An order picking control method for a mobile robotic warehousing system

Abstract

This invention discloses an order picking control method for a mobile robot warehousing system, comprising the following steps: S1, acquiring data information from the mobile robot warehousing system; S2, determining an order picking strategy based on the data information; S3, determining order allocation and shelf inventory allocation results based on the picking strategy, and generating task records; S4, generating task assignments based on the task records and executing picking operations according to the task assignments; reducing the number of shelf movements required to complete all picking tasks, improving shelf hit rate, reducing picking station working time, and improving warehouse picking efficiency; significantly improving warehouse order picking efficiency, increasing overall throughput, reducing energy consumption and carbon emissions; and simultaneously solving the problems of order allocation and shelf inventory allocation.

Description

Technical Field

[0001] This invention relates to the field of warehouse order optimization control, and more particularly to an order picking control method for a mobile robot warehousing system. Background Technology

[0002] With the rapid development of the e-commerce industry and increasingly stringent consumer demands for delivery times, many large e-commerce companies are placing greater emphasis on improving order picking efficiency within their warehouses. The entire order picking control method consists of order allocation methods (i.e., which orders are assigned to the same picking station and the specific order picking order sequence) and shelf inventory allocation methods (i.e., which SKUs on which shelves are selected to fulfill the order). We have found that order allocation methods and shelf inventory allocation methods are direct factors affecting the order picking efficiency of this type of system.

[0003] Among existing companies using mobile robot warehousing systems, the vast majority rely on experience-based picking control methods. Their methods separate order allocation from shelf inventory allocation, developing separate approaches for each. The current picking control methods first allocate shelf inventory to each order to minimize the required number of shelves (i.e., shelf inventory allocation method). Then, based on the similarity between orders, they group orders into batches and assign all orders in each batch to the same picking station (i.e., order allocation method). Because these picking control methods are outdated, these companies' warehousing systems have low average shelf hit rates, require handling a large number of shelves to complete order picking tasks, and have very low warehouse order picking efficiency. This not only leads to significant robot energy consumption but also necessitates a large number of mobile robots in the warehouse, greatly increasing the company's facility costs.

[0004] For example, a "robot-based warehouse order picking method" disclosed in Chinese patent literature, publication number CN109544068A, discloses a method that includes instructing pickers to pick goods from corresponding storage locations and place them in the turnover location according to the placement marks, which also has the above-mentioned problems. Summary of the Invention

[0005] To address the problems of low picking efficiency and high operating costs in existing technologies, this invention provides an order picking control method for mobile robot warehousing systems, which can significantly improve the operational efficiency of warehousing systems, reduce robot energy consumption, and greatly reduce carbon emissions.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for order picking control in a mobile robot warehousing system includes the following steps: S1, acquiring data information from the mobile robot warehousing system; S2, determining an order picking strategy based on the data information; S3, determining order allocation and shelf inventory allocation results based on the picking strategy, and generating task records; S4, generating task assignments based on the task records and executing picking operations according to the task assignments. This method improves picking efficiency and reduces operating costs by optimizing order allocation and shelf inventory allocation.

[0008] Preferably, step S1 includes: acquiring data information from the mobile robot warehousing system, including order information, shelf information, and picking station information; order information includes: all orders to be picked, the inventory units contained in each order, and the quantity required for each type of inventory unit; shelf information includes: all available shelves in the picking area, the inventory units s stored on each shelf, and the quantity of each type of inventory unit; picking station information includes: all available picking stations. This allows for the acquisition of all orders and the storage space on all shelves, enabling optimization based on all inventory units and picking stations.

[0009] Preferably, step S2 includes:

[0010] S2.1. Using L order L represents the set of unassigned orders; rack Indicates the set of available shelves;

[0011] S2.2. If Stop the algorithm and output all task records (γ) b ,o i ,s,r j ,q);

[0012] S2.3. Based on the δ corresponding to each order i , will L order All orders are based on |δ i The order sequence Γ is obtained by arranging the values ​​of | in non-increasing order.

[0013] S2.4. According to each picking station γ b Number of allocated order lines All picking stations according to The sizes are arranged in non-decreasing order to obtain the picking station sequence E;

[0014] S2.5. Take the first order o in Γ τ And the corresponding δ for this order τ The shelves in the middle are assigned to the first picking station in E. σ At the same time, the order was transferred from L order Remove from, i.e., α σ=α σ +o τ ,β σ =β σ ∪δ τ ,L order =L order -o τ ;

[0015] S2.6. Traversing L order Find all orders that meet the requirements. Orders meeting certain conditions form an order set Ω, i.e. Select some orders from Ω and assign them to picking station γ. σ ;

[0016] S2.7. According to α σ and β σ , allocate β σ Generate task records for inventory on the middle shelf;

[0017] S2.8. Calculate α σ Not beta σ The shelves in the storage unit set S satisfy the following conditions: ′ ,Right now if Then return S2.2; otherwise, return S. ′ Select a batch of shelves Ψ to meet the requirements. Assign the shelves in Ψ to picking stations γ σ , i.e. β σ =β σ ∪Ψ, return to S2.7. It can allocate based on order sequence and picking sequence, making it easier to select more suitable shelves to complete order picking and better allocate shelf inventory.

[0018] Preferably, S22 includes: S2.2.1. For order o i ∈L order Initialize δ i =L rack Calculate r for each shelf j ∈L rack with o i The common set of inventory units Φ i,j , that is Φ i,j =S i ∩U j ;

[0019] S2.2.2. All Φ i,j According to |Φ i,j The values ​​of | are arranged in non-decreasing order, for r j′ and r j″ ,if So, let's move the shelf r j′ From δ i Remove from the list. It can be determined that all shelves are in use.

[0020] Preferably, S26 includes:

[0021] S2.6.1. Transfer the orders in Ω according to |δ i The order sequence Γ is obtained by arranging the values ​​of the items in non-decreasing order. ′ ;

[0022] S2.6.2 Traversing Γ ′ The orders in the middle, for Γ ′ Orders in ω ,if Then o ω Add to α σ In, i.e., α σ =α σ +o ω ,L order =L order -o ω Otherwise, proceed directly to S2.7. This allows for the iteration through all orders.

[0023] Preferably, step S3 includes calculating α σ Not beta σ The shelves in the storage unit set S satisfy the following conditions: ′ ,Right now Based on the control method, calculate the order allocation and shelf inventory allocation results, and generate task records; including: setting L order =O,L rack =R, call the S2 control method to perform calculations, and obtain all task records (γ) b ,o i ,s,r j (q). It is possible to obtain inventory units that are not fulfilled by the shelf.

[0024] Preferably, S3 includes: S31, for S ′ Initialize Ψ = L rack Calculate r for each shelf j ∈L rack With S ′ The common set of inventory units Φ j ′ , that is Φ j ′ =S ′ ∩U j ;

[0025] S32.、All Φ j′ According to |Φ j ′ The values ​​of | are arranged in non-decreasing order, for r j′ and r j″ ,if So, let's move the shelf r j′ Remove from Ψ. Able to select shelves.

[0026] Preferably, S4 includes generating a task assignment list based on all task records and executing picking operations according to the task assignment list. That is, based on the task assignment list, the mobile robot warehousing system issues picking tasks one by one, determining which picking station to pick each inventory unit in each order, which shelf to move to the picking station, and how many inventory units to pick from the shelf. This enables optimized control of each inventory unit.

[0027] Preferably, a picking evaluation is conducted after the picking operation. This evaluation includes using multiple metrics, such as improvements in work efficiency and shelf hit rate, and a percentage increase in average work efficiency at the picking station (Δ). we The average working time of the picking station was reduced by a percentage Δ wt The percentage decrease in the total number of shelf tasks Δ rn and the percentage increase in average shelf hit rate Δ rs Four indicators are used for measurement; the calculation formulas for the four indicators are expressed by equations (1) to (4):

[0028]

[0029] Wherein, WE(P) refers to the average working efficiency of the picking station when all picking tasks are completed according to the results of experience-based decision-making, and WE(A) is the average working efficiency of the picking station when all picking tasks are completed according to the results of control methods.

[0030]

[0031] WT(P) refers to the average working time of the picking station when all picking tasks are completed according to the results of empirical decision-making, and WT(A) is the average working time of the picking station when all picking tasks are completed according to the results of the control method.

[0032]

[0033] Wherein, RN(P) refers to the total number of shelf tasks when all picking tasks are completed according to the empirical decision-making results, and RN(A) is the total number of shelf tasks when all picking tasks are completed according to the control method results.

[0034]

[0035] Here, RS(P) refers to the average shelf hit rate when all picking tasks are completed based on empirical decision-making results, and RS(A) refers to the average shelf hit rate when all picking tasks are completed based on control method results. This allows for the evaluation of the effectiveness of the picking process.

[0036] The present invention has the following advantages:

[0037] The order picking control method for mobile robot warehousing systems provided by this invention differs from existing methods that address order allocation and shelf inventory allocation separately; instead, it solves both problems simultaneously. Compared to existing methods, this invention can more rationally allocate orders to picking stations, select more suitable shelves to complete order picking, and better allocate shelf inventory. This reduces the number of shelf movements required to complete all picking tasks, increases shelf hit rate, reduces picking station working time, and improves warehouse picking efficiency. Multiple simulation experiments have shown that, compared to existing enterprise control methods, the order picking control method proposed in this invention can improve picking station efficiency by at least 41%, shorten picking station working time by 44%, reduce the number of shelf movements required by 33%, and increase shelf hit rate by 51%. Therefore, by applying the control method of this invention, enterprises can significantly improve warehouse order picking efficiency, increase overall throughput, and reduce energy consumption and carbon emissions. Attached Figure Description

[0038] The accompanying drawings described below are merely exemplary. Those skilled in the art can derive other embodiments based on the provided drawings without any inventive effort.

[0039] Figure 1 This is a flowchart of an order picking control method for a mobile robot warehousing system provided in an embodiment of the present invention. Detailed Implementation

[0040] The following specific embodiments illustrate the implementation of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0041] like Figure 1As shown, in a preferred embodiment, the present invention discloses an order picking control method for a mobile robot warehousing system, including step 1. Obtaining data information of the mobile robot warehousing system, including order information, shelf information, and picking station information; the order information includes: all orders to be picked, the inventory units (hereinafter referred to as SKUs) contained in each order, and the quantity required for each SKU; the shelf information includes: all available shelves in the picking area, the SKUs stored on each shelf, and the quantity of each SKU stored; the picking station information includes: all available picking stations. All orders to be picked are represented by a set O, and each order is represented as... Order o i The set of SKUs included is denoted as S. i The required quantity for each SKU is expressed as s represents a SKU; all available shelves are represented by a set R, and each shelf is represented as . Shelf r j The set of SKUs stored above is represented as U j The quantity of each SKU stored is expressed as All available picking stations are represented by set B, using This represents each picking station.

[0042] Step 2. Based on the acquired data, construct an order picking control method; including the following steps:

[0043] Step 2.1. Use L order L represents the set of unassigned orders; rack Indicates the available shelf set; the maximum number of order lines that can be assigned to a picking station. for Let α represent the set of shelves that have been assigned. b Represents the set of orders that have been assigned, set

[0044] Step 2.2. If Stop the algorithm and output all task records (γ) b ,o i ,s,r j ,q); where, (γ b ,o i ,s,r j ,q) represents order o i Assigned to picking station γ b Select shelf r j Come and choose i Includes SKUs, and from r j q items were selected; otherwise, o items were selected based on each order. i ∈L orderThe corresponding S i Without considering In the case of allocating a batch of shelves for each order This ensures that the SKUs stored on the allocated shelves include S i ,Right now For each order i ∈L order Allocation δ i The method is as follows:

[0045] Step 2.2.1. For order o i ∈L order Initialize δ i =L rack Calculate r for each shelf j ∈L rack with o i The common set of SKUs Φ i,j , that is Φ i,j =S i ∩U j ;

[0046] Step 2.2.2. Put all Φ i,j According to |Φ i,j The values ​​of | are arranged in non-decreasing order, for r j′ and r j″ ,if So, let's move the shelf r j′ From δ i Remove from the middle.

[0047] Step 2.3. Based on the δ corresponding to each order i , will L order All orders are based on |δ i The order sequence Γ is obtained by arranging the values ​​of | in non-increasing order.

[0048] Step 2.4. Based on each picking station γ b Number of allocated order lines All picking stations according to The sizes are arranged in non-decreasing order to obtain the picking station sequence E.

[0049] Step 2.5. Take the first order o in Γ τ And the corresponding δ for this order τ The shelves in the middle are assigned to the first picking station in E. σ At the same time, the order was transferred from L order Remove from, i.e., α σ =α σ +o τ ,β σ =β σ ∪δτ ,L order =L order -o τ ;

[0050] Step 2.6. Traverse L order Find all orders that meet the requirements. Orders meeting certain conditions form an order set Ω, i.e. Select some orders from Ω and assign them to picking station γ. σ Select some orders from Ω and assign them to picking station γ. σ The method is as follows:

[0051] Step 2.6.1. Transfer the orders in Ω according to |δ i The order sequence Γ′ is obtained by arranging the values ​​of | in non-decreasing order.

[0052] Step 2.6.2. Traverse the orders in Γ′, for each order o in Γ′ ω ,if Then o ω Add to α σ In, i.e., α σ =α σ +o ω ,L order =L order -o ω Otherwise, proceed directly to step 2.7.

[0053] Step 2.7. According to α σ and β σ , allocate β σ Inventory on the middle shelf, generate task records; allocate β σ The methods for managing inventory on the mid-shelf and generating task records are as follows:

[0054] Step 2.7.1. Initialization: n = 1, m = 1.

[0055] Step 2.7.2. Select β σ The nth shelf r n and α σ The m-th order o m ,for

[0056] if Generate task records Place S m =S m -s;

[0057] if Generate task records Place S m =S m -s,U n =U n -s;

[0058] if Generate task records Place U n =U n -s.

[0059] Step 2.7.3. If shelf r n From L rack Remove from L rack =L rack -r n .

[0060] Step 2.7.4. If n = |β σ |,m=|α σ |, proceed to step 2.8.; otherwise, if m = |α σ If n = n + 1 and m = 1, return to (b); otherwise, if m = m + 1, return to step 2.7.2.

[0061] Step 3. Calculate α σ Not beta σ The shelves in the data satisfy the set S′ of SKUs, that is if Then return to step 2.2; otherwise, select a batch of shelves Ψ for S′ such that they satisfy... Assign the shelves in Ψ to picking stations γ σ , i.e. β σ =β σ ∪Ψ; Return to step 2.7. The method used to select a batch of shelves Ψ for S′ is as follows:

[0062] Step 2.8.1. For S′, initialize Ψ = L rack Calculate r for each shelf j ∈L rack The SKU set Φ contained together with S′ j ′, i.e. Φ j ′=S′∩U j ;

[0063] Step 2.8.2. Put all Φ j According to |Φ j The values ​​of ′| are arranged in non-decreasing order for r. j′ and r j″ ,if So, let's move the shelf r j′ Remove from Ψ.

[0064] Step 3. Based on the control method, calculate the order allocation and shelf inventory allocation results, and generate task records; including: setting L order =O,L rack =R, call the control method in step 2 to perform calculations, and obtain all task records (γ) b ,o i ,s,r j ,q).

[0065] Step 4. Generate a task assignment sheet with the fields shown in Table 1 based on all task records, and execute the picking operation according to the task assignment sheet; that is, according to the task assignment sheet, the mobile robot warehousing system issues picking tasks one by one, determines which picking station to pick each SKU in each order, selects which shelf to move to the picking station, and how many SKUs to pick from the shelf.

[0066] Table 1. Illustration of fields published under task

[0067] <![CDATA[γ b ]]> <![CDATA[o i ]]> s <![CDATA[r j ]]> q

[0068] Based on the current state of picking operations in enterprise warehousing systems according to this invention, and to intuitively demonstrate the effectiveness of the order picking control method proposed in this invention, subsequent embodiments will use the percentage increase Δ in the average working efficiency of the picking station when all picking tasks are completed. we The average working time of the picking station was reduced by a percentage Δ wt The percentage decrease in the total number of shelf tasks Δ rn and the percentage increase in average shelf hit rate Δ rs Four indicators are used for measurement. The calculation formulas for the four indicators are expressed by equations (1) to (4):

[0069]

[0070] Wherein, WE(P) refers to the average working efficiency of the picking station when all picking tasks are completed according to the results of experience-based decision-making, and WE(A) is the average working efficiency of the picking station when all picking tasks are completed according to the results of control methods.

[0071]

[0072] WT(P) refers to the average working time of the picking station when all picking tasks are completed according to the results of empirical decision-making, and WT(A) is the average working time of the picking station when all picking tasks are completed according to the results of the control method.

[0073]

[0074] Wherein, RN(P) refers to the total number of shelf tasks when all picking tasks are completed according to the empirical decision-making results, and RN(A) is the total number of shelf tasks when all picking tasks are completed according to the control method results.

[0075]

[0076] Among them, RS(P) refers to the average shelf hit rate when all picking tasks are completed according to the results of empirical decision-making, and RS(A) is the average shelf hit rate when all picking tasks are completed according to the results of control methods.

[0077] In the second embodiment, the data information is as follows: 3,000 orders to be picked, the SKUs contained in each order and the required quantity are known; 2,021 available shelves, the SKUs stored on each shelf and the quantity stored are known; and 29 available picking stations.

[0078] Implementation Step 1. Based on the data information used in Example 1, set the values ​​of each parameter in Step 1 of the control method, including 0, 0, etc. i S i , R, r j U j , B and γ b .

[0079] Implementation step 2. Set L order =O,L rack =R, call the control method step 2. The method content performs calculations to obtain all task records (γ). b ,o i ,s,r j In this embodiment, a total of 12,042 task records were obtained.

[0080] Implementation step 3. Based on all task records (γ) b ,o i ,s,r j ,q), generate the task list with the fields shown in Table 1 in step 4 of the control method, and execute the picking operation according to the task list.

[0081] To more intuitively demonstrate how this invention can significantly improve the order picking efficiency of mobile robot warehousing systems, we will compare the order picking operation results using the order picking control method proposed in this invention with the order picking operation results using the existing experience-based control methods of leading companies. The improvement will be measured by the percentage increase Δ in the average work efficiency of the picking station. we The average working time of the picking station was reduced by a percentage Δ wt The percentage decrease in the total number of shelf tasks Δ rnand the percentage increase in average shelf hit rate Δ rs The results of comparing the four indicators are shown in Table 2.

[0082] Table 2. Comparison of order picking results in Example 2

[0083]

[0084] As can be seen in Example 2, the order picking control method of the present invention can improve the picking station efficiency by 41.92%, shorten the picking station working time by 44.62%, reduce the shelving tasks that need to be moved by 33.71%, and increase the shelving hit rate by 51.18%.

[0085] In the third embodiment, the data information used in embodiment 3 is described as follows: 4,000 orders to be picked, the SKUs contained in each order and the required quantity are known; 2,021 available shelves, the SKUs stored on each shelf and the quantity stored are known; 29 available picking stations.

[0086] Implementation Step 1. Based on the data information used in Example 3, set the values ​​of each parameter in Step 1 of the control method, including 0, 0, etc. i S i , R, r j U j , B and γ b .

[0087] Implementation step 2. Set L order =O,L rack =R, call the control method step 2. The method content performs calculations to obtain all task records (γ). b ,o i ,s,r j In this embodiment, a total of 15,752 task records were obtained.

[0088] Implementation step 3. Based on all task records (γ) b ,o i ,s,r j ,q), generate the task list with the fields shown in Table 1 in step 4 of the control method, and execute the picking operation according to the task list.

[0089] To more intuitively demonstrate how this invention can significantly improve the order picking efficiency of mobile robot warehousing systems, we will compare the order picking operation results using the order picking control method proposed in this invention with the order picking operation results using the existing experience-based control methods of leading companies. The improvement will be measured by the percentage increase Δ in the average work efficiency of the picking station. weThe average working time of the picking station was reduced by a percentage Δ wt The percentage decrease in the total number of shelf tasks Δ rn and the percentage increase in average shelf hit rate Δ rs The results of comparing the four indicators are shown in Table 3.

[0090] Table 3. Comparison of order picking results in Example 3

[0091]

[0092] As can be seen in Example 3, the order picking control method of the present invention can improve the picking station efficiency by 49.58%, shorten the picking station working time by 43.62%, reduce the shelving tasks that need to be moved by 36.77%, and increase the shelving hit rate by 57.89%.

[0093] In the fourth embodiment, the data information used in embodiment 4 is described as follows: 10,000 orders to be picked, the SKUs contained in each order and the required quantity are known; 2,015 available shelves, the SKUs stored on each shelf and the quantity stored are known; 29 available picking stations.

[0094] Implementation Step 1. Based on the data information used in Example 4, set the values ​​of each parameter in Step 1 of the control method, including 0, 0, etc. i S i , R, r j U j , B and γ b .

[0095] Implementation step 2. Set L order =O,L rack =R, call the control method step 2. The method content performs calculations to obtain all task records (γ). b ,o i ,s,r j In this embodiment, a total of 33,074 task records were obtained.

[0096] Implementation step 3. Based on all task records (γ) b ,o i ,s,r j ,q), generate the task list with the fields shown in Table 1 in step 4 of the control method, and execute the picking operation according to the task list.

[0097] To more intuitively demonstrate how this invention can significantly improve the order picking efficiency of mobile robot warehousing systems, we will compare the order picking operation results using the order picking control method proposed in this invention with the order picking operation results using the existing experience-based control methods of leading companies. The improvement will be measured by the percentage increase Δ in the average work efficiency of the picking station. we The average working time of the picking station was reduced by a percentage Δ wt The percentage decrease in the total number of shelf tasks Δ rn and the percentage increase in average shelf hit rate Δ rs The results of comparing the four indicators are shown in Table 3.

[0098] Table 3. Comparison of order picking results in Example 4

[0099]

[0100] As can be seen in Example 4, the order picking control method of the present invention can improve the picking station efficiency by 55.46%, shorten the picking station working time by 39.14%, reduce the shelving tasks that need to be moved by 40.59%, and increase the shelving hit rate by 68.49%.

[0101] In summary, the order picking control method for mobile robot warehousing systems proposed in this invention obtains task records, i.e., order allocation and shelf inventory allocation results, by continuously cyclically allocating orders and shelf inventory. Comparison with empirical control methods shows that the control method of this invention can significantly improve picking station efficiency, reduce the total number of shelf tasks for all picking tasks, and increase shelf hit rate, thereby significantly shortening completion time, improving order picking efficiency, and reducing enterprise warehouse operating costs.

[0102] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. An order picking control method for a mobile robot warehousing system, characterized in that, Includes the following steps: S1. Obtain data information from the mobile robot warehousing system; S2. Determine the order picking strategy based on the data information; S3. Determine the order allocation and shelf inventory allocation results based on the picking strategy, and generate task records; S4. Generate a task list based on the task record and execute the picking operation according to the task list; S2 includes: S2.

1. Using This represents the set of unassigned orders. Indicates the set of available shelves; S2.

2. If Stop the algorithm and output all task records. , where the parameters Indicates the picking station number, Indicates order number, Indicates material number, Indicates shelf number, Indicates the quantity of materials; S2.

3. Based on each order ,Will All orders according to The sizes are arranged in non-increasing order to obtain the order sequence. ,in, Represented as an order The allocated set of shelves; S2.

4. According to each picking station Number of allocated order lines All picking stations according to The sizes are arranged in non-decreasing order to obtain the picking station sequence. ; S2.

5. [The following appears to be a separate, unrelated sentence:] Will The first order and the corresponding order The shelves in the middle are assigned to The first picking station in At the same time, the order was transferred from Remove from the middle, that is ,in, This indicates that it has been assigned to a picking station. A collection of shelves, This indicates that it has been assigned to a picking station. The order collection; S2.

6. Traversal Find all orders that meet the requirements. Orders that meet certain conditions form an order set. ,Right now ,from Select some orders to assign to the picking station , where the parameters Indicates order Included SKU set, Indicates shelf The SKU set stored above; S2.

7. According to and ,distribute Generate task records for inventory on the middle shelf; S2.

8. Calculate China was not The set of inventory units satisfied by the shelves in the middle ,Right now ,if If yes, then return S2.2; otherwise, return S2.

2. Select a batch of shelves To satisfy ,Will The shelves in the middle are allocated to the picking station ,Right now Return to S2.7; where the parameter Indicates order For SKU The required quantity; S2.2 includes: S2.2.

1. For orders ,initialization Calculate each shelf and Commonly contained set of inventory units ,Right now ; S2.2.

2. All of them according to The sizes are arranged in non-decreasing order. and ,if So, the shelves from Remove from, among which parameters and They represent the numbers respectively. and The shelves, and satisfy the set of SKUs they contain. and With orders Included SKU set There is an intersection; S2.6 includes: S2.6.

1. Will Orders in the order book The sizes are arranged in non-decreasing order to obtain the order sequence. ; S2.6.

2. Traversal For orders in the middle, any one of the orders ,if , then Add to In, that is Otherwise, proceed directly to S2.7; where the parameters express The number in orders, Indicates order The set of SKUs included This indicates the maximum number of order lines that can be allocated to each picking station.

2. The order picking control method for a mobile robot warehousing system according to claim 1, characterized in that, Step S1 includes: acquiring data information from the mobile robot warehousing system, including order information, shelf information, and picking station information; order information includes: all orders to be picked, the inventory units contained in each order, and the quantity required for each type of inventory unit; shelf information includes: all available shelves in the picking area, the inventory units stored on each shelf, and the quantity of each type of inventory unit; picking station information includes: all available picking stations.

3. The order picking control method for a mobile robot warehousing system according to claim 1, characterized in that, The implementation of S3 includes calculating China was not The set of inventory units satisfied by the shelves in the middle ,Right now ; Based on the control method, calculate the order allocation and shelf inventory allocation results, and generate task records, including: setting , The control method described in S2 is invoked to perform calculations and obtain all task records. , where the parameters This represents the initial set of all available shelves in the warehouse, with parameters... This represents the initial set of all orders to be picked.

4. The order picking control method for a mobile robot warehousing system according to claim 3, characterized in that, The S3 mentioned above includes: S3.1, for Initialize the shelf set Calculate each shelf and Commonly contained set of inventory units ,Right now ; S3.

2. All of them according to The sizes are arranged in non-decreasing order. and ,if So, the shelves from Remove from the middle.

5. The order picking control method for a mobile robot warehousing system according to claim 4, characterized in that, The S4 includes generating a task assignment list based on all task records and executing picking operations according to the task assignment list. That is, according to the task assignment list, the mobile robot warehousing system issues picking tasks one by one, determining which picking station to pick each inventory unit in each order, selecting which shelf to move to the picking station, and how many inventory units to pick from the shelf.

6. The order picking control method for a mobile robot warehousing system according to claim 5, characterized in that, The picking evaluation is performed after the picking operation is carried out. The picking evaluation is implemented by using multiple indicators, including determining the improvement of work efficiency and the improvement of shelf hit rate.

Images