Layout optimization method of intelligent warehouse and intelligent warehousing system

Abstract

The invention discloses a layout optimization method of an intelligent warehouse and an intelligent warehousing system, and relates to the technical field of intelligent warehouses. The method comprises a goods allocation layout step: obtaining warehouse plane size information and goods shelf plane size information; obtaining a preset warehouse layout rule which comprises an operation unit size configuration rule and a goods allocation size configuration rule; according to the plane size of the warehouse, based on the plane size of the operation units configured in the rule, determining the number K of the operation units capable of being arranged in the to-be-arranged warehouse; according to the plane size of the goods shelf, the plane size of the goods allocation is determined based on the goods allocation allowance configured in the rule, and one goods allocation is used for placing one goods shelf; according to the plane size of the operation unit and the plane size of the goods allocation, the total number of the goods allocation capable of being arranged in one operation unit is determined. The space utilization efficiency of the warehouse and the operation efficiency of goods entering and exiting from the warehouse are both considered, the operation units can be flexibly deployed according to needs, and the expandability is high.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent warehouses, and in particular to a layout optimization method for intelligent warehouses and an intelligent warehousing system. Background Art

[0002] Traditional warehouses rely primarily on manual labor for the handling, shelving, dispatching, and shipping of goods. Upon receiving an order, a worker pushes a cart into the warehouse, removes goods from the shelves in sequence according to the order, and manually enters the removed goods into the system. This traditional dispatching method, a "person-to-goods" approach, is highly reliant on manual labor, resulting in low processing efficiency, prone to errors, and high labor costs. With the rise of e-commerce and the rapid development of technologies such as the Internet of Things, robotic handling, and artificial intelligence, high-flow intelligent warehouses have become a necessity for many companies.

[0003] To achieve warehouse automation, warehouses are typically equipped with integrated racks, forklifts, stackers, elevators, conveyor belts, and other transportation equipment, combined with advanced warehouse management systems (WMS) to optimize the automated storage, retrieval, and distribution of goods. However, direct-to-consumer warehouses, such as those in e-commerce and retail, are characterized by high mobility and a diverse and dispersed inventory. These fully automated warehousing systems are inefficient when retrieving small batches of multiple items. Consequently, existing technologies offer intelligent warehousing systems that utilize a "goods-to-person" approach. These systems primarily leverage the autonomous task-acceptance and execution capabilities of intelligent handling robots (currently commonly used intelligent handling robots are AGVs, or Auto Guide Vehicles). These robots automatically transport shelves within the warehouse and deliver them to designated sorting locations (or sorting platforms or workstations), where workers perform item sorting and warehousing operations. The handling robots then automatically carry the shelves back to their original storage locations, place them down, and await the next task. This system uses robots to transport shelves while human sorters pick items from fixed sorting locations. This is a "goods-to-person" approach, eliminating the need for human sorters to enter the warehouse during the entire sorting process. This significantly improves efficiency and saves significant manpower, making it particularly suitable for consumer-oriented sales scenarios with a wide variety of goods. In existing intelligent warehousing systems, the "goods-to-person" approach, assisted by intelligent robots, has become a common operating mode.

[0004] In order to improve the efficiency of the intelligent warehousing system in the above-mentioned "goods to person" operation mode, practitioners have conducted optimization research from many aspects. As an example, Chinese patent ZL201810079319.6 discloses a large-scale intelligent warehousing distributed picking system, including a central control server, multiple sorting stations, multiple mobile robots, multiple movable shelves and multiple scheduling servers. The central control server communicates with multiple sorting stations and multiple scheduling servers by wire, and each mobile robot communicates with the scheduling server wirelessly and completes the transportation of different mobile shelves according to the system's instructions. Each scheduling server is set in different areas of the warehouse and completes the task scheduling of the mobile robots with the assistance of the central control server, and controls the mobile robots to avoid collisions during operation. The layout of the entire system is adjusted according to the size and shape of the warehouse. It also discloses the layout plan of the warehouse, as follows: the entire warehouse is mapped in the form of a grid, with the side length of the grid set to 1m, to construct a grid map, which is stored in the central control server. A QR code label recording the location information of the grid is affixed to the center of each grid; then, the central control server is deployed at the edge of the warehouse, and the six sorting stations are evenly deployed at the edge of the warehouse, and are connected to the central control server through wired connections; then, the movable shelves are regularly arranged in the center of the warehouse, and each shelf is located in the center of the grid, forming a shelf array with multiple rows and columns, and forming a cargo rack in the form of 2 columns and 6 rows. Shelf groups, with a grid channel left between the shelf groups; then, the entire warehouse is evenly divided into 6 areas, each area has 3*7=21 shelf groups, and each area is deployed with multiple wireless access terminals. It should be noted that each area in the figure contains fewer shelf groups. In actual deployment, the number of shelf groups contained in each area can be adjusted according to the computing power of the scheduling server and the number of mobile robots; finally, a scheduling server is deployed in the center of each warehouse area. Each scheduling server communicates with the central control server through a wired connection. At the same time, each scheduling server communicates wirelessly with all mobile robots in the area through multiple wireless access terminals in the area. In the above scheme, the entire warehouse adopts a channel layout and is evenly divided into multiple areas in the form of grid division. Multiple shelf groups are set up in each area. Two rows of shelves form a shelf group. The shelf groups are connected by channels. The sorting stations in multiple areas are deployed together. See Figure 1 As shown, this approach suffers from the following drawbacks: All sorting stations across multiple areas are located in a single area, making the sorting area prone to congestion. A malfunction at a station could impact overall operational efficiency. Furthermore, shelves deep within the warehouse are located far from the sorting stations, forcing mobile robots to travel long distances, impacting operational efficiency. Furthermore, optimizing the utilization of warehouse space and mobile robots when designing shelf layouts within a warehouse is an important research topic. Summary of the Invention

[0005] The present invention aims to overcome the shortcomings of existing technologies by providing a method for optimizing the layout of an intelligent warehouse and an intelligent warehousing system. The method provides a balanced approach to warehouse space utilization and the efficiency of goods entering and leaving the warehouse. Furthermore, the method allows for flexible deployment of operational units as needed, is highly scalable, and can significantly improve the operational efficiency of intelligent warehouses.

[0006] To achieve the above objectives, the present invention provides the following technical solutions: A layout optimization method for an intelligent warehouse comprises the following steps: Obtaining warehouse plan size information for the warehouse to be laid out and shelf plan size information for the shelves to be placed; and obtaining preset warehouse layout rules; the warehouse layout rules include operating unit size configuration rules and shelf size configuration rules, the operating units are used to perform human-machine collaborative goods picking tasks, and each operating unit includes a shelf storage area and a sorting area. The shelf storage area is used for placing movable shelves and moving intelligent robots that transport shelves, and the sorting area includes picking docking locations and a manual work area. According to the warehouse plane size and the plane size of the work unit configured in the work unit size configuration rule, the number K of work units that can be arranged in the warehouse to be arranged is determined; and according to the shelf plane size and the shelf margin configured in the shelf size configuration rule, the plane size of the shelf is determined, with one shelf being placed in one shelf. The total number H of cargo locations that can be arranged in an operation unit is determined based on the plane size of the operation unit and the plane size of the cargo location.

[0007] Furthermore, when the number K of the operating units is greater than or equal to 2, multiple operating units are arranged side by side, in rows, or in multiple rows and columns in the warehouse according to the plane size of the warehouse to be laid out; When the warehouse to be laid out is divided into areas, one or more of the work units are laid out in each area; wherein, when multiple work units can be laid out in an area, the multiple work units are arranged side by side, in rows, or in multiple rows and columns in the area according to the plane size of the area.

[0008] Furthermore, the shelf storage area includes two longitudinal main aisles and a shelf group located between the two longitudinal main aisles; the sorting area is located on one side of the shelf storage area and is connected to the two longitudinal main aisles at both ends; the picking docking position of the sorting area is connected to the shelf storage area and forms a separation zone between the shelf storage area and the manual work area; the operation unit size configuration rule includes main aisle size configuration information, shelf group configuration information, picking docking position configuration information, and manual work area configuration information; At this time, the steps of determining the total number of cargo locations H that can be arranged in an operation unit include: According to the determined cargo space plane dimensions (a, b), a grid map is constructed in the operation unit according to the cargo space plane dimensions or a preset ratio of the cargo space plane dimensions, wherein a represents the cargo space width and b represents the cargo space length; Determine, according to the grid map, the number of shelf groups that can be placed in the work unit and the number of shelves that can be arranged in each row of each shelf group based on the main aisle size configuration information, the shelf group configuration information, and the manual workspace configuration information; The total number H of cargo locations that can be arranged in each operation unit is calculated based on the number of shelf groups and the number of cargo locations.

[0009] Furthermore, the main channel size configuration information includes a main channel width value, and the main channel width value is related to the plane size of the cargo space; The rack group configuration information includes a rack group division method and a rack group length value under the division method; wherein the rack group division method is as follows: each rack group includes two rows of racks and a row of transverse aisles located between the two rows of racks, the transverse aisles are perpendicular to and intersect with the longitudinal main aisles, each row of racks occupies one row of grids, and a row of transverse aisles occupies one row of grids, i.e., each rack group length value is three rows of grids; The picking stop configuration information includes the length of the cargo space occupied by the sorting position and the number of picking stations; The manual work area configuration information includes the length of the cargo space occupied by the manual work area.

[0010] Furthermore, the width of the main channel is configured as s, the cargo space length occupied by the sorting position is configured as 1 cargo space length, and the cargo space length B occupied by the manual work area is configured as i cargo space lengths, where i is a positive integer greater than or equal to 1; Assume that the plane dimensions of the work unit configuration are (W, L), where W represents the width of the work unit and L represents the length of the work unit. The steps for calculating the total number of storage locations H are as follows: According to the length of the working unit L, the length of the manual working area B=i*b and the length value of the shelf group L u =3*b, calculate the allowable value n of the shelf group of the work unit, the calculation formula is n=(LB) / L u ; and, according to the width W of the work unit, the width s of the main channel and the width a of the cargo space, calculate the allowable value m of the cargo space of each row of the work unit grid, and the calculation formula is m=(W-2*s) / a; Round off the aforementioned shelf group allowance n and shelf location allowance m to obtain the number of shelf groups n0 that can be placed in the work unit and the number of shelves m0 that can be arranged in each row of grids in the work unit. The shelf location in the outermost shelf group is used as the picking docking location. Calculate the total number of cargo spaces H based on n0 and m0, using the formula H = (n0*2-1)*m0; Where n0 = [n], m0 = [m], and [·] is the rounding symbol.

[0011] Furthermore, the picking stop position occupies an entire row of grids of the work unit to form the separation zone, including the shelf group grids and the main channel grids located in the same row, and one grid corresponds to one sorting position; The sorting position is provided with a shelf door curtain. When loading or picking is required, the intelligent robot moves the shelf to the sorting position and stops it for manual loading or picking operations. When loading or picking goods, the information of goods on each layer of the current shelf is displayed through the shelf door curtain.

[0012] Furthermore, the picking stop includes multiple picking stations, one picking station occupies one or more grids, and each picking station is equipped with at least one picking person and one intelligent robot; It also includes a picking station scheduling step, as follows: collecting sales order information to be shipped out, and configuring the number of picking stations that need to be opened currently, as well as the number of intelligent robots and the number of manpower corresponding to each picking station according to the number of sales orders; wherein, according to the number of sales orders, a variety of human-machine collaboration modes are configured, including at least a few-single human-machine collaboration mode, a many-single human-machine collaboration mode and a peak human-machine collaboration mode, and different human-machine collaboration modes correspond to different numbers of picking stations opened, numbers of intelligent robots and / or numbers of manpower.

[0013] Furthermore, the number of shelves and the number of storage locations on each shelf are adjustable, with one storage location being used to place one stock keeping unit (SKU); It also includes the steps of product SKU planning, as follows: collecting the product type of the goods to be put into the warehouse, obtaining the product characteristics corresponding to the product type and the inventory unit SKU information of the goods, configuring the number of shelves and the number of storage locations on each shelf according to the product characteristics and the corresponding SKU information of the goods, and determining the number of SKUs of the goods that can be placed on each shelf according to the number of shelves and the number of storage locations on each shelf.

[0014] Furthermore, a storage map of the warehouse to be laid out is constructed, wherein the storage map includes a grid map, cargo location, aisle location, shelf location, and shelf storage location; Also, monitor the location information of the cargo locations and aisles of each work unit in the warehouse. For any work unit, when its cargo location and / or aisle changes, determine that the layout of the work unit has changed, and perform the following steps: obtain the ID of the work unit whose layout has changed, and the changed cargo location and / or aisle location information, and update the cargo location and / or aisle location information of the corresponding work unit in the warehouse map.

[0015] Furthermore, the shelf storage area of the operating unit is divided into a hot zone, a cold zone and an ultra-cold zone; At this time, it also includes a product zoning planning step as follows: based on historical order data and information data of robot transport shelves, based on a preset statistical time period T, the number of times q that the shelf where the product SKU is placed in the operation unit is transported within the statistical time period T is counted; when the number of transports of the shelf where the product SKU is located exceeds a preset first transport number threshold J1, it is determined that the product SKU is a high-heat product, and the shelf where the high-heat product is located is placed in the hot zone; when the number of transports of the shelf where the product SKU is located is less than or equal to the first transport number threshold J1 but greater than the preset second transport number threshold J2, it is determined that the product SKU is an ordinary heat product, and the shelf where the ordinary heat product is located is placed in the cold zone; when the number of transports of the shelf where the product SKU is located is less than or equal to the second transport number threshold J2, it is determined that the product SKU is a low-heat product, and the shelf where the low-heat product is located is placed in the super-cold zone; And the hot zone channel optimization steps are as follows: evaluate the traffic status of each shelf group channel in the hot zone, and for the shelf group channel that is congested, count the duration of the shelf group channel in the congested state under the preset time length. When the duration exceeds the preset time length threshold, it is determined that the shelf group channel needs to be widened and a channel layout adjustment instruction is issued.

[0016] The present invention also provides an intelligent warehousing system, comprising an intelligent warehouse for human-machine collaboration; one or more operating units are provided in the warehouse, each operating unit being used to perform human-machine collaborative goods picking tasks, each operating unit comprising a shelf storage area and a sorting area, the shelf storage area being used for placing movable shelves and moving intelligent robots for transporting shelves, the sorting area comprising picking docking positions and a manual work area; The system also includes a cargo space layout module, which is configured to: obtain warehouse plane dimension information and shelf plane dimension information of the shelves to be placed; and obtain preset warehouse layout rules, wherein the warehouse layout rules include operation unit size configuration rules and cargo space size configuration rules; according to the warehouse plane dimension, based on the operation unit plane dimension configured in the operation unit size configuration rule, determine the number K of operation units that can be laid out in the warehouse; and, according to the shelf plane dimension, based on the cargo space margin configured in the cargo space size configuration rule, determine the plane dimension of the cargo space, one cargo space is used for one shelf; according to the operation unit plane dimension and cargo space plane dimension, determine the total number H of cargo spaces that can be laid out in one operation unit.

[0017] Due to the adoption of the above technical solution, the present invention has the following advantages and positive effects compared with the existing technology, as an example: the layout optimization method of the intelligent warehouse provided by the present invention takes into account the space utilization efficiency of the warehouse and the operational efficiency of goods entering and leaving the warehouse, and the operating units can be flexibly deployed as needed, with strong scalability, and can significantly improve the operational efficiency of the intelligent warehouse. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the layout of a smart warehouse provided by existing technology.

[0019] Figure 2 This is a flow chart of the layout optimization method for the intelligent warehouse provided by the present invention.

[0020] Figure 3 This is a schematic diagram of the layout of the operating unit provided by the present invention.

[0021] Figure 4 This is a schematic diagram of the layout of the shelf group provided by the present invention.

[0022] Figure 5 Schematic diagram of the layout of multiple work units deployed in a warehouse provided by the present invention Figure 1 .

[0023] Figure 6 Schematic diagram of the layout of multiple work units deployed in a warehouse provided by the present invention Figure 2 .

[0024] Figure 7 This is a schematic diagram of the module structure of the intelligent warehousing system provided by the present invention.

[0025] Description of reference numerals: Shelf group 100, shelf row 110, aisle row 120, shelf 111; Intelligent robot 200. DETAILED DESCRIPTION

[0026] The following is a further detailed description of the layout optimization method of the intelligent warehouse and the intelligent warehousing system disclosed in the present invention in conjunction with the accompanying drawings and specific embodiments. It should be noted that the technologies (including methods and devices) known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the above-mentioned known technologies are considered to be part of the specification. At the same time, other examples of the exemplary embodiments may have different values. The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the limiting conditions for the implementation of the invention. In the description of the embodiments of the present application, " / " means or, and "and / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" means: A and B exist alone, B exists alone, and A and B exist at the same time. In the description of the embodiments of the present application, "multiple" refers to two or more. Example

[0027] See also Figure 2 As shown, a layout optimization method of an intelligent warehouse provided by the present invention is provided in the intelligent warehouse. Movable shelves and intelligent robots are provided in the intelligent warehouse, and the intelligent robots are used to carry the movable shelves.

[0028] The method includes the steps of cargo location layout, as follows: S100, obtaining warehouse plane size information of a warehouse to be laid out and shelf plane size information of shelves to be placed; and obtaining preset warehouse layout rules.

[0029] The warehouse layout rules are preset and can adopt the system's default warehouse layout rules or can be customized warehouse layout rules set by the user as needed. In this embodiment, the warehouse layout rules include operation unit size configuration rules and storage location size configuration rules. The operation unit is used to perform human-machine collaborative goods picking tasks and is the basic segmentation unit for performing human-machine collaborative tasks. Each operation unit includes a shelf storage area and a sorting area. The shelf storage area is used for placing movable shelves and moving intelligent robots that transport shelves. The sorting area includes a picking stop and a manual work area. The manual work area is located at the outermost side of the operation unit. When loading or picking goods is required, the intelligent robot transports the movable shelves in the warehouse according to the task instructions and transports them to the designated sorting position of the picking stop in the sorting area. The sorting personnel in the manual work area perform goods picking and warehousing and outbound operations; then, the transport robot automatically carries the movable shelf to the original storage location of the shelf and puts the shelf down; then, the transport robot waits for the next task instruction.

[0030] S200, determining the number K of work units that can be arranged in the warehouse to be arranged according to the warehouse plane size and the work unit plane size configured in the work unit size configuration rule, wherein K is a positive integer greater than or equal to 1.

[0031] S300: Determine the plane size of the shelf according to the plane size of the shelf and the shelf margin configured in the shelf size configuration rule, where one shelf is used for placement.

[0032] That is, the planar dimensions of the shelf locations used to place the shelves are determined based on the shelf dimensions, with shelves and shelves being arranged in a one-to-one correspondence. Specifically, the planar dimensions of the shelf locations are equal to the planar dimensions of the shelf plus the aforementioned configured shelf margin. The shelf margin can include a width margin and a length margin, which can be the same or different. Preferably, the shelf margin is related to the shelf dimensions and is set according to a preset ratio based on the shelf dimensions. The corresponding ratios of the width margin and length margin can be the same or different. As an example and not a limitation, for example, the plane dimensions (a0, b0) of the shelf are: shelf width a0 = 80 cm, shelf length b0 = 60 cm, and the cargo space margin ratio includes the width margin ratio and the length margin ratio. For example, if the width margin ratio is configured as 1 / 4, the corresponding width margin is 80 cm * (1 / 4) = 20 cm, and if the length margin ratio is configured as 1 / 2, the corresponding length margin is 60 cm * (1 / 2) = 30 cm. Then the plane dimensions (a, b) of the cargo space are: cargo space width a = 100 cm, and cargo space length b = 90 cm.

[0033] S400: Determine the total number H of cargo locations that can be arranged in an operation unit according to the plane size of the operation unit and the plane size of the cargo location, where H is a positive integer.

[0034] See also Figure 3 The figure shows a typical layout of a work unit. The work unit is divided into a shelf storage area and a sorting area. The shelf storage area may include two longitudinal main channels and a shelf group located between the two longitudinal main channels. The sorting area is located on one side of the shelf storage area and is connected to the two longitudinal main channels at both ends. In addition, the picking stop in the sorting area is connected to the shelf storage area and forms a separation zone between the shelf storage area and the manual work area. The shelf storage area is located on the inner side of the picking stop, and the manual work area is located on the outer side of the picking stop. By separating the machine work area and the manual work area, the system safety is improved and the interference between them is reduced.

[0035] Correspondingly, the operation unit size configuration rules may include main channel size configuration information, shelf group configuration information, picking stop configuration information and manual work area configuration information.

[0036] At this point, the steps to determine the total number of cargo locations H that can be arranged in a work unit are as follows: S410 , constructing a grid map in the operation unit according to the determined cargo location plane size (a, b) or a preset ratio of the cargo location plane size, where a represents the cargo location width and b represents the cargo location length.

[0037] In this embodiment, when constructing a plane grid map of an operation unit, the grid can be divided directly using the plane size of the cargo location (a, b) as the grid size. The grid formed at this time is a standard grid, which is also the grid division method used in most cases. Alternatively, the plane size of the cargo location (a, b) can be multiplied by a preset ratio - for example, 95%, and then divided into (95%a, 95%b) as the grid size. The grid formed at this time is an adjusted grid, which is an adjustment solution when the standard grid division method cannot meet the warehouse space utilization requirements.

[0038] The preset ratio can be a reduction ratio (i.e., a ratio value less than 1) or an expansion ratio (i.e., a ratio value greater than 1). Specifically, the preset ratio can be configured based on the planar dimensions of the warehouse to be laid out. For example, if the warehouse cannot accommodate an integer number of work units divided according to a standard grid, the width and height of the work unit grid can be appropriately reduced to allow the warehouse to deploy an integer number of work units. Of course, the reduced grid size should be larger than the shelf size to ensure that the shelf can be smoothly placed in the grid (shelf location).

[0039] S420: Determine the number of shelf groups that can be placed in the work unit and the number of cargo locations that can be arranged in each row of each shelf group based on the grid map, the main channel size configuration information, the shelf group configuration information, and the manual workspace configuration information.

[0040] Specifically, the main channel size configuration information includes a main channel width value. The main channel width value is related to the plane size of the cargo space, and the main channel width value should be greater than the cargo space width.

[0041] The shelf group configuration information includes the shelf group division method and the shelf group length value under the division method. Figure 4 As shown, the shelf group is divided as follows: each shelf group 100 includes two shelf rows 110 and an aisle row 120 located between the two rows of shelves. Each shelf row is provided with corresponding shelves 111 according to the number of cargo locations. The aisle row 120 forms a row of transverse aisles between the two shelf rows 110. The transverse aisles are perpendicular to and intersect with the longitudinal main aisles. Figure 3Each row of shelves occupies one row of grids, and each row of transverse aisles occupies one row of grids, meaning each shelf group is three rows long. This row of aisles, combined with the upper and lower rows of shelves, optimizes aisle utilization and effectively improves warehouse space utilization.

[0042] The picking stop location configuration information includes the cargo location length occupied by the sorting location and the number of picking stations.

[0043] The manual work area configuration information includes the length of the cargo space occupied by the manual work area.

[0044] S430: Calculate the total number H of cargo locations that can be arranged in each operation unit according to the number of shelf groups and the number of cargo locations.

[0045] In specific implementation, for example, the initial value of the main channel width can be configured as s, the cargo space length occupied by the sorting position can be configured as 1 cargo space length, and the cargo space length B occupied by the manual work area can be configured as i cargo space lengths, where i is a positive integer greater than or equal to 1.

[0046] Let the plane size of the work unit configuration be (W, L), where W represents the width of the work unit, and L represents the length of the work unit. The steps for calculating the total number of cargo locations H are as follows: First, based on the length of the work unit L, the length of the manual work area B=i*b and the length value of the shelf group Lu=3*b, calculate the shelf group allowable value n of the work unit. The shelf group allowable value refers to the maximum number of shelf groups that can be placed in the length direction of the work unit, and the calculation formula is n=(LB) / Lu. Then, based on the width of the work unit W, the width of the main channel s and the cargo location width a, calculate the cargo location allowable value m of each row of the work unit grid. The cargo location allowable value refers to the maximum number of cargo locations that can be placed in the width direction of the work unit, and the calculation formula is m=(W-2*s) / a. Subsequently, the aforementioned shelf group allowable value n and cargo location allowable value m are rounded to obtain the number of shelf groups n0 that can be placed in the work unit and the number of cargo locations m0 that can be arranged in each row of the work unit. A row of cargo locations in the outermost shelf group serves as a picking stop, see Figure 3 The total number of cargo spaces H is calculated based on n0 and m0 using the formula H = (n0*2-1)*m0, where n0 = [n], m0 = [m], and [·] is a rounding symbol indicating rounding of the data in brackets. * represents a multiplication sign.

[0047] It should be noted that when the width value s of the main channel of the operation unit is inconsistent with the cargo location width a, two sizes of grids are formed in the grid map of the operation unit, including a cargo location grid (or cargo location grid) and a main channel grid. The cargo location grid size is the aforementioned cargo location size a*b, and the grid width of the main channel grid is configured as s*b, where the s value is greater than the a value.

[0048] The following configuration is based on the operating unit size (W, L) of 12m*20m, combined with Figure 3 Describe the storage location layout optimization process in detail.

[0049] Assume that based on the shelf size and the shelf margin, the calculated shelf size (a, b) is (1m, 1m), that is, the shelf grid size is 1m*1m. Figure 3 The rack group has two longitudinally arranged main aisles, each of which has a grid size of (s, b), where the width s = 1.25m and the length is equal to the length of the shelf b, which is 1m. u =3*b=3m. The length of the artificial working area B=i*b=2b=2m.

[0050] First, based on the length of the work unit L, calculate how many shelf groups can be arranged in the longitudinal direction (i.e. the length direction of the work unit). The calculation formula is n = (LB) / L u =(20-2) / 3=6, that is, a maximum of 6 shelf groups can be arranged in the length direction.

[0051] Then, based on the width W of the work unit, calculate how many cargo spaces (grids) can be placed in each row of the work unit. The cargo space (grid) width is a=1m, and the calculation formula is m=(W-2*s) / a=(12-2*1.25) / 1=9.5, that is, the work unit can have a maximum of 9.5 cargo spaces (shelves) in the width direction.

[0052] Then, the above-mentioned shelf group allowable value n and the shelf position allowable value m are rounded to integers, and n0=[n]=6, m0=[m]=9 are obtained. Based on n0 and m0, the total number of shelf positions H is calculated as (n0*2-1)*m0 = (6*2-1)*9=99. Among them, n0*2 minus 1 is because the row of shelves in the outermost shelf group ( Figure 3 The bottom row of shelves in the picking process should be used as the picking stop.

[0053] It should be noted that since nine cargo locations are arranged in a row across the width of the work unit, the remaining width is 12-9*a=3m, which does not match the sum of the widths of the two main aisles, 2.5m. Therefore, the width of the main aisle needs to be corrected based on the calculated number of cargo locations in the cargo row, m0, i.e., the main aisle width is adjusted from its initial value of 1.25m to 3m / 2=1.5m. Accordingly, this embodiment also includes a main aisle width correction module, which is configured to correct the main aisle width based on the difference between m and m0 when the calculated cargo location allowance, m, is not an integer. The corrected main aisle width is the value obtained by adding (m-m0)*a / 2 to the initial value, s, of the main aisle width. In addition, a manual work area length correction module is set up, which is configured to: when the calculated shelf group allowable value n is not an integer, the manual work area length is corrected according to the difference between n and n0, and the correction value of the manual work area length is the initial configuration value B of the manual work area length plus the value obtained by (n-n0)*b.

[0054] In this embodiment, one or more operation units are deployed in the warehouse according to the size of the warehouse plane, and multiple operation units can be expanded horizontally or vertically.

[0055] Specifically, when the number K of the operation units is greater than or equal to 2, multiple operation units are arranged side by side, in rows, or in multiple rows and columns in the warehouse according to the plane size of the warehouse to be laid out. Figure 5 As shown, the case where two rows and two columns of job units are set is exemplified.

[0056] In another embodiment, the warehouse can be divided into multiple areas, and the operation units can be deployed in one or more areas as needed. Figure 6 As shown, an example is given in which a warehouse is divided into three areas, including area A, area B, and area C, and one work unit is deployed in each of said areas A, B, and C.

[0057] Specifically, when the warehouse to be laid out is divided into areas, one or more of the work units are laid out in each area. When multiple work units can be laid out in an area, the multiple work units are arranged side by side, in rows, or in multiple rows and columns in the area according to the planar dimensions of the area.

[0058] The picking stop occupies a whole row of grids to form the separation zone, combined with Figure 3 As shown, the grid of the picking stop position includes the shelf group grid and the main channel grid located in the same row, and one grid corresponds to one sorting position.

[0059] The sorting position can be provided with a shelf curtain. When loading or picking goods is required, the intelligent robot moves the shelf to the sorting position and docks it for manual loading or picking operations. When loading or picking goods, the shelf curtain displays the product information of each layer on the currently docked shelf.

[0060] Furthermore, the picking stop can be divided into multiple picking stations. A picking station can include multiple grids. Each picking station needs to be equipped with at least one picking person and one intelligent robot. Figure 3 Take the picking stop occupying 11 grids as an example - including 2 main channel grids and 9 cargo grids, which can be divided into 3 picking stations (as a workstation). Each picking station includes 3-4 grids, and each grid forms a sorting position. Shelf curtains can be installed on each sorting position, that is, 3-4 curtains form a group to form a picking station.

[0061] Preferably, a picking station may include: 2-3 sorting positions with high shelf door curtains installed and 1 sorting position with temporary shelf door curtains installed, and be equipped with a picking person.

[0062] In this embodiment, the number of layers of the shelf and the storage locations of each layer are adjustable, and one storage location is used to place one stock keeping unit SKU (or stock keeping unit).

[0063] In smart warehouses, shelves are used to store SKUs (Stock Keeping Units). Shelves can be divided into multiple layers, each containing one or more storage units—for example, cells to distinguish between different types of merchandise. Each storage unit stores the same SKU. In this embodiment, each shelf layer can have one or more storage locations, each for a single SKU.

[0064] At this point, a product SKU planning step is also configured, as follows: collect the product type of the goods to be stored, obtain the product characteristics corresponding to the product type and the stock keeping unit SKU information of the goods, plan the number of shelves and the number of storage locations per shelf based on the product characteristics and corresponding SKU information, and determine the number of SKUs of the goods that can be placed on each shelf based on the number of shelves and the number of storage locations per shelf. Specifically, the product characteristics include product type information and characteristic information of the goods of that type. The SKU information includes the length, width, height and weight parameters of the SKU.

[0065] As an example and not a limitation, for example, the product types may include beauty products, clothing products, and grocery products, and correspondingly, beauty product SKU information, auxiliary SKU information, and grocery product SKU information are configured respectively. For beauty product types, there are many small items, and the product height is relatively low, so the corresponding SKU height is relatively low. The corresponding shelves are configured with 5 layers, with 4 storage locations on each layer, that is, 4 SKUs are placed, so the number of goods stored on each shelf is 20. For another example, for clothing product types, the corresponding shelves are configured with 4 layers, with 6 storage locations on each layer, that is, 6 SKUs are placed, and the number of goods stored on each shelf is 24.

[0066] For example, for grocery products, each shelf is configured with cells of multiple sizes (for example, large cells and small cells), and one cell is one SKU. If the number of cells on each shelf is 10, the number of SKUs stored is 10.

[0067] In another implementation of this embodiment, picking stations can also be scheduled based on the characteristics of the outgoing sales orders. In this case, the picking station scheduling step includes the following: collecting sales order information to be shipped, and planning the number of picking stations that need to be opened, as well as the number of intelligent robots and labor staff corresponding to each picking station based on the number of sales orders; wherein, according to the number of sales orders, multiple human-machine collaboration modes are configured, including at least a low-order human-machine collaboration mode, a high-order human-machine collaboration mode, and a high-peak human-machine collaboration mode, and different human-machine collaboration modes correspond to different numbers of open picking stations, intelligent robots, and / or labor staff.

[0068] As an example and not a limitation, for example, a first threshold value for sales orders and a second threshold value for sales orders can be preset. When the number of sales orders to be shipped out on the same day is less than the first threshold value for sales orders (for example, 500 orders), it is determined to be a small order type, corresponding to the small order human-machine collaboration mode. At this time, the number of picking stations opened, the number of intelligent robots, and the number of manpower configured for the small order human-machine collaboration mode are obtained. For example, one picking station is opened, and five snail robots (i.e., intelligent robots) and one picking person are designed.

[0069] When the number of sales orders to be shipped out on the same day is greater than the first threshold of sales orders (for example, 500 orders) but less than the second threshold of sales orders (for example, 3000 orders), it is determined to be a multiple-order type, corresponding to the multi-order human-machine collaboration mode. At this time, the number of picking stations opened, the number of intelligent robots, and the number of manpower configured in the multi-order human-machine collaboration mode are obtained. For example, 2 picking stations are opened, and each picking station is designed with 10 snail robots (i.e., intelligent robots) and 3 manpower, including 1 picker and 2 packers.

[0070] When the number of sales orders to be shipped out on that day exceeds the second threshold (e.g., 3,000 orders), it is determined to be a peak-type operation, corresponding to the peak human-robot collaboration mode. At this time, the number of open picking stations, the number of intelligent robots, and the number of workers configured for the peak human-robot collaboration mode are obtained. For example, three picking stations are open, each with 10 Snail robots (intelligent robots used to transport shelves) and 3 workers. A special flatbed robot is also deployed to work with the Bobo Bear robot to ship large quantities of goods in original cartons. The Bobo Bear robot can pick up goods from the shelves transported by the Snail robot and place them in the original cartons. The operation mode of multiple robot types depends on the robot cluster scheduling algorithm, which can be based on various existing robot cluster scheduling algorithms and will not be detailed here.

[0071] In this embodiment, a storage map of the aforementioned warehouse to be laid out can also be constructed. The storage map includes a grid map, cargo location, aisle location, shelf location and shelf storage location, and location information of the storage locations on the shelves. A location identifier is set for each storage location, and the location identifier is set in a one-to-one correspondence with the storage location location.

[0072] Also, monitor the location information of the cargo locations and aisles of each work unit in the warehouse. For any work unit, when its cargo location and / or aisle changes, determine that the layout of the work unit has changed, and perform the following steps: obtain the ID of the work unit whose layout has changed, and the changed cargo location and / or aisle location information, and update the cargo location and / or aisle location information of the corresponding work unit in the warehouse map.

[0073] In this way, when the warehouse layout changes (for example, the storage location is newly set as an aisle, and the aisle is adjusted to the storage location), there is no need to paste the dividing line (such as the green line) on the ground again, and you can just update the warehouse map.

[0074] In another embodiment of the present invention, the shelf storage area of the operation unit can be further divided into a hot zone, a cold zone, and an ultra-cold zone. Specifically, the hot zone, the cold zone, and the ultra-cold zone are divided according to the distance between the shelf and the manual work area.

[0075] Among them, the hot zone is the shortest to the manual work area, and the intelligent robot has to travel a short distance to transport the shelves. The cold zone is slightly farther from the manual work area, and the intelligent robot has to travel a long distance to transport the shelves. The shelves in this area need to be pulled a certain distance to the manual work area. The ultra-cold zone is the farthest from the manual work area among the three zones, and the intelligent robot has to travel the longest distance to transport the shelves. By way of example and not limitation, in a specific setting, the area of the hot zone can account for 1 / 5 to 1 / 3 of the area of the entire shelf storage area, the area of the cold zone can account for 1 / 3 to 3 / 5 of the area of the entire shelf storage area, and the area of the ultra-cold zone can account for 1 / 5 to 1 / 3 of the area of the entire shelf storage area.

[0076] At this time, the product zoning planning step is also included as follows: based on historical order data and information data on robot-handled shelves, based on a preset statistical time period T, the number of times q that the shelf containing the product SKU placed in the operation unit is handled within the statistical time period T is counted. When the number of times the shelf containing the product SKU is handled exceeds a preset first handling number threshold J1, the product SKU is determined to be a high-heat product, and the shelf containing the high-heat product is placed in the hot zone. When the number of times the shelf containing the product SKU is handled is less than or equal to the first handling number threshold J1 but greater than a preset second handling number threshold J2, the product SKU is determined to be a normal-heat product, and the shelf containing the normal-heat product is placed in the cold zone. When the number of times the shelf containing the product SKU is handled is less than or equal to the second handling number threshold J2, the product SKU is determined to be a low-heat product, and the shelf containing the low-heat product is placed in the super-cold zone. In this way, the efficiency of goods entering and leaving the warehouse can be further improved.

[0077] The second handling times threshold J2 is an integer greater than or equal to 1, and the first handling times threshold J1 is greater than the second handling times threshold J2. In specific settings, the first handling times threshold J1 and the second handling times threshold can be set by system default or customized by the user as needed.

[0078] Furthermore, the shelves where the SKUs of goods to be shipped are located can be adjusted to the aforementioned hot zones based on the predicted SKU information of goods to be shipped, such as the SKU information of goods that have been ordered but not shipped, or the SKU information of goods that have been signed and are expected to be shipped in the near future.

[0079] More preferably, for the hot zone, in order to further improve operational efficiency, the passage status of the aisle can be evaluated, and the aisle layout can be adjusted based on the evaluation results. The passage status can include a congested state and an unobstructed state. Specifically, the hot zone aisle optimization step is as follows: the passage status of each rack group aisle in the hot zone is evaluated. For a rack group aisle that is congested, the duration of the rack group aisle being congested within a preset time length is counted. When the duration exceeds a preset time length threshold, it is determined that the rack group aisle needs to be widened, for example, to be widened to a dual aisle, and an aisle layout adjustment instruction is issued.

[0080] Based on the aisle layout adjustment instructions, the system controls the transport robot to perform shelf handling to adjust the aisle and shelf layout. Specifically, the aisle layout adjustment instructions may include information such as the shelf group ID of the aisle to be adjusted, aisle adjustment parameters, and the work unit ID of the shelf group. The aisle adjustment parameters may include the current aisle width (e.g., single grid width) and current grid occupancy information, as well as the adjusted aisle width (e.g., double grid width) and grid occupancy information. The grid occupancy information is expressed in grid coordinates.

[0081] In this way, by widening the channel - for example, expanding a single channel into a double channel, the mutual interference between the racks on different sides of channel 2 when the racks are transported can be reduced, and the efficiency of the racks passing through this section can be increased.

[0082] Preferably, the transportation status of the shelf group aisle is evaluated by analyzing the transportation process data of the hot zone shelves. The specific steps can be as follows: obtain the transportation process data of the hot zone shelves, calculate the number of passive stops kk and the total passive stop time tt of each shelf on the path from the cargo position to the sorting area stop position, and the passive stop refers to the non-human controlled stop behavior; when the ratio u (u=kk:tt) of the total stop time tt and the number of passive stops kk of a shelf on the transportation path is greater than the preset time threshold q, it is determined that the transportation path of the shelf is congested, otherwise it is determined that the transportation path of the shelf is unobstructed; for the shelf with congestion in the transportation path, obtain the congestion section location information, and when the congestion section location is located in the shelf group aisle, it is determined that the shelf group aisle is congested.

[0083] It should be noted that after adjusting the channel layout, the aforementioned warehouse map can be updated according to the layout adjustment information without pasting ground marks.

[0084] Another embodiment of the present invention further provides an intelligent warehousing system.

[0085] The system includes a human-machine collaborative intelligent warehouse, in which one or more work units are set up, and the work units are used to perform human-machine collaborative goods picking tasks. Each work unit includes a shelf storage area and a sorting area. The shelf storage area is used for placing movable shelves and moving intelligent robots that transport shelves. The sorting area includes picking docking positions and manual work areas.

[0086] See also Figure 7As shown, the system also includes a cargo space layout module, which is configured to: obtain warehouse plane dimension information and shelf plane dimension information of the shelves to be placed; and obtain preset warehouse layout rules, the warehouse layout rules including work unit size configuration rules and cargo space size configuration rules; according to the warehouse plane dimension, based on the work unit plane dimension configured in the work unit size configuration rule, determine the number K of work units that can be laid out in the warehouse, wherein K is a positive integer greater than or equal to 1; and, according to the shelf plane dimension, based on the cargo space margin configured in the cargo space size configuration rule, determine the plane dimension of the cargo space, one cargo space is used for one shelf; according to the work unit plane dimension and the cargo space plane dimension, determine the total number H of cargo spaces that can be laid out in one work unit, wherein H is a positive integer.

[0087] In this embodiment, the number of shelves and the number of storage locations on each shelf are adjustable, with one storage location used to store one SKU. A product SKU planning module is also provided, which is configured to: collect the product type of the goods to be stored, obtain the product characteristics corresponding to the product type and the SKU information of the goods; plan the number of shelves and the number of storage locations on each shelf based on the product characteristics and corresponding SKU information; and determine the number of SKUs of the goods that can be placed on each shelf based on the number of shelves and the number of storage locations on each shelf.

[0088] Preferably, the system may further include a picking station scheduling module, which is configured to: obtain sales order information to be shipped out, and plan the number of picking stations that need to be opened, as well as the number of intelligent robots and manpower corresponding to each picking station according to the number of sales orders; wherein, a variety of human-machine collaboration modes are configured according to the number of sales orders, including at least a few-single human-machine collaboration mode, a many-single human-machine collaboration mode and a peak human-machine collaboration mode, and different human-machine collaboration modes are configured with different numbers of picking stations opened, intelligent robots and manpower.

[0089] The system may further include a warehouse monitoring module and a warehouse map module.

[0090] The warehouse monitoring module is used to monitor the location information of the cargo locations and channels of each work unit in the warehouse. For any work unit, when its cargo location and / or channel changes, it is determined that the layout of the work unit has changed, and the ID of the work unit with the changed layout and the changed cargo location and / or channel location information are obtained and sent to the warehouse map module.

[0091] The warehouse map module is used to initialize (build) and update the warehouse map of the warehouse to be laid out. The warehouse map includes a grid map, shelf locations, aisle locations, shelf locations, and shelf storage location information. Each shelf location is assigned a location identifier, and the location identifier is set in a one-to-one correspondence with the storage location.

[0092] After receiving the information sent by the warehouse monitoring module, the warehouse map module can update the cargo location and / or channel location information of the corresponding operation unit in the warehouse map according to the operation unit ID and the changed cargo location and / or channel location information, thereby forming an updated warehouse map.

[0093] In this embodiment, the shelf storage area of the operation unit can be divided into a hot zone, a cold zone, and an ultra-cold zone. In this case, a product zoning planning module is also included, which is configured to: based on historical order data and information data of robot-transported shelves, based on a preset statistical time period T, count the number of times q that the shelf where the product SKU placed in the operation unit is transported within the statistical time period T; when the number of times the shelf where the product SKU is located exceeds a preset first transport number threshold J1, the product SKU is determined to be a high-heat product, and the shelf where the high-heat product is located is placed in the hot zone; when the number of times the shelf where the product SKU is located is less than or equal to the first transport number threshold J1 but greater than a preset second transport number threshold J2, the product SKU is determined to be a normal-heat product, and the shelf where the normal-heat product is located is placed in the cold zone; when the number of times the shelf where the product SKU is located is less than or equal to the second transport number threshold J2, the product SKU is determined to be a low-heat product, and the shelf where the low-heat product is located is placed in the ultra-cold zone.

[0094] Furthermore, it can also include a hot zone channel optimization module, which is configured to: evaluate the traffic status of each shelf group channel in the hot zone, and for the shelf group channel that is congested, count the duration of the shelf group channel in the congested state within a preset time length; when the duration exceeds the preset time length threshold, it is determined that the shelf group channel needs to be widened, and a channel layout adjustment instruction is issued.

[0095] For other technical features, please refer to the description of the previous embodiment and will not be repeated here.

[0096] It should be noted that the various method embodiments of the present invention can be implemented in software, hardware, firmware, etc. Regardless of whether the present invention is implemented in software, hardware, or firmware, the instruction code can be stored in any type of computer-accessible memory (e.g., permanent or modifiable, volatile or non-volatile, solid or non-solid, fixed or removable media, etc.). Similarly, the memory can be, for example, a programmable array logic (PAL), a random access memory (RAM), a programmable read-only memory (PROM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic disk, an optical disk, a digital versatile disk, etc.

[0097] In the above description, the disclosure of the present invention is not intended to limit itself to these aspects. Rather, within the scope of the intended protection of the present disclosure, the components can be selectively and operationally combined in any number. In addition, terms such as "including", "encompassing" and "having" should be interpreted as inclusive or open by default, rather than exclusive or closed, unless they are explicitly defined to the contrary. All technical, scientific or other terms have the meaning understood by those skilled in the art unless they are defined to the contrary. Common terms found in dictionaries should not be interpreted too idealistically or too impractically in the context of relevant technical documents, unless the present disclosure explicitly defines them as such. Any changes and modifications made by a person of ordinary skill in the field of the present invention based on the above disclosure are within the scope of protection of the claims.

Claims

1. A layout optimization method for an intelligent warehouse, characterized in that Including steps: Obtaining warehouse plan size information for the warehouse to be laid out and shelf plan size information for the shelves to be placed; and obtaining preset warehouse layout rules; the warehouse layout rules include operating unit size configuration rules and shelf size configuration rules, the operating units are used to perform human-machine collaborative goods picking tasks, and each operating unit includes a shelf storage area and a sorting area. The shelf storage area is used for placing movable shelves and moving intelligent robots that transport shelves, and the sorting area includes picking docking locations and a manual work area. According to the warehouse plane size and the plane size of the work unit configured in the work unit size configuration rule, the number K of work units that can be arranged in the warehouse to be arranged is determined; and according to the shelf plane size and the shelf margin configured in the shelf size configuration rule, the plane size of the shelf is determined, with one shelf being placed in one shelf. The total number H of cargo locations that can be arranged in an operation unit is determined based on the plane size of the operation unit and the plane size of the cargo location.

2. The method according to claim 1, wherein: When the number K of the operating units is greater than or equal to 2, multiple operating units are arranged side by side, in rows, or in multiple rows and columns in the warehouse according to the plane size of the warehouse to be laid out; When the warehouse to be laid out is divided into areas, one or more of the work units are laid out in each area; wherein, when multiple work units can be laid out in an area, the multiple work units are arranged side by side, in rows, or in multiple rows and columns in the area according to the plane size of the area.

3. The method according to claim 1, wherein: The shelf storage area includes two longitudinal main aisles and a shelf group located between the two longitudinal main aisles. The sorting area is located on one side of the shelf storage area and is connected to the two longitudinal main aisles at both ends. The picking docking station of the sorting area is connected to the shelf storage area and forms a separation zone between the shelf storage area and the manual work area. The operation unit size configuration rule includes main aisle size configuration information, shelf group configuration information, picking docking station configuration information, and manual work area configuration information. At this time, the steps of determining the total number of cargo locations H that can be arranged in an operation unit include: According to the determined cargo space plane dimensions (a, b), a grid map is constructed in the operation unit according to the cargo space plane dimensions or a preset ratio of the cargo space plane dimensions, wherein a represents the cargo space width and b represents the cargo space length; Determine, according to the grid map, the number of shelf groups that can be placed in the work unit and the number of shelves that can be arranged in each row of each shelf group based on the main aisle size configuration information, the shelf group configuration information, and the manual workspace configuration information; The total number H of cargo locations that can be arranged in each operation unit is calculated based on the number of shelf groups and the number of cargo locations.

4. The method according to claim 3, wherein: The main channel size configuration information includes a main channel width value, and the main channel width value is related to the plane size of the cargo space; The rack group configuration information includes a rack group division method and a rack group length value under the division method; wherein the rack group division method is as follows: each rack group includes two rows of racks and a row of transverse aisles located between the two rows of racks, the transverse aisles are perpendicular to and intersect with the longitudinal main aisles, each row of racks occupies one row of grids, and a row of transverse aisles occupies one row of grids, i.e., each rack group length value is three rows of grids; The picking stop configuration information includes the length of the cargo space occupied by the sorting position and the number of picking stations; The manual work area configuration information includes the length of the cargo space occupied by the manual work area.

5. The method according to claim 4, characterized in that: The width of the main channel is configured as s, the cargo space length occupied by the sorting position is configured as 1 cargo space length, and the cargo space length B occupied by the manual work area is configured as i cargo space lengths, where i is a positive integer greater than or equal to 1; Assume that the plane dimensions of the work unit configuration are (W, L), where W represents the width of the work unit and L represents the length of the work unit. The steps for calculating the total number of storage locations H are as follows: According to the length of the working unit L, the length of the manual working area B=i*b and the length value of the shelf group L u =3*b, calculate the allowable value n of the shelf group of the work unit, the calculation formula is n=(LB) / L u ; And, according to the width W of the operation unit, the width s of the main channel and the width a of the cargo space, the allowable value m of the cargo space of each row of the operation unit grid is calculated, and the calculation formula is m=(W-2*s) / a; Round off the aforementioned shelf group allowance n and shelf location allowance m to obtain the number of shelf groups n0 that can be placed in the work unit and the number of shelves m0 that can be arranged in each row of grids in the work unit. The shelf location in the outermost shelf group is used as the picking docking location. Calculate the total number of cargo spaces H based on n0 and m0, using the formula H = (n0*2-1)*m0; Where n0 = [n], m0 = [m], and [·] is the rounding symbol.

6. The method according to claim 3, wherein: The picking docking position occupies an entire row of grids of the work unit to form the separation zone, including the shelf group grids and the main channel grids located in the same row, and one grid corresponds to one sorting position; The sorting position is provided with a shelf door curtain. When loading or picking is required, the intelligent robot moves the shelf to the sorting position and stops it for manual loading or picking operations. When loading or picking goods, the information of goods on each layer of the current shelf is displayed through the shelf door curtain.

7. The method according to claim 3, wherein: The picking stop includes multiple picking stations, one picking station occupies one or more grids, and each picking station is equipped with at least one picking person and one intelligent robot; It also includes a picking station scheduling step, as follows: collecting sales order information to be shipped out, and configuring the number of picking stations that need to be opened currently, as well as the number of intelligent robots and the number of manpower corresponding to each picking station according to the number of sales orders; wherein, according to the number of sales orders, a variety of human-machine collaboration modes are configured, including at least a few-single human-machine collaboration mode, a many-single human-machine collaboration mode and a peak human-machine collaboration mode, and different human-machine collaboration modes correspond to different numbers of picking stations opened, numbers of intelligent robots and / or numbers of manpower.

8. The method according to claim 1, wherein: The number of shelves and the storage locations on each shelf are adjustable, with one storage location being used to place one stock keeping unit (SKU); It also includes the steps of product SKU planning, as follows: collecting the product type of the goods to be put into the warehouse, obtaining the product characteristics corresponding to the product type and the inventory unit SKU information of the goods, configuring the number of shelves and the number of storage locations on each shelf according to the product characteristics and the corresponding SKU information of the goods, and determining the number of SKUs of the goods that can be placed on each shelf according to the number of shelves and the number of storage locations on each shelf.

9. The method according to claim 1, wherein: Constructing a storage map of the aforementioned warehouse to be laid out, wherein the storage map includes a grid map, cargo location, aisle location, shelf location, and shelf storage location; Also, monitor the location information of the cargo locations and aisles of each work unit in the warehouse. For any work unit, when its cargo location and / or aisle changes, determine that the layout of the work unit has changed, and perform the following steps: obtain the ID of the work unit whose layout has changed, and the changed cargo location and / or aisle location information, and update the cargo location and / or aisle location information of the corresponding work unit in the warehouse map.

10. The method according to claim 1, wherein: The shelf storage area of the operation unit is divided into a hot zone, a cold zone and an ultra-cold zone. At this time, it also includes a product zoning planning step as follows: based on historical order data and information data of robot transport shelves, based on a preset statistical time period T, the number of times q that the shelf where the product SKU placed in the operation unit is transported within the statistical time period T is counted; when the number of transports of the shelf where the product SKU is located exceeds a preset first transport number threshold J1, it is determined that the product SKU is a high-heat product, and the shelf where the high-heat product is located is placed in the hot zone; when the number of transports of the shelf where the product SKU is located is less than or equal to the first transport number threshold J1 but greater than a preset second transport number threshold J2, it is determined that the product SKU is an ordinary heat product, and the shelf where the ordinary heat product is located is placed in the cold zone; when the number of transports of the shelf where the product SKU is located is less than or equal to the second transport number threshold J2, it is determined that the product SKU is a low-heat product, and the shelf where the low-heat product is located is placed in the ultra-cold zone; And the hot zone channel optimization steps are as follows: evaluate the traffic status of each shelf group channel in the hot zone, and for the shelf group channel that is congested, count the duration of the shelf group channel in the congested state under the preset time length. When the duration exceeds the preset time length threshold, it is determined that the shelf group channel needs to be widened and a channel layout adjustment instruction is issued.

11. An intelligent warehousing system, including a human-machine collaborative intelligent warehouse, characterized by: One or more work units are provided in the warehouse, and the work units are used to perform goods picking tasks in a human-machine collaborative manner. Each work unit includes a shelf storage area and a sorting area. The shelf storage area is used for placing movable shelves and moving intelligent robots that transport shelves. The sorting area includes a picking docking station and a manual work area. The system also includes a cargo space layout module, which is configured to: obtain warehouse plane dimension information and shelf plane dimension information of the shelves to be placed; and obtain preset warehouse layout rules, wherein the warehouse layout rules include operation unit size configuration rules and cargo space size configuration rules; according to the warehouse plane dimension, based on the operation unit plane dimension configured in the operation unit size configuration rule, determine the number K of operation units that can be laid out in the warehouse; and, according to the shelf plane dimension, based on the cargo space margin configured in the cargo space size configuration rule, determine the plane dimension of the cargo space, one cargo space is used for one shelf; according to the operation unit plane dimension and cargo space plane dimension, determine the total number H of cargo spaces that can be laid out in one operation unit.

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