc.
  • the picking target is the shortest picking interval for the item with the same receiving address in the item list in the picking list
  • the attribute item corresponding to the picking target includes the receiving address of the item.
  • A12 Obtain the item list and combine the items in the item list to generate a pick list.
  • the items in the item list can be arranged and combined to generate a plurality of alternative picking orders.
  • the combination may include a combination of all quantity forms, for example, if 5 items are included in 2 item lists, the 5 items are combined in a 1 and 4 number form, and a combination of 2 and 3 quantity forms is performed.
  • A13 Determine the attribute data corresponding to the item and the attribute item in the picking list, and calculate the comprehensive score of the picking list according to the attribute data.
  • the data on the attribute item is determined for the item in the picking list, and the data may be referred to as attribute data. For example, determining the picking area where the item is located according to the type of the item, determining the location of the picking area, the working efficiency of the picking area, and the workload of the picking area; for example, determining the item list according to the receiving address corresponding to the item list The shipping address of the item.
  • the comprehensive score of the alternative picking order firstly, according to the attribute data of the items in the alternative picking list, the attribute data of the alternative picking order is calculated, and then the comprehensive score of the alternative picking order is obtained according to the attribute data of the alternative picking list.
  • the interval between the items in the alternative picking order is calculated according to the location of the picking area where the items in the alternative picking order are located; and the load status corresponding to the alternative picking order is determined according to the workload of the picking area in which the item in the alternative picking order is located .
  • the load status corresponding to the alternative picking order is high; and if the picking area of the item satisfying the quantity requirement in the alternative picking order is selected If the workload is medium, the load status corresponding to the alternative picking order is determined to be medium; and if the workload of the picking area where the item satisfying the quantity requirement in the alternative picking order is low, the load status corresponding to the alternative picking order is determined. It is low.
  • the conversion relationship between the attribute data of the alternative picking order and the score may be set in advance.
  • the interval between items in the alternate picking order is in the range [0,5), then it is converted to 1 point, and the interval between items in the alternative picking order is in the range of [5,10).
  • the conversion is 2 points, etc.; if the load status corresponding to the alternative picking order is high, it is converted into 3 points, and if the load status corresponding to the alternative picking order is medium, it is converted into 2 points, If the load status corresponding to the picking order is low, convert it to 1 point.
  • the corresponding scores mentioned above are merely illustrative examples, and may be other values in practical applications.
  • the score corresponding to the picking order can be calculated. Since the attribute item included in the picking target may be a plurality of items, the calculated attribute data of the picking order may also include a plurality of items, and each attribute data is converted into a corresponding score, and each point is summed to obtain an alternative picking.
  • a single score which can be called a composite score.
  • the attribute items that can affect the picking time of the item include four items: the position of the picking area where the item is located, the workload of the picking area where the item is located, and the picking of the item.
  • the alternative picking list includes the scores converted from the attribute data of the four items, and then the four points are summed to obtain a comprehensive score.
  • the composite score is obtained from a score.
  • A14 Select the picking list whose comprehensive score meets the picking target.
  • the picking target is that the picking time of all items in the item list is the shortest, and according to the conversion relationship, it can be determined that the smaller the comprehensive score is, the shorter the picking time is, so that the alternative picking list with the smallest comprehensive score can be determined as the picking order that meets the picking target.
  • the picking order that meets the picking target can be referred to as a target picking slip.
  • the process of generating a pick list based on the item list above may be referred to as aggregation of the item list.
  • the present application can aggregate items satisfying the selection target in the item list into the same picking list according to different picking targets. For example, if the picking target is the shortest picking time for all items in the item list, the items in the same or similar picking area of the item list may be included in the same picking list.
  • the process of aggregating the above items into a picking list is regarded as a global optimization problem, and an optimal solution of the optimization problem can be obtained by setting constraints and constraining targets.
  • the algorithm used to solve the global optimization problem may be an optimization algorithm, including but not limited to a column generation algorithm, a genetic algorithm, a greedy algorithm, and the like.
  • the global optimization problem corresponding to the item billing can be described as the following.
  • the objective function corresponding to the item list aggregation is: Where p j represents an alternative picking order, j represents the serial number of the alternate picking order, M represents the number of alternative picking orders; F(p j ) represents the picking duration corresponding to the alternate picking order, and the picking duration is determined by the alternative The number of items in the picking list, the location of the picking area where the item is located, the workload of the picking area where the item is located, the work efficiency of the picking area where the item is located, and the picking priority of the item are obtained.
  • constraints that the objective function needs to satisfy include the following two items.
  • A2 The items in the picking list corresponding to the same picking area are divided into the same picking subtask.
  • the picking subtask means picking items from the picking area.
  • the present application can aggregate various item lists to obtain various picking orders, and the picking order is divided into individual picking subtasks.
  • the picking ability of the work equipment such as the article carrying device and the driving device in the storage space of the article is limited, and the picking subtask is not guaranteed to be executed at the same time. Therefore, after the picking subtask is obtained, the execution process of the picking subtask needs to be sorted. Ensure that the execution results of the picking subtask meet the requirements of the picking target.
  • FIG. 1 shows a flow of the item picking method provided by the present application, specifically including steps S101-S103.
  • S101 Determine the picking target and the attribute item associated with the picking target.
  • S102 Obtain a plurality of picking subtasks, and determine attribute data corresponding to the picking subtasks and the attribute items.
  • the number of picking subtasks generated by the item picking device may be multiple, and the picking subtasks may be generated in real time or may be executed. Therefore, it can be considered that the item picking device maintains a sorting subtask pool, and the newly generated picking subtask can be added to the picking subtask pool, and the picking subtask in the sorting subtask pool can also be deleted because it is executed.
  • the number of picking subtasks in the picking subtask pool may be one, or multiple, or possibly zero.
  • the timing of obtaining the picking subtasks may include the following, such as when generating a new picking subtask, receiving a sorting subtask sorting instruction when completing a picking subtask, or a preset sorting period arrives. For convenience of description, these timings may be referred to as preset conditions.
  • Multiple pick subtasks are obtained from the pick subtasks maintained by the item picking device. It can be understood that the obtained picking subtask is an unexecuted picking subtask.
  • the obtained picking subtasks may be any sorting subtasks or designated picking subtasks; the number of picking subtasks obtained may be a preset number or a quantity determined according to the picking state. For example, if the picking status of the device is idle, a larger number of picking subtasks are obtained; if the picking state of the device is busy, a smaller number of picking subtasks are obtained.
  • the picking subtask may also be corresponding to the storage space of the item, or may be all the selected subtasks corresponding to the storage space of the item.
  • the item picking device maintains a corresponding picking subtask, and the number of picking subtasks currently corresponding to the item storage space can obtain all the sorting subtasks. In this way, all the sorting subtasks can be sorted as a whole according to the following steps to obtain the overall sorting optimal effect of all the sorting subtasks corresponding to the item storage space.
  • the screening condition may include selecting the type of the item in the subtask to be a specific type, selecting the estimated length of the item in the subtask to be within a preset duration, selecting the number of items in the subtask within a preset number range, and the like. Any one or more of them.
  • the screening condition may be any condition set according to actual conditions, and the present application is not specifically limited.
  • the picking target is that the picking time of all the items in the item list is the shortest, and the attribute items that can affect the picking time of the item include any one or more of the following items: the number of items included in the picking subtask, the workload of the picking area, Work efficiency, picking priority, etc. in the picking area. Therefore, it is necessary to determine the number of items included in the picking subtask, the workload of the picking area corresponding to the picking subtask, the working efficiency of the picking area corresponding to the picking subtask, and the priority of the picking subtask.
  • the workload can be embodied in the number of items that have not been selected in the picking area.
  • the determined attribute data is the attribute data of the sorting subtask.
  • S103 Determine an execution order of the plurality of picking subtasks according to the attribute data of the picking target and the picking subtask.
  • the picking condition of the picking subtask can be determined, and then the order of selecting the subtasks can be arranged according to the picking condition of the picking subtasks.
  • an implementation manner of this step may be: determining a plurality of alternative execution orders of the picking subtasks; estimating the picking condition of each candidate execution order according to the attribute data of the sorting subtask; and satisfying The alternate execution order corresponding to the picking condition of the picking target is determined as the execution order of the picking subtasks.
  • the alignment combination method can be used when determining an alternate execution order for the picking subtasks.
  • not all execution orders resulting from the permutation combination can be implemented in the picking scenario, and these unimplemented execution orders are not an alternative execution order. Therefore, the execution order obtained by the permutation combination can be filtered using the constraint condition, and the execution order satisfying the constraint condition is selected as the alternative execution order.
  • the picking subtasks corresponding to the same item carrying tool can only be executed sequentially.
  • the picking ability of the picking area is usually limited.
  • the same picking area can only perform the sorting work of the picking subtasks in sequence.
  • the obtained picking subtasks include three, the picking subtask 1 and the picking subtask 2 correspond to the same item carrying tool, and the picking subtask 3 corresponds to another item carrying tool.
  • the picking subtask 1 and the picking subtask 3 correspond to the picking area A, and the picking subtask 2 corresponds to the picking area B.
  • two alternative execution sequences shown in FIGS. 2A and 2B can be obtained.
  • the long box filled with the left diagonal line indicates the picking subtask 1
  • the long box filled with the right diagonal line indicates the picking subtask 2
  • the long box filled with the vertical line indicates the picking subtask 3.
  • the picking situation is used to indicate that the picking subtasks are completed in an alternate execution order.
  • the picking target is the shortest picking time for the item, and the picking condition indicates the picking time length after the picking subtask is executed in the alternate execution order.
  • the picking target has the shortest picking interval duration for the items having the same attribute, and the picking condition indicates the picking completion interval duration of the items having the same attribute after the sorting subtasks are executed in the alternative execution order.
  • the picking situation of each picking subtask can be obtained first according to the attribute data of the picking subtask. Then, using the picking of the picking subtasks, the picking of the alternative execution order is obtained.
  • the execution time of the picking subtask 1 is 1 minute
  • the execution time of the sorting subtask 2 is 2 minutes
  • the execution time of the sorting subtask 3 is 1.5 minutes.
  • the alternative execution order shown in FIG. 2A it may be determined that the execution duration of the alternate execution order is 4.5 minutes; with respect to the alternative execution order shown in FIG. 2B, it may be determined that the execution duration of the alternate execution order is 3 minutes.
  • the alternative execution order in which the picking condition satisfies the picking target is selected in the alternative execution order as the execution order of the picking subtask. Still taking the alternative execution order shown in FIG. 2A and FIG. 2B as an example, it is apparent that the execution time of the alternative execution order shown in FIG. 2B is short, and thus the execution order shown in FIG. 2B is taken as the target execution order.
  • the above mainly describes the picking target corresponding to the picking duration of the item.
  • the following describes the execution order of the picking subtasks that satisfy the other picking targets. If the picking target is the shortest picking interval for items with the same attributes in the order, the picking subtasks with the same attribute items can be executed at the shortest time interval.
  • the obtained picking subtasks include five, and the items having the same attribute among the five sorting subtasks include two types, and the first sorting subtasks include selecting subtasks 1, selecting subtasks 2, and selecting subtasks 3,
  • the second type of picking subtasks includes picking subtask 4 and picking subtask 5.
  • the picking subtask 1, the picking subtask 2, and the picking subtask 3 correspond to the same item carrying tool
  • the picking subtask 4 and the picking subtask 5 correspond to the same item carrying tool.
  • the picking subtask 1 and the picking subtask 4 correspond to the picking area A
  • the picking subtask 3 and the picking subtask 5 correspond to the picking area B.
  • the pick subtask 2 corresponds to the picking area C.
  • the determined execution order may be as shown in FIG. 3.
  • the picking area C performs the picking subtask 2, the picking area A executes the picking subtask 1 and then the picking subtask 4, and the picking area B executes the picking subtask 3 first. Perform the pick subtask 5.
  • the picking subtask 1, the picking subtask 2, and the picking subtask 3 included in the first sorting subtask can be sorted as much as possible; the picking subtask 4 and the picking subtask 5 included in the first sorting subtask can be simultaneously
  • the picking is completed. It can be seen that in this way, the items having the same attribute have the shortest picking interval duration and satisfy the picking target.
  • the process of determining the execution order for the picking subtasks can be regarded as the process of batch job scheduling, and the batch job scheduling algorithm can be used to solve the execution order satisfying the picking target.
  • the mathematical model constructed by the batch job scheduling algorithm for sorting sub-task sorting problems and the solving process of the mathematical model are introduced.
  • i denotes a collection of picking areas, all picking areas in an item storage space as a collection of picking areas, or an item storage space comprising a plurality of picking area sets, each picking area set comprising a partial picking area; j representing a picking subtask ;k denotes a single picking area in the picking area set; C denotes the completion time; C ijk is a variable of 0 or 1, indicating that the single picking area k of the picking area set i completes the estimated length of the picking subtask j.
  • constraints of the objective function include but are not limited to the following seven.
  • This constraint indicates that a single picking area k in the picking area set i is within a time segment t, and at most one picking subtask j can be executed.
  • n denotes the number of picking subtasks
  • X ijkt is a variable of 0 or 1, indicating whether the sorting subtask j is executed in the single picking area k in the picking area set i in the time segment t.
  • This constraint indicates that at any time segment t, the picking subtask j can only be executed in one picking area.
  • s represents the number of picking area sets;
  • m i represents the number of picking areas in the picking area set i.
  • This constraint indicates that at any time segment t, the time corresponding to the picking subtask j corresponding to a single picking area k in the picking area set i must be the same as the preset execution time P ijk .
  • U t denotes a planned time period
  • P ijk denotes a preset execution time on a single picking area k in the picking subtask j picking area set i
  • Y ijk is a variable of 0 or 1, indicating whether the picking subtask j is picking A single picking area k of the area set i is executed.
  • This constraint indicates that if the picking subtask j has performed a cycle on a single picking area k in the picking area set i, then this picking subtask must be executed on a single picking area k in this picking area i. among them,
  • This constraint indicates that for each picking area set i, one picking subtask j can only be executed on one picking area k.
  • This constraint is a way of estimating the execution time of the picking subtask j in the picking area k of the picking area set i.
  • the execution order of the sorting subtasks can be obtained.
  • the following is an example of the execution sequence of the sub-tasks that are not solved before the batch job scheduling algorithm is solved and after the batch job scheduling algorithm is solved.
  • FIG. 4A which shows the execution sequence of the pre-selection sub-tasks not solved using the batch job scheduling algorithm
  • Figure 4B which shows the execution sequence of the post-select sub-tasks using the batch job scheduling algorithm.
  • the different fills in the long box represent picking subtasks generated by different picking tasks.
  • the length of the long box filled with content indicates the estimated execution time of the pick subtask in the picking area.
  • the blank area in each line represents the idle time period of the picking area.
  • Each row represents the execution order of the individual picking subtasks performed in a picking area. It can be seen that each picking area can only perform one picking subtask at the same time.
  • the order of execution of the picking subtasks is different.
  • the total execution time of the sorting subtasks is shorter than that before the solution is not used by the batch job scheduling algorithm, thereby shortening the total execution time of the picking subtasks and reducing the idle duration of the picking area, that is, The invalid wait time for picking subtasks.
  • the item picking method provided by the present application can determine the picking target and the attribute item associated with the picking target, obtain the plurality of picking subtasks to be sorted, and determine the attribute data corresponding to the picking subtask and the attribute item, and further The attribute data of the picking target and the picking subtasks are determined to determine the execution order of the plurality of picking subtasks. It can be seen that the application can schedule the picking order of the picking subtasks according to the picking target, so that the completion of the picking subtasks meets the requirements of the specific picking target.
  • another item picking method provided by the present application may further include the following steps B1 and B2 on the basis of the item picking method shown in FIG. 4.
  • B1 Determine the corresponding item carrying device for the picking subtask according to the attribute of the item corresponding to the picking subtask.
  • a sorting operation device such as a robot arm may be disposed in the picking area for removing the items stored on the shelf and placing them in the article carrying device.
  • a sorting operation device such as a robot arm
  • the corresponding item carrying device can be assigned to the picking subtask according to the corresponding relationship between the package type of the item in the sorting subtask and the item carrying device, the corresponding relationship between the size of the item and the item carrying device, and the like.
  • an item carrying device may need to go to a plurality of picking areas to perform picking subtasks. If a plurality of item carrying devices are queued in the same picking area to perform a picking subtask, a heavier picking pressure is imposed on the picking operation equipment of the picking area. If the waiting item carrying device needs to go to other storage areas for sorting, there is no item carrying device in the other area, so that waiting in the queue will reduce the picking efficiency.
  • the article carrying device is not easily queued in the same picking area, thereby not only avoiding the picking pressure on the picking operation equipment of the same picking area, but also The utilization rate of the article carrying device can be improved, and the sorting efficiency of the article can also be improved.
  • B2 Allocating a driving device for the article carrying device, so that the driving device drives the article carrying device to the picking region corresponding to the picking subtask to meet the resource requirement.
  • one picking order corresponds to one item carrying device, and if one picking order is divided into a plurality of picking subtasks, the item carrying device needs to go to different picking areas to perform the sorting subtask.
  • the device that drives the article carrying device to move is referred to as a driving device, such as a mobile robot.
  • At least one driving device is disposed in the storage space of the article, and the driving device is distributed at various positions in the storage space of the article.
  • the resources consumed by the driving devices in different positions to drive the same article carrying device are different, wherein the resources may be duration or power. Therefore, for the article carrying device determined in step B1, it is calculated which drive device drives the article carrying device respectively to ensure that the total resources consumed by all the driving devices meet the resource requirements.
  • the article carrying device determined in step B1 can be used as a whole to calculate how to drive all the article carrying devices with the least resources.
  • this step can also select a partial article carrying device from step B1 to determine a driving device for driving the selected article carrying device.
  • the driving device is pre-allocated for the article carrying device, and various pre-allocation combinations of the article carrying device and the driving device are obtained; the resource consumption corresponding to each pre-allocation combination is calculated; and the pre-allocation combination that meets the resource requirement is selected as the resource consumption condition.
  • Target allocation combination is pre-allocated for the article carrying device, and various pre-allocation combinations of the article carrying device and the driving device are obtained; the resource consumption corresponding to each pre-allocation combination is calculated; and the pre-allocation combination that meets the resource requirement is selected as the resource consumption condition.
  • a resource item can be either a duration or a battery.
  • the resource item can be either a duration or a battery.
  • the influencing factors of the duration may include: a path distance between the driving device and the article carrying device, a traffic jam on the path between the driving device and the article carrying device, and the like.
  • the selection of the sub-task to another pick sub-task refers to the picking sub-task corresponding to the item carrying device, and the two adjacent sub-tasks are sorted according to the sorting sub-task.
  • algorithms for allocating a drive device to an item carrying device include, but are not limited to, an implicit enumeration method, a maximum value allocation method, or a Hungarian algorithm.
  • the execution of these algorithms is as follows.
  • A is a collection of drives and T is a collection of item carriers.
  • C ⁇ R m ⁇ n is a distribution cost matrix indicating the cost of assigning an item carrying device to a driving device, where the cost is the resource consumed.
  • C (i, j) shows a drive means assigned to a i t j article carrying apparatus, the drive means driving a i t j completed article carrier means the length of the chosen sub-consuming task.
  • F represents the total cost of each allocation combination.
  • the constraints of the objective function include: The two constraints respectively indicate that only one item carrying device is assigned to each driving device, and each article carrying device is assigned at most one driving device.
  • the foregoing allocation algorithm may be executed according to a trigger condition, and the trigger condition may include that a preset time period arrives, an allocation instruction is received, or the picking subtask is completed.
  • the trigger condition may include that a preset time period arrives, an allocation instruction is received, or the picking subtask is completed.
  • the higher-ranking sorting sub-tasks may be a sorting sub-task with a waiting time exceeding a certain time threshold, a high-priority picking sub-task, and the like.
  • the technical solution provided by the present application can be applied to picking in a storage space such as a warehouse.
  • warehouses can receive a large number of orders, and the length of the order (the type and quantity of items included in a single order) is long, and the picking pressure of the warehouse is relatively high.
  • This application does not aggregate orders into picking orders based on simple screening criteria but based on picking targets.
  • the picking order can be divided into picking subtasks and sorting the subtasks so that the picking of the picking subtasks meets the picking target.
  • the present application can not only sort the sorting subtasks, but also can schedule the driving devices so that the resources consumed by the driving device to drive the article carrying devices can be satisfied. Resource requirements.
  • FIG. 5 shows a structure of the item picking device provided by the present application, which specifically includes: a memory 501, a processor 502, and a bus 503.
  • the memory 501 is configured to store program instructions and/or data.
  • the processor 502 is configured to perform the following operations by reading instructions and/or data stored in the memory 501:
  • the attribute data determines an execution order of the plurality of picking subtasks.
  • a bus 503 is used to couple the various hardware components of the item picking device together.
  • the processor is configured to determine an execution sequence of the plurality of picking subtasks according to the picking target and the attribute data of the picking subtask, including: the processor is specifically configured to determine the picking subtask a plurality of alternative execution orders; estimating a picking condition of each of the candidate execution orders according to the attribute data of the sorting subtask; and determining an alternate execution order corresponding to the picking condition satisfying the picking target as the picking The order in which tasks are executed.
  • the processor is configured to obtain the at least one picking subtask
  • the method includes: the processor is specifically configured to: when the preset condition is met, obtain at least one picking subtask; wherein the preset condition comprises: generating a picking area corresponding to The picking subtasks complete the picking subtasks corresponding to the picking area, receive the picking subtask sorting instructions, or the sorting cycle arrives.
  • the processor is configured to obtain the at least one picking subtask
  • the method is specifically configured to: select, from the picking subtask corresponding to the item storage space, a plurality of picking subtasks that meet the screening condition; wherein the filtering
  • the condition includes any one or more of the following items: the type of the item in the picking subtask is a specific kind, the picking time of the item in the picking subtask is within a preset duration, and the quantity of the item in the sorting subtask is Within the preset number range.
  • the picking target determined by the processor includes any one of the following items: the picking time is the shortest, and the picking interval duration of the item having the same attribute is the shortest.
  • the processor is further configured to obtain a list of items, and generate a pick list that meets the picking target according to the item list; and divide the items in the picking list that correspond to the same picking area into the same picking subtask.
  • the processor is configured to obtain a list of items, and generate a picking list according to the picking target according to the item list, including: the processor is specifically configured to obtain the item list, and combine the items in the item list Generating a picking list; determining attribute data corresponding to the item in the picking order, and calculating a comprehensive score of the picking order according to the attribute data of the item; and selecting a picking list whose comprehensive score meets the picking target .
  • the processor is further configured to determine a corresponding item carrying device for the picking subtask according to an attribute of the item corresponding to the picking subtask.
  • the processor is further configured to allocate a driving device to the article carrying device, so that the driving device drives the article carrying device to the picking region corresponding to the picking subtask to consume resources to meet resource requirements. .
  • the processor is configured to allocate a driving device to the article carrying device such that the driving device drives the article carrying device to a picking region corresponding to the picking subtask to consume resources that meet resource requirements.
  • the processor is specifically configured to pre-allocate the driving device for the article carrying device, obtain various pre-allocation combinations of the article carrying device and the driving device, calculate resource consumption conditions corresponding to each of the pre-allocated combinations, and select resources A pre-allocated combination that meets the resource requirements as a target allocation combination.
  • FIG. 6 shows a structure of the article picking apparatus provided by the present application, and specifically includes: a picking target determining unit 601, an attribute data determining unit 602, and an execution order determining unit 603.
  • a picking target determining unit 601 configured to determine a picking target and an attribute item associated with the picking target
  • the attribute data determining unit 602 is configured to obtain a plurality of picking subtasks, and determine attribute data of the picking subtask corresponding to the attribute item;
  • the execution order determining unit 603 is configured to determine an execution order of the plurality of picking subtasks according to the picking target and the attribute data of the picking subtask.
  • each unit of the item picking device can be implemented according to the corresponding steps in the above-mentioned item picking method when implementing a specific function, and details are not described herein.

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Abstract

La présente invention concerne un procédé de saisie d'articles et un appareil associé. Le procédé comprend les étapes consistant : à déterminer des cibles de saisie et des attributs associés aux cibles de saisie (S101) ; à acquérir de multiples sous-tâches de saisie à ordonnancer, puis à déterminer des données d'attribut correspondant aux sous-tâches de saisie et aux attributs (S102) ; et à déterminer un ordre d'exécution des multiples sous-tâches de saisie en fonction des cibles de saisie et des données d'attribut des sous-tâches de saisie (S103). Le procédé permet de placer dans un certain ordre des sous-tâches de saisie sur la base des cibles de saisie, de sorte que la réalisation des sous-tâches de saisie répond à une exigence spécifique des cibles de saisie. L'invention concerne également un appareil associé à la saisie d'articles, destiné à appliquer et à mettre en œuvre le procédé.
PCT/CN2018/121446 2017-12-22 2018-12-17 Procédé de saisie d'articles, et appareil associé WO2019120158A1 (fr)

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