WO2019120158A1

WO2019120158A1 - Item picking method, and related apparatus

Info

Publication number: WO2019120158A1
Application number: PCT/CN2018/121446
Authority: WO
Inventors: 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
Priority date: 2017-12-22
Filing date: 2018-12-17
Publication date: 2019-06-27
Also published as: CN109961244A; TW201928811A

Abstract

An item picking method and a related apparatus. The method comprises: determining picking targets and attributes associated with the picking targets (S101); acquiring multiple picking sub-tasks to be put in order, and then determining attribute data corresponding to the picking sub-tasks and the attributes (S102); and determining an execution order of the multiple picking sub-tasks according to the picking targets and the attribute data of the picking sub-tasks (S103). The method arranges an order of the picking sub-tasks on the basis of the picking targets, such that completion of the picking sub-tasks meets a specific requirement of the picking targets. The invention provides an apparatus related to item picking for applying and implementing the method in practice.

Description

Item picking method and related equipment

The present application claims priority to Chinese Patent Application Serial No. No. No. No. No. No. No. No. No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No No

Technical field

The present application relates to the field of warehouse management technology, and more specifically, to an item picking method and related equipment.

Background technique

In the storage space of goods such as warehouses, in order to facilitate the management of articles, 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.

For example, if the item order includes 10 items of 3 types, 2 items of category 1 include 2 items, category 2 items include 4 items, and category 3 items include 4 items, then 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.

At present, the execution order of the picking subtasks is arbitrary, and the completion of the picking usually cannot meet the picking target requirements.

Summary of the invention

In view of this, the present application provides an item picking method such that the completion of the picking subtask meets the preset picking target.

To achieve the stated object, the technical solution provided by the present application is as follows:

In a first aspect, the present application provides an item picking method, including:

Determining a picking target and an attribute item associated with the picking target;

Obtaining a plurality of picking subtasks, and determining attribute data of the picking subtask corresponding to the attribute item;

And determining an execution order of the plurality of picking subtasks according to the picking target and the attribute data of the picking subtask.

In a second aspect, 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:

Determining an execution order of the plurality of picking subtasks according to the picking target and the attribute data of the picking subtask.

In a third aspect, the present application provides 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.

It can be seen from the above technical solution that 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.

DRAWINGS

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings to be used in the embodiments or the prior art description will be briefly described below. Obviously, the drawings in the following description are only It is an embodiment of the present application, and those skilled in the art can obtain other drawings according to the provided drawings without any creative work.

1 is a flow chart of an article picking method provided by the present application;

2A and 2B are schematic diagrams showing two execution sequences of the picking subtasks provided by the present application;

3 is a schematic diagram of an execution sequence of the picking subtask provided by the present application;

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.

FIG. 6 is a schematic structural view of an article sorting apparatus provided by the present application.

Detailed ways

The technical solutions in the embodiments of the present application are clearly and completely described in the following with reference to the drawings in the embodiments of the present application. It is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope are the scope of the present application.

In the storage space of the article, a plurality of storage areas are usually provided for storing different kinds of articles. In practical applications, it is necessary to obtain an item that satisfies the demand from the storage area, and the process is sorted, and the storage area may also be referred to as a picking area.

In order to realize automatic picking work, the article carrying device and the driving device can also be arranged in the object storage space. Wherein the article carrying device is configured to carry articles sorted from the picking area, and 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. In order to facilitate understanding, 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.

Among them, 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.

Generally, there are a plurality of items to be picked in the item list, and there are also a plurality of items to be picked. In order to control the picking process, these items can be picked from the picking area according to the picking target. For example, 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.

Once the picking target is determined, 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.

Among them, the picking target is associated with an attribute item, and the attribute item is an attribute that affects the completion of the picking target. For example, if the picking target is that the picking time of all items in the item list is the shortest, 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. For another example, if 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.

Among them, 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. Of course, it is also possible to set the combined quantity form requirements. For example, if each pick list includes at least two items, then 5 items are combined in a 2 and 3 number form.

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.

Wherein, 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.

In order to calculate 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.

For example, 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 .

For another example, if the workload of the picking area in which the quantity requirement is satisfied in the alternative picking order is high, it is determined that 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.

In order to calculate the score, the conversion relationship between the attribute data of the alternative picking order and the score may be set in advance.

For example, if 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. It should be noted that the corresponding scores mentioned above are merely illustrative examples, and may be other values in practical applications.

Based on the attribute data of the alternative picking order, and the conversion relationship between the attribute data of the picking order and the score, 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.

For example, if the picking target is that the picking time of all items in the item list is the shortest, 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. Regional work efficiency, item picking priority. Therefore, 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.

Of course, if the selection target contains an attribute item, the composite score is obtained from a score.

A14: Select the picking list whose comprehensive score meets the picking target.

Among them, different picking targets have different requirements for comprehensive scores. For example, 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. . For the convenience of description, 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. According to the above technical solution, 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.

It should be noted that 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. Specifically, 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.

Let the collection of the item list be O={o _i }, where o _i represents the item list.

Assuming that the constraint target is the shortest picking time for all items in the item list, 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.

The constraints that the objective function needs to satisfy include the following two items.

Indicates that each item list corresponds to only one alternative picking order; where i represents the serial number of the item list, and x _ij =1 indicates that the item list is added to the alternate picking list.

Indicates that the number of items corresponding to each alternative picking order is within a preset threshold K. Of course, it is also possible to set the weight and type of the items contained in each of the alternative picking orders to not exceed a certain threshold in this form.

According to the constraint condition and the constraint target, after the above objective function is solved, a picking list that satisfies the constraint target can be obtained.

A2: The items in the picking list corresponding to the same picking area are divided into the same picking subtask.

As mentioned above, different kinds of items can be stored in different picking areas. The items corresponding to the same picking area are divided into the same group according to the picking area of the items included in the picking list. Since the picking order can be referred to as a picking task, the grouping of items divided according to the picking list can be referred to as a picking subtask. Among them, the picking subtask means picking items from the picking area.

As can be seen from the above description, 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.

For the description of the selection target, please refer to the above description, which is not described here.

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. Specifically, for an item storage space, 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.

Alternatively, it is also possible to select a plurality of picking subtasks that meet the screening condition from the picking 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.

After obtaining the picking subtask and determining the picking target, it is necessary to determine the attribute data of the picking subtask on the attribute item of the picking target. For example, 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. It should be noted that 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.

Wherein, according to the attribute data of the selected 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.

In a specific implementation, 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.

In particular, the alignment combination method can be used when determining an alternate execution order for the picking subtasks. However, 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.

In particular, since an item carrying tool cannot be sorted at different picking areas at the same time, the picking subtasks corresponding to the same item carrying tool can only be executed sequentially. In addition, the picking ability of the picking area is usually limited. In the case where the picking area has limited picking ability, the same picking area can only perform the sorting work of the picking subtasks in sequence. Using the above two constraints, the execution order that does not satisfy the above constraints can be deleted, thereby obtaining an alternative execution order.

For example, 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. Then, two alternative execution sequences shown in FIGS. 2A and 2B can be obtained. Among them, 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, and 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. For example, 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. For another example, 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.

In order to determine the picking situation of 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.

Taking the picking situation as the picking time length as an example, a method of determining the picking situation of the alternative execution order of the sorting subtasks will be described. 2A and 2B, it is assumed that the execution time of the picking subtask 1 is 1 minute, the execution time of the sorting subtask 2 is 2 minutes, and the execution time of the sorting subtask 3 is 1.5 minutes. Regarding 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.

According to the picking situation corresponding to the alternate execution order, 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.

For example, 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, and 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, and 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.

Then, 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. In this way, 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.

It should be noted that, in practical applications, 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.

Taking the picking target as the shortest picking time of all the items in the item list, 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.

According to the above picking target, it can be determined that the optimization goal is to minimize the completion time of the latest picking subtask, so the objective function constructed is: min C=Max C _ijk .

Where 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.

The 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. Where 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. Where 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 . Where 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 indicates that the pick subtask cannot be interrupted.

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.

According to the above constraints, after the objective function is solved, 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.

See Figure 4A, which shows the execution sequence of the pre-selection sub-tasks not solved using the batch job scheduling algorithm; see Figure 4B, which shows the execution sequence of the post-select sub-tasks using the batch job scheduling algorithm. As shown, 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.

4A and 4B, the order of execution of the picking subtasks is different. After being solved by the batch job scheduling algorithm, 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.

In addition, 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.

Wherein, 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. There may be many different types of item carrying devices, and the types of items that different types of item carrying devices can carry are also different. Therefore, 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.

From the point of view of the item carrying device, 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.

Therefore, if the execution order of the picking subtasks satisfying the picking target is determined according to the picking target, 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.

Wherein, 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. It should be noted that, in this step, 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. Of course, 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.

Specifically, 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.

Before calculating the resource consumption condition corresponding to the pre-allocation combination of the item carrying device and the driving device, the resource item corresponding to the resource requirement needs to be determined. For example, a resource item can be either a duration or a battery. Taking the resource item as the time duration as an example, after determining the resource item, calculating the length of time taken by the driving device in each pre-allocated combination to drive the picking area corresponding to the picking sub-task from the picking area of the picking sub-task to the picking area corresponding to the other picking sub-task . 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.

In practical applications, 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.

Suppose A is a collection of drives and T is a collection of item carriers.

Where a _i represents a drive device in the set of drive devices; i represents the drive device number; m represents the number of drive devices in the set of drive devices.

Where t _j represents an item carrying device in the collection of item carrying devices; j represents the item carrying device serial number; n represents the number of item carrying devices in the set of item carrying devices.

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. In particular, 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.

The objective function of the algorithm is: arg min F=∑x _i,j C(i,j); where x _i,j is a variable of 0 or 1, and x _i,j is 1 means that the driving device a _{i is} assigned to the item bearing Device t _j . 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.

Using the algorithm described above, an optimal solution that satisfies the constraints can be solved, which represents which drive device is assigned to each item carrier.

It should be noted that 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. In addition, for the item carrying device corresponding to the higher-ranking picking sub-task, it is possible to assign the driving device to it preferentially, and then distribute the remaining driving device for the remaining item carrying device in the manner described above. Among them, 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.

As can be seen from the above, the technical solution provided by the present application can be applied to picking in a storage space such as a warehouse. In general, 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. In the case where a plurality of article carrying devices and a plurality of driving devices are simultaneously operated, 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.

The structure of the article sorting apparatus provided by the present application will be described below. As shown in FIG. 5, it 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:

Determining a picking target and an attribute item associated with the picking target; obtaining a plurality of picking subtasks, and determining attribute data of the picking subtask corresponding to the attribute item; and determining, according to the picking target and the selecting subtask 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.

In one example, 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.

In one example, 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.

In an example, 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.

In one example, 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.

In one example, 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.

In one example, 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 .

In one example, 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.

In one example, 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. .

In one example, 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.

The structure of the article sorting apparatus provided by the present application will be described below. As shown in FIG. 6, it 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.

It should be noted that 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.

It should be noted that each embodiment in the specification is described in a progressive manner, and each embodiment focuses on differences from other embodiments, and the same similar parts between the embodiments are referred to each other. can.

It should also be noted that, in this context, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying such entities or operations. There is any such actual relationship or order between them. Furthermore, the term "comprises" or "comprises" or "comprises" or any other variations thereof is intended to encompass a non-exclusive inclusion, such that a process, method, article, or device that comprises a plurality of elements includes not only those elements but also Other elements, or elements that are inherent to such a process, method, item, or device. An element that is defined by the phrase "comprising a ..." does not exclude the presence of additional elements in the process, method, article, or device that comprises the above described elements.

The above description of the disclosed embodiments enables those skilled in the art to make or use the application. Various modifications to these embodiments are obvious to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the application. Therefore, the application is not limited to the embodiments shown herein, but is to be accorded the broadest scope of the principles and novel features disclosed herein.

Claims

An item picking method, comprising:

Determining a picking target and an attribute item associated with the picking target;

Obtaining a plurality of picking subtasks, and determining attribute data of the picking subtask corresponding to the attribute item;

Determining 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 according to claim 1, wherein the determining the execution order of the plurality of picking subtasks according to the attribute data of the picking target and the picking subtask comprises:

Determining a plurality of alternative execution orders of the picking subtasks;

Estimating the picking condition of each of the alternative execution orders according to the attribute data of the picking subtask;

The alternative execution order corresponding to the picking condition that satisfies the picking target is determined as the execution order of the picking subtasks.
The article picking method according to claim 1, wherein said obtaining at least one picking subtask comprises:

When the preset condition is met, at least one picking subtask is obtained; wherein the preset condition includes: generating a picking subtask corresponding to the picking area, completing the picking subtask corresponding to the picking area, receiving the sorting subtask sorting instruction, or sorting The cycle arrives.
The article picking method according to claim 1, wherein said obtaining at least one picking subtask comprises:

Selecting, from the picking subtask corresponding to the storage space of the item, a plurality of picking subtasks that meet the screening condition; wherein the screening condition includes any one or more of the following items: the type of the item in the sorting subtask is a specific type The selection duration of the items in the sub-tasks is within the preset duration, and the number of items in the sub-tasks is within a preset amount.
The article picking method according to claim 1, wherein the picking target includes any one of the following items: the picking time is the shortest, and the picking interval length of the item having the same attribute is the shortest.
The article picking method according to claim 1, wherein the manner of generating the picking subtask comprises:

Obtaining a list of items, and generating a picking order according to the picking target according to the item list;

The items corresponding to the same picking area in the picking list are divided into the same picking subtasks.
The article picking method according to claim 6, wherein the obtaining the item list and generating the picking list according to the picking target according to the item list comprises:

Obtaining a list of items and combining the items in the list of items to generate 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 attribute data of the item;

Select a picking list with a comprehensive score that matches the picking target.
The article picking method according to claim 1, further comprising:

Determining a corresponding item carrying device for the picking subtask according to an attribute of the item corresponding to the picking subtask.
The article picking method according to claim 8, further comprising:

A drive device is assigned to the article carrying device such that the drive device drives the article carrier device to the picking area corresponding to the picking subtask to meet resource requirements.
The article picking method according to claim 9, wherein said assigning means for said article carrying device is such that said driving device drives said article carrying device to a picking region corresponding to said picking subtask The resources consumed meet the resource requirements, including:

Pre-dispensing the driving device for the article carrying device to obtain various pre-allocation combinations of the article carrying device and the driving device;

Calculating resource consumption conditions corresponding to each of the pre-allocated combinations;

A pre-allocated combination that meets the resource requirements is selected as the target allocation combination.
An item picking device, comprising: a processor and a memory, the processor performing at least the following steps by running a software program stored in the memory, calling data stored in the memory:

Determining a picking target and an attribute item associated with the picking target;

Obtaining a plurality of picking subtasks, and determining attribute data of the picking subtask corresponding to the attribute item;

Determining 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 apparatus according to claim 11, wherein the processor 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, including:

a processor, specifically for determining a plurality of alternative execution orders of the picking subtasks; estimating, according to the attribute data of the picking subtasks, a picking condition of each of the alternative execution orders; and meeting the picking target The alternate execution order corresponding to the picking situation is determined as the execution order of the picking subtasks.
The article picking apparatus according to claim 11, wherein said processor is configured to obtain at least one picking subtask, comprising:

The processor is configured to obtain at least one picking subtask when the preset condition is met; wherein the preset condition includes: generating a picking subtask corresponding to the picking area, completing the picking subtask corresponding to the picking area, and receiving the picking subroutine The task sort instruction, or the sort cycle arrives.
The article picking device according to claim 11, wherein the processor is configured to obtain at least one picking subtask, comprising:

The processor is specifically configured to: select, from the picking subtask corresponding to the storage space of the item, a plurality of picking subtasks that meet the screening condition; wherein the screening condition includes any one or more of the following items: selecting the subtask The type of the item is a specific type, the picking time of the item in the picking subtask is within the preset duration, and the number of items in the sorting subtask is within a preset number range.
The article sorting apparatus according to claim 11, wherein

The processor is further configured to obtain a list of items, and generate a picking order according to the picking target according to the item list; and divide the items in the picking list corresponding to the same picking area into the same picking subtask.
The article picking device according to claim 15, wherein 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, comprising:

a processor, specifically for obtaining a list of items, and combining the items in the item list to generate a picking list; determining attribute data corresponding to the item in the picking order and according to attributes of the item Data, calculating a comprehensive score of the picking order; and selecting a picking list whose comprehensive score meets the picking target.
The article sorting apparatus according to claim 11, wherein

The processor is further configured to determine, according to an attribute of the item corresponding to the picking subtask, a corresponding item carrying device for the picking subtask.
The article sorting apparatus according to claim 17, wherein

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 area corresponding to the picking subtask to consume resources to meet resource requirements.
The article picking apparatus according to claim 18, wherein said processor is configured to assign a driving device to said article carrying device to cause said driving device to drive said article carrying device to said picking subtask corresponding The resources spent in the picking area meet the resource requirements, including:

a processor, specifically for pre-allocating a driving device for the article carrying device, obtaining a plurality of pre-allocation combinations of the article carrying device and the driving device; calculating a resource consumption condition corresponding to each of the pre-allocated combinations; and selecting a resource consumption situation A pre-allocated combination that meets the resource requirements is used as the target allocation combination.
An article sorting device, comprising:

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.