Task allocation method and device, equipment, warehousing system and storage medium

Abstract

This disclosure provides a task allocation method, apparatus, device, warehousing system, and storage medium. The task allocation method is applied to a warehousing system whose warehouse includes multiple logical partitions, each logical partition including one or more physical areas. The method includes: determining each item to be scheduled corresponding to at least one task; determining each target robot to perform at least one task based on the logical partition corresponding to each item to be scheduled and the area attributes of each robot, wherein the area attributes are used to describe the logical partition corresponding to the robot; and determining the task to be performed by each target robot based on the storage space corresponding to each item to be scheduled, so as to complete at least one task. This realizes the determination of the robot to perform the task corresponding to the item based on the area corresponding to the item and the area attributes of the robot, thereby improving the flexibility of task allocation and the efficiency of task processing.

Description

[0001] This application is a divisional application of patent application No. 202111076808.4, filed on September 14, 2021, entitled "Task Allocation Method, Apparatus, Equipment, Warehousing System and Storage Medium". Technical Field

[0002] This disclosure relates to the field of intelligent warehousing technology, and in particular to a task allocation method, apparatus, equipment, warehousing system and storage medium. Background Technology

[0003] Robot-based warehousing systems employ intelligent operating systems that enable the automatic retrieval and storage of goods through system commands. They can operate 24 / 7, replacing manual management and operation, thus improving warehousing efficiency and gaining widespread application and popularity.

[0004] As warehouse areas continue to expand, the distances robots need to travel to execute warehouse orders also gradually increase, leading to a decrease in order processing efficiency. To improve order processing efficiency, warehouses are typically divided into multiple separate physical areas, and a group of robots is assigned to each physical area to execute the orders corresponding to that physical area.

[0005] In existing technologies, when assigning tasks to robots, the limitations of physical space mean that robots can only handle tasks within the corresponding physical area. This results in low flexibility in task assignment, low task processing efficiency, and an inability to meet the requirements. Summary of the Invention

[0006] This disclosure provides a task allocation method, apparatus, equipment, warehousing system, and storage medium. It adopts a logical partitioning approach, which improves the flexibility of partitioning. Task allocation is performed based on the logical partitions corresponding to the robots, thereby improving the flexibility of task allocation and the efficiency of order processing.

[0007] In a first aspect, embodiments of this disclosure provide a task allocation method, the method being applied to a warehousing system, wherein the warehouse of the warehousing system includes multiple logical partitions, each logical partition including one or more physical areas, the method comprising:

[0008] Identify at least one task and each item to be scheduled; determine each target robot to execute the at least one task based on the logical partition corresponding to each item to be scheduled and the area attributes of each robot, wherein the area attributes are used to describe the logical partition corresponding to the robot; determine the task to be executed by each target robot based on the storage space corresponding to each item to be scheduled, so as to complete the at least one task, wherein the storage space is the space in the logical partition used to store the items.

[0009] Optionally, based on the logical partitions corresponding to each of the goods to be scheduled and the regional attributes of each robot, each target robot to perform the at least one task is determined, including:

[0010] The logical partitions corresponding to each of the goods to be scheduled are determined as target areas; from the robots whose area attributes include the target areas, each target robot is determined to perform the at least one task.

[0011] Optionally, determining the target robot to perform the at least one task from among the robots whose region attributes include the target region includes:

[0012] The operation status of each robot in the target area is obtained, including the area attributes. Based on the task volume and task priority of the at least one task, each target robot to perform the at least one task is determined from the robots whose area attributes include the target area and whose operation status is order-accepting.

[0013] Optionally, the region attribute includes a first attribute, which describes the logical partition to which the robot belongs during its lifecycle, and the first attribute is an immutable attribute; determining each target robot to perform the at least one task from among the robots whose region attribute includes the target region includes:

[0014] Obtain the operating status of each first robot whose first attribute is the target area; determine each target robot to execute the at least one task based on the operating status of each first robot and the task volume of the at least one task.

[0015] Optionally, the region attribute further includes a second attribute, which describes one or more logical partitions to which the robot belongs, and the second attribute is a modifiable attribute; determining each target robot to perform the at least one task based on the operating status of each of the first robots and the workload of the at least one task includes:

[0016] Based on the task volume of the at least one task, determine whether the total number of orders received by each first robot in the order-accepting state is less than the task volume of the at least one task; if so, obtain the task priority of the at least one task; when the task priority is higher than a preset priority, determine each first robot in the order-accepting state as a first target robot, and obtain the running status of each second robot whose second attribute includes the target area; based on the task volume of the at least one task and the first total number of orders received, determine at least one second robot in the order-accepting state as a second target robot, so that each first target robot and the second target robot can complete the at least one task.

[0017] Optionally, the region attribute further includes a third attribute, which describes the logical partitions that the robot can traverse during a single trip. When the second total number of orders received by each of the first and second target robots is less than the task volume of the at least one task, the method further includes:

[0018] The third attribute is obtained, including the operating status of each third robot in the target area; based on the second total order volume and the task volume, at least one third target robot is determined from each third robot whose operating status is in the order-accepting state, so that each of the first target robot, the second target robot and the third target robot can complete the at least one task.

[0019] Optionally, the logical partition includes a first partition attribute, which describes a preset number of robots allowed to operate in the logical partition at the same time; the method further includes:

[0020] Obtain the number of robots currently operating in each logical partition corresponding to the goods to be scheduled; for each logical partition corresponding to the goods to be scheduled, when the sum of the total number of target robots and the number of operations in the logical partition exceeds a preset number corresponding to the first partition attribute of the logical partition, determine a first type of robot and a second type of robot from the target robots, wherein the sum of the number of the first type of robot and the number of operations is equal to the preset number, and the second type of robot is the target robot remaining after removing the first type of robot; control the first type of robot to execute the corresponding pending task; when it is detected that a first number of robots in the logical partition have left the logical partition, control the first number of the second type of robot to move to the logical partition and execute the corresponding pending task.

[0021] Optionally, the method further includes:

[0022] Based on the location of the storage space for each of the goods to be scheduled corresponding to the at least one task, the physical areas of the warehouse are divided to determine the logical partitions of the warehousing system; based on the logical partitions, the area attributes of each robot are set.

[0023] Optionally, based on the storage space corresponding to each of the goods to be scheduled, the tasks to be performed by each of the target robots are determined, including:

[0024] Based on the alleyway to which the storage space corresponding to each of the goods to be scheduled belongs, the task to be executed by each of the target robots is determined, so that the span of the alleyway corresponding to the goods to be scheduled in the task to be executed by each target robot is less than a preset value.

[0025] Optionally, before determining the individual goods to be dispatched corresponding to at least one task, the method further includes:

[0026] Receive an order; determine at least one task based on the order; determine one or more target workstations based on the task requirements of the at least one task, the logical partitions corresponding to each workstation, and the goods storage status of each logical partition, wherein the logical partitions corresponding to the one or more target workstations contain goods that meet the task requirements of the at least one task.

[0027] Accordingly, at least one task is identified, including the following:

[0028] Based on the task requirements of the at least one task, each cargo to be scheduled for the at least one task is determined in the logical partition corresponding to the target control console.

[0029] Secondly, embodiments of this disclosure also provide a task allocation device, which is applied to a warehousing system. The warehouse of the warehousing system includes multiple logical partitions, each logical partition including one or more physical areas. The device includes:

[0030] The cargo determination module is used to determine each cargo to be scheduled corresponding to at least one task; the robot determination module is used to determine each target robot according to the logical partition corresponding to each cargo to be scheduled and the regional attributes of each robot, wherein the regional attributes are used to describe the logical partition corresponding to the robot; the task determination module is used to determine the task to be executed by each target robot according to the storage space corresponding to each cargo to be scheduled, so as to complete the at least one task, wherein the storage space is the space in the logical partition used to store cargo.

[0031] Thirdly, embodiments of this disclosure also provide a task allocation device, including: a memory and at least one processor; the memory stores computer execution instructions; the at least one processor executes the computer execution instructions stored in the memory, causing the at least one processor to perform the task allocation method provided in any embodiment corresponding to the first aspect of this disclosure.

[0032] Fourthly, embodiments of this disclosure also provide a warehousing system, including: a robot, a warehouse including multiple logical partitions, and a task allocation device provided in the embodiments corresponding to the third aspect of this disclosure.

[0033] Fifthly, embodiments of this disclosure also provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the task allocation method provided in any embodiment corresponding to the first aspect of this disclosure.

[0034] In a sixth aspect, embodiments of this disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements the task allocation method provided in any embodiment corresponding to the first aspect of this disclosure.

[0035] The task allocation method, apparatus, device, warehousing system, and storage medium provided in this disclosure are for warehousing systems comprising multiple logical partitions. Each logical partition may include one or more physical partitions. By dividing the warehouse of the warehousing system into multiple variable areas through logical partitioning, when at least one task needs to be processed, the various goods to be scheduled corresponding to the at least one task are first determined. Then, based on the logical partitions corresponding to each goods to be scheduled and the area attributes of each robot, a robot is allocated to the at least one task, and the corresponding robot executes the allocated task to complete the at least one task. By pre-setting area attributes for the robots and allocating robots to tasks based on the area attributes and the logical partitions corresponding to the goods for the task, the flexibility of task allocation is improved. Simultaneously, by matching area attributes with logical partitions, the travel distance of the robots can be effectively reduced, such as avoiding robots performing tasks across logical areas, thereby improving the efficiency of task processing. Attached Figure Description

[0036] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0037] Figure 1 This is an application scenario diagram of the task allocation method provided in the embodiments of this disclosure;

[0038] Figure 2A flowchart illustrating a task allocation method provided in one embodiment of this disclosure;

[0039] Figure 3 A schematic diagram illustrating the logical partitioning of a warehouse according to an embodiment of this disclosure;

[0040] Figure 4 A schematic diagram illustrating the logical partitioning of a warehouse as provided in another embodiment of this disclosure;

[0041] Figure 5 A flowchart of a task allocation method provided in another embodiment of this disclosure;

[0042] Figure 6 A flowchart of a task allocation method provided in another embodiment of this disclosure;

[0043] Figure 7 For this disclosure Figure 6 A schematic diagram of logical partitioning in the illustrated embodiment;

[0044] Figure 8 A flowchart of a task allocation method provided in another embodiment of this disclosure;

[0045] Figure 9 A flowchart of a task allocation method provided in another embodiment of this disclosure;

[0046] Figure 10 For this disclosure Figure 9 The flowchart of step S904 in the illustrated embodiment is shown.

[0047] Figure 11 A flowchart of a task allocation method provided in another embodiment of this disclosure;

[0048] Figure 12 This is a schematic diagram of the structure of a task allocation device provided in one embodiment of the present disclosure;

[0049] Figure 13 This is a schematic diagram of the structure of a task allocation device provided in one embodiment of the present disclosure;

[0050] Figure 14 This is a schematic diagram of the structure of a warehousing system provided in one embodiment of the present disclosure.

[0051] The accompanying drawings have illustrated specific embodiments of this disclosure, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this disclosure to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0052] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0053] The technical solutions of this disclosure and how they solve the aforementioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this disclosure will now be described with reference to the accompanying drawings.

[0054] The application scenarios of the embodiments of this disclosure are explained below:

[0055] Figure 1 This is an application scenario diagram of the task allocation method provided in the embodiments of this disclosure, such as... Figure 1 As shown in the embodiments of this disclosure, the task allocation method can be executed by a task allocation device, which can be a scheduling device for a warehousing system, and its form can be a computer or a server. As the storage volume gradually increases, the area occupied by the warehouse in the warehousing system 100 also increases. To facilitate management, the warehouse is divided into multiple physical areas 110 for zoned management. One or more robots 120 are allocated to each physical area 110 to handle the goods within that physical area 110. Figure 1 Taking three physical areas 110 and one robot 120 corresponding to each physical area 110 as an example, when the scheduling device 130 of the warehousing system 100 receives an order, such as an outbound order or a sorting order, if the task volume of the order is large, the order can be divided into multiple tasks, and robots can be assigned to each task corresponding to the order. When assigning tasks, the task allocation needs to be based on the physical area 110 corresponding to the robot 120, so that the goods in the task corresponding to each physical area 110 are handled by the robot 120 corresponding to that physical area 110 to complete the order.

[0056] Due to the limitations of the physical area 110, the above task allocation method has low flexibility. As a result, when most of the goods corresponding to a task are stored in a certain physical area 110, and the robots 120 in that physical area 110 are occupied by other tasks, or the number of robots 120 available for the task is small, it will take a long time to complete the task, resulting in low task processing efficiency.

[0057] To improve the flexibility of task allocation and the efficiency of task processing, this disclosure provides a task allocation method. The main concept of this method is to partition the warehouse of the warehousing system through logical partitioning, thereby achieving on-demand partitioning and improving the flexibility of partitioning. Furthermore, it involves pre-setting region attributes for each robot to describe one or more logical partitions corresponding to that robot. After determining the various goods to be scheduled for a task, based on the logical partitions corresponding to each goods and the region attributes of each robot, one or more robots matching the region attributes are allocated to the task. This approach improves the flexibility of task allocation and the efficiency of task processing by combining logical partitioning and region attributes.

[0058] Figure 2 A flowchart of a task allocation method provided in one embodiment of this disclosure is shown below. Figure 2 As shown, this task allocation method is applicable to a warehousing system. The warehouse of this system includes multiple logical partitions, each of which may consist of one or more physical areas. This task allocation method can be executed by a task allocation device. The task allocation method provided in this embodiment includes the following steps:

[0059] Step S201: Determine each shipment to be dispatched corresponding to at least one task.

[0060] At least one task can be part or all of an order received by the warehousing system. This order can be an outbound order or a sorting order. An outbound order requires moving the corresponding goods from various storage locations in the warehouse to the outside, such as the goods exit. A sorting order requires sorting out some or all of the items stored in the corresponding goods until the quantity of items corresponding to the order is met, and then packing the sorted items for outbound shipment. The goods to be dispatched are the goods corresponding to the at least one task.

[0061] Specifically, one or more tasks can be identified first, and then each cargo to be dispatched can be determined based on the task requirements of those tasks.

[0062] Furthermore, the goods to be dispatched can be determined based on the items and quantities stored in each cargo in the warehousing system, as well as the task requirements of the at least one task.

[0063] For example, suppose that the warehouse of the warehousing system has storage locations 1-5 with goods 1-5 respectively, and goods 1-5 contain 2, 4, 5, 6 and 3 items A respectively. If the task requirement of at least one task is 10 items A, then the goods to be dispatched can be determined to be goods 2 stored in storage location 2 and goods 4 stored in storage location 4, or the goods to be dispatched can be determined to be goods 1 stored in storage location 1, goods 3 stored in storage location 3 and goods 5 stored in storage location 5.

[0064] Specifically, when each item is stored in the warehouse, the warehousing system's scheduling equipment can update the stored storage record based on the items stored in the item, the quantity of the items, and the storage location of the item. In this way, based on the storage record and the task requirements of at least one task, the system can determine each item to be scheduled that meets the task requirements.

[0065] Furthermore, based on the target item corresponding to the task requirements of at least one task, each alternative goods containing the target item can be selected. Then, based on the required quantity of the target item in the task requirements of at least one task, the quantity of the target item in each alternative goods, and the location of each alternative goods, each item to be dispatched can be determined. This minimizes the total quantity of the items to be dispatched and makes the locations of each item to be dispatched as close as possible, thereby reducing the number of times the robot picks up goods and the walking distance, and improving task processing efficiency.

[0066] For example, suppose the warehousing system includes two shelves, shelf H1 and shelf H2, each shelf has 5 layers, and each layer can be set with 10 storage locations. The task requirement for at least one task is 100 pieces of clothing C. The warehousing system has 5 boxes containing clothing C, namely boxes B1-B5. The number of pieces of clothing C stored in boxes B1-B5 are 16, 50, 40, 45 and 15 respectively. Boxes B1-B5 are located at storage locations 22, 35 and 44 on shelf H1, and storage locations 11 and 56 on shelf H2. Here, the first number in the storage location number indicates the layer where the storage location is located, and the second number indicates the column where the storage location is located. Storage location 22 means that the storage location is in the second column of the second layer. Then the goods to be dispatched are determined to be boxes B1-box B3, so that the boxes are concentrated on shelf H1, avoiding the need for the robot to move to shelf H1 and shelf H2 separately when picking up the goods, and reducing the robot's walking distance.

[0067] Step S202: Based on the logical partitions corresponding to each of the goods to be scheduled and the regional attributes of each robot, determine each target robot to perform the at least one task.

[0068] The region attribute is used to describe one or more logical partitions corresponding to the robot.

[0069] The warehouse of the warehousing system disclosed herein uses logical partitioning to divide the area. In some embodiments, the logical partitioning can be a variable partitioning, such as the physical area corresponding to each logical partition can be changed based on the current warehousing status or order demand.

[0070] For example, Figure 3 This is a schematic diagram illustrating the logical partitioning of a warehouse according to an embodiment of this disclosure. Figure 4This is a schematic diagram illustrating the logical partitioning of a warehouse according to another embodiment of this disclosure. Figure 3 and Figure 4 All correspond to the same warehouse, combined Figure 3 and Figure 4 It can be seen that the warehouse comprises a total of 8 physical areas, namely W1-W8. Figure 3 In the diagram, the warehouse is divided into three logical partitions, which are represented by dashed boxes. Figure 4 In this case, warehouse 300 is divided into two logical partitions, which are represented by dashed boxes.

[0071] In some embodiments, when the total workload of at least one task is small, the number of target robots may be one.

[0072] For a warehousing system that uses logical partitioning for partitioning, when matching robots for tasks, i.e., when determining each target robot to perform at least one task, the target robot to perform at least one task can be determined based on the logical partition where each item to be scheduled is located and the area attributes of each robot.

[0073] Specifically, a robot whose regional attributes include at least one logical partition corresponding to a cargo to be scheduled can be identified as the target robot, and the target robot can then perform the corresponding tasks for each cargo to be scheduled in the logical partition where the cargo to be scheduled is located, based on its regional attributes.

[0074] Optionally, based on the logical partitions corresponding to each of the goods to be scheduled and the regional attributes of each robot, each target robot to perform the at least one task is determined, including:

[0075] The logical partitions corresponding to each of the goods to be scheduled are determined as target areas; from the robots whose area attributes include the target areas, each target robot is determined to perform the at least one task.

[0076] Among them, the regional attribute includes the target region, which can be understood as the regional attribute including at least one logical partition in the target region.

[0077] Specifically, the logical partitions corresponding to each cargo to be dispatched can be counted to obtain one or more target areas.

[0078] Furthermore, robots whose regional attributes include at least one target partition can be identified as candidate robots, and then one or more target robots for performing at least one task can be selected from among the candidate robots.

[0079] Specifically, one or more target robots can be determined from the candidate robots based on the logical partitions corresponding to the regional attributes of each candidate robot, the number of idle shelves in the temporary storage racks of each candidate robot, and the total number of goods to be dispatched.

[0080] Specifically, the robot's regional attributes can be pre-set based on the logical partitioning of the warehouse system.

[0081] For example, consider a warehouse system with two logical partitions, L1 and L2. Orders received by the warehouse system are divided into multiple tasks. The tasks currently requiring processing correspond to 5 items in logical partition L1 and 8 items in logical partition L2. The warehouse system includes a total of 5 robots, R1-R5. Robots with the area attribute of logical partition L1 are R1-R3, and robots with the area attribute of logical partition L2 are R3-R5. That is, robot R3 can handle the tasks corresponding to logical partitions L1 and L2. Each robot R1-R5 has 5-layer temporary storage shelves. The number of empty shelves for robots R1-R5, i.e., the number of layers that can store goods, is 3, 2, 4, 4, and 3 respectively. In this case, when assigning robots to the current task, the target robots can be robots R1-R4. Robots R1 and R2 are used to handle the 5 items in logical partition L1, while robots R3 and R4 are used to handle the 8 items in logical partition L2.

[0082] Step S203: Based on the storage space corresponding to each of the goods to be scheduled, determine the task to be performed by each of the target robots to complete the at least one task.

[0083] Storage space refers to the space on the shelves of the warehouse where goods awaiting dispatch are stored; it can also be called a storage location.

[0084] Specifically, after identifying the goods to be dispatched for at least one task, the storage space or warehouse location corresponding to each goods can be determined based on its identifier. Once the storage space for each goods is obtained, tasks are planned for each target robot based on the location of each storage space. This aims to concentrate the storage spaces for the goods corresponding to each target robot's tasks as much as possible, or to make the storage spaces as close as possible to each other, thereby reducing the distance the target robot travels when performing its tasks and improving task processing efficiency.

[0085] Furthermore, the tasks to be performed by each target robot can be determined based on the current location of each target robot, the number of empty shelves in the temporary storage area, and the storage space for each item to be dispatched.

[0086] In some embodiments, goods to be scheduled may be stored in multiple logical partitions. When determining the tasks to be performed by each target robot, the tasks to be performed by each target robot can also be determined by combining the logical partitions included in the area attributes of the target robot, so that the target robot can process one or more goods to be scheduled stored in the logical partitions included in its area attributes.

[0087] For example, taking a warehousing system with 5 logical partitions, namely logical partitions L21-L25, the logical partitions involved in each shipment to be dispatched are L22, L23 and L25. Among them, logical partition L22 includes 9 shipments to be dispatched, logical partition L23 includes 8 shipments to be dispatched, and logical partition L25 includes 3 shipments to be dispatched. The target robots are robots R21-R28. Table 1 is a table showing the correspondence between the regional attributes of the target robots and the logical partitions. The logical partitions included in the regional attributes of each target robot are shown in Table 1. Given that the number of idle shelves for robots R21-R28 are 2, 3, 2, 3, 3, 2, 4, and 5 respectively, the 9 items to be scheduled in logical partition L22 can be processed by R21-R24, the 8 items to be scheduled in logical partition L23 can be processed by R25-R27, and the 3 items to be scheduled in logical partition L25 can be processed by R28. The specific allocation method of the tasks to be executed by each target robot can be based on the number of idle shelves in its temporary storage.

[0088] Table 1. Correspondence between the regional attributes and logical partitions of the target robot

[0089] Target robot Logical partitions included in the region attributes R21 L22 R22 L22 R23 L22 R24 L22, L23 R25 L23 R26 L23 R27 L23, L25 R28 L25

[0090] The task allocation method provided in this disclosure is for a warehousing system comprising multiple logical partitions, each of which may include one or more physical partitions. By dividing the warehouse of the warehousing system into multiple variable areas through logical partitioning, when at least one task needs to be processed, the method first determines the various goods to be scheduled corresponding to the at least one task. Then, based on the logical partitions corresponding to the goods to be scheduled and the area attributes of each robot, a robot is allocated to the at least one task, and the corresponding robot executes the allocated task to complete the at least one task. By pre-setting area attributes for the robots and allocating robots to tasks based on the area attributes and the logical partitions corresponding to the goods for the task, the flexibility of task allocation is improved. Simultaneously, by matching area attributes with logical partitions, the robot's travel distance can be effectively reduced, such as avoiding robots performing tasks across logical areas, thereby improving task processing efficiency.

[0091] Optional, Figure 5This is a flowchart illustrating a task allocation method provided in another embodiment of the present disclosure. Figure 2 Based on the illustrated embodiment, before step S201, that is, before determining each shipment to be scheduled corresponding to at least one task, the following steps are added:

[0092] Step S501: Receive order.

[0093] The order can be initiated by the customer or obtained through an order receiving device, or it can be obtained by scanning the customer's order QR code with a handheld electronic device. The order can be an outbound order or a sorting order. An outbound order means that specified goods are shipped out of the warehouse, while a sorting order means that a specified quantity of specified items are shipped out of the warehouse.

[0094] Step S502: Determine at least one task based on the order.

[0095] The sum of the task requirements for at least one task is consistent with the order requirements for the order.

[0096] Specifically, after receiving an order, the task allocation or scheduling equipment can extract information from the order to obtain the order requirements, and then determine one or more tasks based on the order requirements.

[0097] Furthermore, when the order is a sorting order, at least one task can be determined based on the items corresponding to the order. For example, the order can be divided according to the type of each item, storage attributes, and the required quantity of each item to obtain various tasks.

[0098] For example, suppose an order is for the shipment of 100 pieces of clothing C5, 50 pieces of clothing C6, and 200 pairs of shoes X5. The storage attribute of clothing C5 and clothing C6 is the first attribute. Items with the same storage attribute can be stored together in one box. Then the order can be divided into two tasks. One task is to ship 100 pieces of clothing C5 and 50 pieces of clothing C6, and the other task is to ship 200 pairs of shoes X5.

[0099] Step S503: Based on the task requirements of the at least one task, the logical partitions corresponding to each operating station, and the storage status of goods in each logical partition, determine one or more target operating stations.

[0100] The logical partitions corresponding to the one or more target workstations contain goods that meet the task requirements of the at least one task. The storage status of goods in the logical partitions may include the goods stored in each storage location of the logical partition, and may also include the items stored in each storage location and their quantities.

[0101] In some embodiments, an operator console may correspond to one or more logical partitions, and a logical partition may also correspond to one or more operator consoles.

[0102] Specifically, after identifying at least one task, it is necessary to determine the target workstations for processing that task. If a workstation exists whose corresponding one or more logical partitions contain goods that satisfy all the task requirements of at least one task, then that workstation is prioritized as the target workstation. That is, priority is given to selecting workstations with the fewest number of workstations and whose corresponding logical partitions contain goods that meet the task requirements of at least one task as target workstations. This reduces the number of target workstations and avoids occupying too many workstations, which could affect the processing of other tasks.

[0103] The corresponding step S201 specifically involves: determining each of the at least one task's scheduled goods in the logical partition corresponding to the target operating console, based on the task requirements of the at least one task.

[0104] Specifically, after determining the target control station, each cargo to be scheduled can be determined in the logical partition corresponding to the one or more target control stations based on the task requirements of the at least one task.

[0105] Furthermore, when the order is a sorting order, that is, when the task is a sorting task, each item to be dispatched can be determined based on the storage location of each item in the task requirement in the logical partition corresponding to the target operation station, as well as the quantity of the item stored in each item, so that the storage locations of each item to be dispatched are as close as possible and the total quantity of the items to be dispatched is as small as possible.

[0106] For example, taking a warehouse in a warehousing system that includes 3 logical partitions and 2 workstations as an example, at least one task requires the outbound shipment of 120 pieces of clothing C31 and 100 pieces of clothing C32, corresponding to logical partitions L31 to L33. Logical partitions L31 and L32 correspond to workstation O31, and logical partition L33 corresponds to workstation O32. Logical partition L31 stores 3 items, containing 100 pieces of clothing C31, 50 pieces of clothing C32, and 36 pieces of clothing C31 respectively. Logical partition L32 stores 2 items, containing... There are 67 pieces of clothing C31 and 86 pieces of clothing C32. Logical partition L33 stores one item containing 100 pieces of clothing C31 and 15 pieces of clothing C32. Since the logical partitions corresponding to console O31, namely logical partitions L31 and L32, contain the quantity of clothing C31 and C32 that meets the task requirements of the above task, console O31 can be determined as the target console. The items to be scheduled can be the three items stored in logical partition L31 and the item containing 86 pieces of clothing C32 stored in logical partition L32.

[0107] Figure 6 This is a flowchart of a task allocation method provided in another embodiment of the present disclosure. The task allocation method provided in this embodiment is... Figure 2 Based on the illustrated embodiment, steps S202 and S203 are further refined, and steps of dividing logical partitions and setting robot region attributes are added after step S201, such as... Figure 6 As shown, the task allocation method provided in this embodiment may include the following steps:

[0108] Step S601: Determine each shipment to be dispatched corresponding to at least one task.

[0109] Specifically, when at least one task requires goods or bins, that is, when executing the processing of each goods or bin, the corresponding goods or bins in the task requirements can be directly identified as each goods to be scheduled.

[0110] Specifically, when at least one task requires items, the available goods to be dispatched can be determined based on the warehouse storage situation of the warehousing system. Items are typically placed in cargo or containers, which are then placed in corresponding storage spaces or locations within the warehouse.

[0111] Step S602: Based on the location of the storage space of each of the goods to be scheduled corresponding to the at least one task, divide the physical areas of the warehouse to determine the logical partitions of the warehousing system.

[0112] Specifically, after identifying each item to be dispatched, the warehouse location or storage space for each item can be determined based on its identification. Then, based on the location of each item's storage space or location—that is, the distribution of each item—the physical areas of the warehouse can be divided, resulting in logical zones. The identification can take the form of a QR code, barcode, or code, used to uniquely identify the item.

[0113] Furthermore, based on the location of the storage space for each cargo to be scheduled, the principle for dividing each physical area should be to divide cargoes that are close to each other into the same or as few logical partitions as possible.

[0114] For example, Figure 7 For this disclosure Figure 6 The schematic diagram of logical partitioning in the illustrated embodiment is as follows: Figure 7 As shown, the warehouse of the warehousing system consists of 5 physical areas, namely RW1-RW5. Goods to be dispatched are represented by solid squares, and their distribution details are as follows. Figure 7As shown, the physical areas of the warehouse can be divided into three logical areas: RL1, RL2, and RL3. The specific division result is as follows: Figure 7 As shown.

[0115] Step S603: Set the region attributes of each robot according to the respective logical partitions.

[0116] Specifically, the total number of robots that can be used for cargo handling in the warehousing system is fixed. After obtaining each logical partition, the area attributes of each robot can be set based on factors such as the floor area, location, and number of corresponding storage spaces or warehouse locations of each logical partition.

[0117] In some embodiments, region attributes may include immutable attributes and modifiable attributes, and may include value setting type attributes and switch setting type attributes.

[0118] Specifically, the region attribute can include an immutable first attribute describing the logical region corresponding to the robot during its lifecycle; it can also include a modifiable second attribute describing a specified logical region corresponding to the robot; both the first and second attributes are value setting types. The region attribute can also include a third attribute of the switch setting type, which can be used to describe whether the robot can cross logical partitions during a single trip.

[0119] When assigning target robots to the goods to be scheduled for each logical partition, priority should be given to robots whose first attribute includes the logical partition, followed by robots whose second attribute includes the logical partition, and then robots whose third attribute allows them to cross logical partitions. In other words, the target robots for the logical partitions corresponding to the goods to be scheduled should be determined according to the order of the first, second, and third attributes.

[0120] Step S604: Determine the logical partition corresponding to each of the goods to be scheduled as the target area.

[0121] Specifically, the logical partitions corresponding to each cargo to be dispatched can be counted to obtain one or more target areas.

[0122] For example, a traversal approach can be used to determine each target area. Specifically, the logical partition corresponding to the first shipment to be scheduled can be obtained first, and this logical partition can be determined as one of the target areas. Then, the logical partition corresponding to the second shipment to be scheduled can be obtained. When this logical partition is different from all the previously obtained logical partitions, this logical partition can be determined as one of the target areas. This process continues until all the shipments to be scheduled have been traversed.

[0123] Step S605: Obtain the region attributes, including the operating status of each robot in the target region.

[0124] The operating status can include an order-accepting status and an order-unaccepting status. In the order-accepting status, at least one layer of the robot's temporary storage shelf is an idle layer and the order-accepting attribute is "acceptable". In the order-unaccepting status, the robot's order-accepting attribute is "unacceptable", or all layers of the temporary storage shelf are occupied, such as by goods for other tasks.

[0125] Specifically, the robot can detect the storage status of each layer of its temporary storage shelves, and then determine the robot's operating status based on the robot's order-taking attributes and the storage status of each layer of the cache shelves.

[0126] Step S606: Based on the task volume and task priority of the at least one task, determine each target robot to perform the at least one task from among the robots whose area attributes include the target area and whose running status is order-accepting.

[0127] Task priority can be determined based on the deadline of the order corresponding to the task or the deadline of the task itself. The closer the deadline, the higher the task priority.

[0128] Specifically, the batching attribute of at least one task can be determined based on the task quantity and priority of at least one task. The batching attribute describes whether the at least one task is allowed to be executed in batches. Batch execution means that the at least one task is divided into at least two batches. After determining the target robots for at least one task, each target robot first executes the first batch of tasks. After the robot moves the first batch of tasks to the corresponding operating table or target operating table, it executes the second batch of tasks, and so on.

[0129] In some embodiments, the batching attribute of tasks with a priority higher than a preset level can be set to disallow batch execution.

[0130] Furthermore, the remaining execution time of at least one task can be determined based on the deadline of at least one task, and then the batching attribute of at least one task can be determined based on the remaining execution time and the task volume of at least one task.

[0131] Specifically, based on the batching attributes of the at least one task, each target robot to perform the at least one task is determined from among the robots whose area attributes include the target area and whose operating status is order-accepting.

[0132] Specifically, when the batching attribute is not allowed to be executed in batches, each target robot to perform the at least one task can be determined from each robot whose area attribute includes the target area and whose running status is order-accepting, based on the quantity of goods to be scheduled corresponding to each target area. This allows each determined target robot to move each goods to be scheduled to the corresponding operating station in one batch.

[0133] Furthermore, when the batching attribute allows batch execution, the remaining execution time of at least one task can be determined based on its deadline. Then, based on this remaining execution time and the workload of the at least one task, the at least one task can be divided to obtain the workload for each batch. Subsequently, for each batch, based on the target areas corresponding to that batch and the goods to be dispatched corresponding to each target area, one or more robots whose area attributes include the target areas corresponding to that batch and whose operating status is "ready to accept orders" are identified as the target robots for that batch. Each target robot then handles the tasks corresponding to that batch.

[0134] Step S607: Based on the alleyway to which the storage space corresponding to each of the scheduled goods belongs, determine the task to be executed for each of the target robots, so that the span of the alleyway corresponding to the scheduled goods in the task to be executed for each target robot is less than a preset value.

[0135] The preset value can be 3, 5 or other values. By setting the preset value, the robot can cross fewer lanes when picking up the corresponding goods to be dispatched, thereby reducing the robot's walking distance and improving the efficiency of goods handling.

[0136] Specifically, to avoid a target robot traversing too many lanes during a single trip, i.e., while heading to retrieve one or more scheduled goods, thus causing the robot to travel too far, it is necessary to consider the lanes to which the storage space or warehouse location of each scheduled goods belongs when allocating scheduled goods to each target robot. This would prioritize allocating scheduled goods corresponding to the same lane or as few lanes as possible to a single target robot.

[0137] In this embodiment, after determining the various goods to be scheduled for a task, the physical partitions of the warehouse are divided based on the location of the storage space of each goods to be scheduled, thereby obtaining various logical partitions. Using the above method, the logical partitioning results may be different for different tasks, thus realizing a task-based dynamic partitioning strategy and improving the flexibility of the warehouse system partitioning. Based on the partitioning of the logical partitions, area attributes are set for each robot in the warehouse system. Based on the target area where the goods to be scheduled are located, and the area attributes including the operating status, workload, and task priority of each robot in the target area, a target robot is assigned to the task, realizing the matching of the logical area corresponding to the task with the robot, reducing the walking distance of the target robot when performing the task. Furthermore, based on the aisle to which the storage space of the goods to be scheduled belongs, a task to be executed is assigned to each target robot, thereby avoiding the need for the target robot to cross many aisles to retrieve the goods to be scheduled for the task, further reducing the robot's walking distance and improving the efficiency of task processing.

[0138] Optional, Figure 8 This is a flowchart of a task allocation method provided in another embodiment of the present disclosure. In this embodiment, a first partition attribute is set for each logical partition. This first partition attribute is used to describe a preset number of robots allowed to work in the logical partition at the same time, such as... Figure 8 As shown, this embodiment is based on the task allocation method provided in any of the above embodiments. After determining the tasks to be performed by each target robot, the task allocation method may further include the following steps:

[0139] Step S801: Obtain the number of robots currently operating in each logical partition corresponding to the goods to be scheduled.

[0140] Specifically, since the warehousing system receives different orders over a period of time, there may be situations where multiple orders are executed simultaneously. Therefore, before executing at least one of the above tasks, there may be robots operating in one or more logical partitions corresponding to the at least one task. Thus, it is necessary to count the number of robots operating in each logical partition corresponding to the at least one task, i.e., the number of tasks in each logical partition corresponding to the goods to be scheduled.

[0141] In some embodiments, the number of jobs can be 0.

[0142] In some embodiments, step S801 may be performed after determining each shipment to be scheduled corresponding to at least one task.

[0143] Step S802: For each logical partition corresponding to the goods to be scheduled, when the sum of the total number of target robots corresponding to the logical partition and the number of operations is greater than the preset number corresponding to the first partition attribute of the logical partition, a first type of robot and a second type of robot are determined from the target robots.

[0144] Wherein, the sum of the number of the first type of robots and the number of tasks is equal to the preset number, and the second type of robots are the target robots remaining after removing the first type of robots.

[0145] Specifically, when the number of robots working in a certain logical partition, i.e. the sum of the number of working robots and the total number of target robots, exceeds the maximum number of robots allowed to work in that logical partition, i.e. the aforementioned preset number, the target robots need to be grouped, that is, divided into first-class robots and second-class robots, in order to avoid too many people working at the same time in the same logical partition, which could easily lead to collisions.

[0146] Step S803: Control the first type of robot to execute the corresponding task to be executed.

[0147] Specifically, after grouping the target robots, the first group of robots will execute their corresponding tasks.

[0148] Step S804: When it is detected that the first number of robots in the logical partition have left the logical partition, control the first number of the second type of robots to move to the logical partition and execute the corresponding task to be executed.

[0149] The first quantity is the number of robots detected to have left the logical partition. It can be a first type of robot or a robot that is currently working, i.e. a robot performing other tasks within the logical partition. The first quantity can be 1.

[0150] After controlling the first type of robot to execute the corresponding task, while the first type of robot is executing the corresponding task, it is detected in real time whether there is a robot that has left the logical partition. If so, the second type of robot, with an equal number of robots that have left the logical partition, is controlled to move to the logical partition to execute the corresponding task, thereby improving task processing efficiency while ensuring safety.

[0151] Figure 9 The flowchart illustrates another embodiment of the task allocation method provided in this disclosure. In this embodiment, the robot's region attributes include a first attribute, which describes the logical partition to which the robot belongs during its lifecycle. This first attribute is immutable. The task allocation method provided in this embodiment is... Figure 2Based on the illustrated embodiment, step S202 is further refined as follows: Figure 9 As shown, the task allocation method provided in this embodiment includes the following steps:

[0152] Step S901: Determine each cargo to be dispatched corresponding to at least one task.

[0153] Step S902: Determine the logical partition corresponding to each of the goods to be scheduled as the target area.

[0154] Step S903: Obtain the running status of each first robot whose first attribute is the target area.

[0155] The first attribute can be set during robot initialization and cannot be modified after it is set. This first attribute describes the logical partition to which the robot belongs from beginning to end. It usually only applies to one logical partition. In some embodiments, the first attribute can correspond to multiple logical partitions.

[0156] When the logical partitions of the warehousing system change, the original logical partition identifiers can be retained, so that each robot whose first attribute is the original logical partition can adopt the identifier of the original logical partition for the new logical partition.

[0157] Specifically, after determining each target area, the robot's first attribute can be filtered based on the identifier of the target area to obtain each first robot whose first attribute is at least one logical partition in the target area, and the operating status of each first robot can be obtained.

[0158] Step S904: Based on the operating status of each of the first robots and the workload of the at least one task, determine each target robot that will perform the at least one task.

[0159] Specifically, based on the operating status of each first robot, the order capacity of each first robot can be determined, i.e., the number of idle shelves in the temporary storage area. Then, based on the task volume of the at least one task, the order capacity of each first robot, and the logical partition corresponding to the first attribute of each first robot, the target robots used to execute the at least one task can be determined.

[0160] Step S905: Based on the storage space corresponding to each of the goods to be scheduled, determine the task to be executed for each of the target robots to complete the at least one task.

[0161] The storage space refers to the space within the logical partition used for storing goods.

[0162] Specifically, after identifying each target robot, for each target robot whose first attribute corresponds to the same logical partition, the task to be executed for each target robot is determined based on the storage space corresponding to each scheduled item in that logical partition.

[0163] In this embodiment, by setting a first attribute for each robot during initialization, the logical partition corresponding to each robot in its life cycle is determined. When assigning tasks, the first attribute is given priority in determining the target robot, thereby realizing partition management and cargo processing and improving efficiency. When allocating the cargo to be scheduled in each logical partition, the storage space of each cargo to be scheduled is considered to specifically allocate the tasks to be executed by the target robot corresponding to that logical partition, so that the cargo to be scheduled processed by each target robot is as concentrated as possible, thereby further reducing the distance the robot travels during operation and improving cargo processing efficiency.

[0164] Optional, Figure 10 For this disclosure Figure 9 The flowchart of step S904 in the illustrated embodiment shows that, in this embodiment, the robot's region attribute further includes a second attribute. This second attribute describes one or more logical partitions to which the robot belongs, and this second attribute is a modifiable attribute, such as... Figure 10 As shown, step S904 may include the following steps:

[0165] Step S9041: Based on the task volume of the at least one task, determine whether the first total order volume of each first robot in the order-accepting state is less than the task volume of the at least one task.

[0166] Specifically, the order capacity of each first robot can be counted to obtain the first total order capacity, and it can be determined whether the first total order capacity is less than the task capacity of the at least one task. If not, each target robot is determined from each first robot, and the task to be executed by each target robot is determined according to the storage space corresponding to each goods to be scheduled, so as to complete the at least one task.

[0167] Step S9042: If yes, then obtain the task priority of the at least one task.

[0168] Task priority can be determined based on the priority or deadline of the order to which the task belongs, or based on the task's deadline. The closer the deadline, the higher the priority.

[0169] In some embodiments, task priorities may include a total of 5 levels, such as first priority to fifth priority.

[0170] Specifically, if the total number of orders received is less than the task volume of at least one task, meaning that each first robot cannot extract each item to be scheduled during a single trip, then a target robot needs to be assigned to the at least one task based on the task priority.

[0171] Step S9043: When the task priority is higher than the preset priority, each first robot whose running state is in the order-accepting state is determined as the first target robot, and the running state of each second robot whose second attribute includes the target area is obtained.

[0172] The preset priority can be a high priority, such as the third priority. The second attribute is a modifiable attribute, meaning that in subsequent tasks, the robot's second attribute can be modified or updated based on the task status of each logical partition.

[0173] Specifically, the robot's second attribute is used to set the various logical partitions that the robot can work on. The value range of the robot's second attribute can be used to describe the set of various logical partitions that the robot can work on. Setting the value of the robot's second attribute at the current time describes one or more logical partitions that the robot can work on at the current time.

[0174] For example, the second attribute of robot R91 includes logical partitions 91 to 95. This means that robot R91 can perform any one or more tasks in logical partitions 91 to 95 by adjusting the value of its second attribute. In other words, the value range of the second attribute of robot R91 is logical partitions 91 to 95. For example, if the value range is 91-95, such as when the second attribute of robot R91 is 93 and 95, it means that robot R91 can process the orders corresponding to logical partitions 93 and 95.

[0175] Specifically, when the task priority is high, that is, when at least one task is urgent, it is necessary to first identify each first robot whose running status is in the order-accepting state as the target robot, that is, the first target robot. At the same time, the second attributes of each second robot that include or correspond to at least one logical partition in the target area are obtained, and the running status of each second robot is obtained.

[0176] Step S9044: Based on the task volume of the at least one task and the first total order volume, determine at least one second robot whose running state is in the order-accepting state as the second target robot, so that the at least one task can be completed by each of the first target robots and the second target robots.

[0177] The first target robot and the second target robot are both the aforementioned target robots.

[0178] Specifically, based on the second total order quantity after deducting the first total order quantity from the task quantity of at least one task, the order quantity of each second robot in the order-accepting state, and the logical partition corresponding to the second attribute of each second robot, each second target robot can be determined so that each first target robot and the second target robot can complete the at least one task.

[0179] By setting a second attribute for the robot, the robot's regional attributes are enriched, and the flexibility of task allocation in the warehousing system is improved.

[0180] Optional, Figure 11 A flowchart of a task allocation method provided in another embodiment of this disclosure is shown. In this embodiment, the robot's region attribute further includes a third attribute, which describes the logical partitions that the robot can traverse during a single trip. This embodiment is... Figure 10 Based on the illustrated embodiment, when the total number of orders received by each first target robot and second target robot is less than the task volume of at least one task, the second total number of orders received is the sum of the first total number of orders received and the number of orders that each second target robot can receive, such as... Figure 11 As shown, when the total number of orders received by each of the first and second target robots is less than the task volume of the at least one task, the task allocation method may further include the following steps:

[0181] Step S1101: Obtain the operating status of each third robot in the target area, including the third attribute.

[0182] The third attribute is a modifiable attribute used to describe whether the robot can cross logical zones during a single operation, such as a pickup, and which logical zones it can cross. The third attribute can be a switch setting type; for example, a value of 0 indicates that crossing zones is not allowed, while a value of 1 indicates that crossing zones is allowed. When the third attribute is a switch setting type, the logical zones the robot can cross can be determined based on the first and second attributes. The third attribute can also be a value setting type to explicitly specify each logical zone the robot can cross.

[0183] For example, taking a warehousing system with three logical partitions, L001-L003, if the first attribute of robot R11 is L002, the second attribute is L003, and the third attribute is 0, it means that robot R11 can execute the task corresponding to logical partition L002 or L003 during a single operation. If the third attribute of robot R11 is 1, it means that robot R11 can execute the tasks corresponding to logical partitions L002 and L003 during a single operation.

[0184] Specifically, when the total number of orders received by each first target robot and the second target robot is still insufficient to meet the task volume of at least one task, it is necessary to consider the third attribute of the robot. Specifically, the third attribute includes each third robot of at least one logical partition corresponding to the target area, and the running status of each third robot is obtained.

[0185] Step S1102: Based on the second total order volume and the task volume, at least one third target robot is determined from each of the third robots in the order-accepting state, so that each of the first target robot, the second target robot and the third target robot can complete the at least one task.

[0186] Among them, the first target robot, the second target robot, and the third target robot are all the aforementioned target robots.

[0187] Specifically, based on the remaining task quantity after deducting the second total order quantity from the task quantity of at least one task and the logical partitions involved or included in the third attributes of each third robot, at least one third target robot can be determined from each third robot in the order-accepting state, so that the at least one task can be completed by each first target robot, second target robot and third target robot.

[0188] By setting a third attribute for the robot, the robot's regional attributes are further enriched, and the flexibility of task allocation in the warehousing system is improved. At the same time, by determining the target robot based on the order of the first, second, and third attributes, the rationality and scientific nature of task allocation are improved, thereby increasing the scheduling efficiency and cargo handling efficiency of the warehousing system.

[0189] Figure 12 This is a schematic diagram of the structure of a task allocation device provided in one embodiment of the present disclosure, as shown below. Figure 12 The device is applied to a warehousing system, the warehouse of which includes multiple logical partitions, each logical partition including one or more physical areas, and the device includes: a goods determination module 1210, a robot determination module 1220, and a task determination module 1230.

[0190] The cargo determination module 1210 is used to determine each cargo to be scheduled corresponding to at least one task; the robot determination module 1220 is used to determine each target robot according to the logical partition corresponding to each cargo to be scheduled and the regional attributes of each robot, wherein the regional attributes are used to describe the logical partition corresponding to the robot; the task determination module 1230 is used to determine the task to be executed of each target robot according to the storage space corresponding to each cargo to be scheduled, so as to complete the at least one task, wherein the storage space is the space in the logical partition used to store cargo.

[0191] Optionally, the robot determination module 1220 includes:

[0192] The target area determination unit is used to determine the logical partition corresponding to each of the goods to be scheduled as the target area; the robot determination unit is used to determine each target robot to perform the at least one task from each robot whose area attributes include the target area.

[0193] Optionally, the robot determining unit includes:

[0194] The robot status acquisition subunit is used to acquire the operating status of each robot whose area attributes include the target area; the robot determination subunit is used to determine each target robot to perform the at least one task from each robot whose area attributes include the target area and whose operating status is order-accepting, based on the task volume and task priority of the at least one task.

[0195] Optionally, the region attribute includes a first attribute, which describes the logical partition to which the robot belongs during its lifecycle, and the first attribute is an immutable attribute; the robot determination unit includes:

[0196] A first state acquisition subunit is used to acquire the running state of each first robot whose first attribute is the target area; a first robot determination subunit is used to determine each target robot that performs the at least one task based on the running state of each first robot and the task volume of the at least one task.

[0197] Optionally, the region attribute further includes a second attribute, which describes one or more logical partitions to which the robot belongs, and the second attribute is a modifiable attribute; the first robot determines the subunit, specifically for:

[0198] Based on the task volume of the at least one task, determine whether the total number of orders received by each first robot in the order-accepting state is less than the task volume of the at least one task; if so, obtain the task priority of the at least one task; when the task priority is higher than a preset priority, determine each first robot in the order-accepting state as a first target robot, and obtain the running status of each second robot whose second attribute includes the target area; based on the task volume of the at least one task and the first total number of orders received, determine at least one second robot in the order-accepting state as a second target robot, so that each first target robot and the second target robot can complete the at least one task.

[0199] Optionally, the region attribute further includes a third attribute, which describes the logical partitions that the robot can traverse during a single trip. When the second total number of orders received by each of the first and second target robots is less than the task volume of the at least one task, the robot determination unit further includes:

[0200] The third robot determination subunit is used to obtain the operating status of each third robot including the target area as the third attribute; and to determine at least one third target robot from each third robot whose operating status is in the order-accepting state according to the second total order volume and the task volume, so that each of the first target robot, the second target robot and the third target robot can complete the at least one task.

[0201] Optionally, the logical partition includes a first partition attribute, which describes a preset number of robots allowed to operate in the logical partition at the same time; the device further includes:

[0202] The module for acquiring the number of tasks is used to acquire the number of tasks currently being performed by robots in each logical partition corresponding to the goods to be scheduled. The module for classifying robots is used to, for each logical partition corresponding to the goods to be scheduled, determine a first type of robot and a second type of robot from the target robots when the sum of the total number of target robots in the logical partition and the number of tasks exceeds a preset number corresponding to the first partition attribute of the logical partition. The first type of robot and the number of tasks are equal to the preset number, and the second type of robot is the target robots remaining after removing the first type of robots. The module for controlling the first type of robot is used to control the first type of robot to execute the corresponding task to be executed. The module for controlling the second type of robot is used to control the first number of second type robots to move to the logical partition and execute the corresponding task to be executed when a first number of robots in the logical partition are detected to have left the logical partition.

[0203] Optionally, the device further includes:

[0204] The logical partitioning module is used to divide the physical areas of the warehouse according to the location of the storage space of each of the goods to be scheduled corresponding to the at least one task, so as to determine the logical partitions of the warehousing system; the area attribute setting module is used to set the area attributes of each robot according to the logical partitions.

[0205] Optional, the task determination module 1230 is specifically used for:

[0206] Based on the alleyway to which the storage space corresponding to each of the goods to be scheduled belongs, the task to be executed by each of the target robots is determined, so that the span of the alleyway corresponding to the goods to be scheduled in the task to be executed by each target robot is less than a preset value.

[0207] Optionally, the device further includes:

[0208] The task partitioning module is used to receive orders before determining the individual goods to be scheduled for at least one task; and to determine at least one task based on the orders. The workstation determination module is used to determine one or more target workstations based on the task requirements of the at least one task, the logical partitions corresponding to each workstation, and the goods storage status of each logical partition, wherein the logical partitions corresponding to the one or more target workstations contain goods that meet the task requirements of the at least one task; the goods determination module is specifically used to determine the individual goods to be scheduled for the at least one task in the logical partitions corresponding to the target workstations based on the task requirements of the at least one task.

[0209] The task allocation device provided in this disclosure can execute the task allocation method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0210] Figure 13 This is a schematic diagram of the structure of a task allocation device provided in one embodiment of the present disclosure, as shown below. Figure 13 As shown, the task allocation device includes: a memory 1310, a processor 1320, and a computer program.

[0211] The computer program is stored in memory 1310 and configured to be executed by processor 1320 to implement this disclosure. Figure 2 , Figure 5 , Figure 6 as well as Figures 8 to 11 The task allocation method provided in any of the corresponding embodiments.

[0212] The memory 1310 and the processor 1320 are connected via a bus 1330.

[0213] For relevant instructions, please refer to the corresponding text. Figure 2 , Figure 5 , Figure 6 as well as Figures 8 to 11 The relevant descriptions and effects corresponding to the steps will be understood, and will not be elaborated on here.

[0214] Figure 14 This is a schematic diagram of the structure of a warehousing system provided in one embodiment of the present disclosure, as shown below. Figure 14As shown, the warehousing system includes: a warehouse with multiple logical partitions 1410, a robot 1420, and a task allocation device 1430.

[0215] Among them, task allocation device 1430 is disclosed in this publication. Figure 13 The illustrated embodiment provides a task allocation device. Each logical partition 1410 includes one or more physical areas for storing goods. Figure 14 The solid-lined box in the middle represents the physical area.

[0216] In some embodiments, the warehousing system may also include devices such as control panels, unloading machines, elevators, and conveyor lines.

[0217] One embodiment of this disclosure provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement this disclosure. Figure 2 , Figure 5 , Figure 6 as well as Figures 8 to 11 The task allocation method provided in any of the corresponding embodiments.

[0218] The computer-readable storage medium can be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0219] This disclosure also provides a program product comprising an executable computer program stored in a readable storage medium. At least one processor of a task allocation device or storage system can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the task allocation device to implement the task allocation methods provided in the various embodiments described above.

[0220] In the several embodiments provided in this disclosure, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0221] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0222] Furthermore, the functional modules in the various embodiments of this disclosure can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The aforementioned modular unit can be implemented in hardware or in a combination of hardware and software functional units.

[0223] The integrated modules implemented as software functional modules described above can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this disclosure.

[0224] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this disclosure can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0225] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0226] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0227] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0228] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. Both the processor and the storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic device or host device.

[0229] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0230] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure, and are not intended to limit them. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this disclosure.

Claims

1. A method of task allocation, characterized by, The method is applied to a warehousing system, the warehouse of which includes robots and multiple logical partitions, each of which includes one or more physical areas. The robots are configured with area attributes, which are used to describe the logical partitions in which the robots can perform tasks. The method includes: Identify at least one target task corresponding to goods to be scheduled; Based on the logical partition corresponding to the goods to be scheduled and the regional attributes of the robot, each target robot to perform the at least one target task is determined. The regional attributes of the robot include at least one of the following: an unmodifiable first attribute, a modifiable second attribute, and a third attribute that allows it to operate across regions. Based on the storage space corresponding to the goods to be scheduled, the tasks to be executed by each of the target robots are determined to complete the at least one task, wherein the storage space is the space in the logical partition used to store the goods.

2. The method of claim 1, wherein, Based on the logical partition corresponding to the goods to be scheduled and the regional attributes of the robot, determine each target robot to perform the at least one target task, including: The logical partition corresponding to the goods to be scheduled is determined as the target area; From the robots whose regional attributes include the target region, each target robot is determined to perform the at least one target task.

3. The method according to claim 2, characterized in that, Determining each target robot to perform the at least one target task from among the robots whose regional attributes include the target region includes: The obtained regional attributes include the operating status of each robot in the target region; Based on the task volume and priority of the at least one target task, each target robot to perform the at least one target task is determined from among the robots whose area attributes include the target area and whose operating status is order-accepting.

4. The method according to claim 2, characterized in that, The region attribute includes a first attribute, which describes the logical partition to which the robot belongs during its life cycle, and the first attribute is an immutable attribute. Determining each target robot to perform the at least one target task from among the robots whose regional attributes include the target region includes: Obtain the operating status of each first robot whose first attribute is the target area; Based on the operating status of each of the first robots and the workload of the at least one target task, each target robot that will perform the at least one target task is determined.

5. The method according to claim 4, characterized in that, The region attribute also includes a second attribute, which describes one or more logical partitions to which the robot belongs, and the second attribute is a modifiable attribute; Based on the operating status of each of the first robots and the workload of the at least one target task, determine each target robot to perform the at least one target task, including: Based on the task volume of the at least one target task, determine whether the first total order volume of each first robot whose running state is in the order-accepting state is less than the task volume of the at least one target task. If so, then obtain the task priority of the at least one target task; When the task priority is higher than the preset priority, each first robot whose running state is in the order-accepting state is determined as the first target robot, and the running state of each second robot whose second attribute includes the target area is obtained; Based on the task volume of the at least one target task and the first total order volume, at least one second robot whose operating state is in the order-accepting state is determined as the second target robot, so that the at least one target task can be completed by each of the first target robots and the second target robots.

6. The method according to claim 5, characterized in that, The region attribute further includes a third attribute, which describes the logical partition that the robot can traverse during a single trip. When the total number of orders received by each of the first and second target robots is less than the task volume of the at least one target task, the method further includes: The third attribute obtained includes the operating status of each third robot in the target area; Based on the second total order volume and the task volume, at least one third target robot is determined from each of the third robots in the order-accepting state, so that each of the first target robot, the second target robot and the third target robot can complete the at least one target task.

7. The method according to claim 1, characterized in that, The at least one target task includes only one target task. Determining each target robot to execute the at least one target task based on the logical partition corresponding to the goods to be scheduled and the robot's regional attributes includes: The logical partition corresponding to the goods to be scheduled is determined as the target area; From the robots whose regional attributes include the target region, a target robot is determined to perform the target task based on the storage space corresponding to the goods to be scheduled. The task to be performed by the target robot includes the goods to be scheduled.

8. The method according to any one of claims 1-6, characterized in that, The logical partition includes a first partition attribute, which describes a preset number of robots allowed to operate in the logical partition at the same time; the method further includes: Obtain the number of robots currently operating within each logical partition corresponding to the goods to be scheduled; For each logical partition corresponding to the goods to be scheduled, when the sum of the total number of target robots corresponding to the logical partition and the number of jobs is greater than the preset number corresponding to the first partition attribute of the logical partition, a first type of robot and a second type of robot are determined from the target robots, wherein the sum of the number of the first type of robot and the number of jobs is equal to the preset number, and the second type of robot is the target robot remaining after removing the first type of robot; Control the first type of robot to execute the corresponding task to be performed; When a first number of robots in the logical partition are detected to have left the logical partition, the system controls the first number of second-type robots to move to the logical partition and execute the corresponding task to be performed.

9. The method according to any one of claims 1-6, characterized in that, The method further includes: Based on the location of the storage space for the goods to be scheduled corresponding to the at least one target task, the warehouse area is divided to determine the logical partitions of the warehousing system. Based on the aforementioned logical partitions, set the regional attributes for each robot.

10. The method according to any one of claims 1-6, characterized in that, Based on the storage space corresponding to the goods to be scheduled, determine the tasks to be performed by each of the target robots, including: Based on the alleyway to which the storage space corresponding to the goods to be scheduled belongs, the tasks to be performed by each target robot are determined, so that the span of the alleyway corresponding to the goods to be scheduled in the tasks to be performed by each target robot is less than a preset value.

11. The method according to any one of claims 1-6, characterized in that, Before determining the cargo to be dispatched corresponding to at least one target task, the method further includes: Receive orders; At least one target task is determined based on the order; Based on the task requirements of the at least one target task, the logical partitions corresponding to each operating station, and the goods storage status of each logical partition, one or more target operating stations are determined, wherein the logical partitions corresponding to the one or more target operating stations contain goods that meet the task requirements of the at least one target task. Accordingly, at least one target task corresponding to the goods to be dispatched is identified, including: Based on the task requirements of the at least one target task, determine the goods to be scheduled for the at least one target task in the logical partition corresponding to the target operation console.

12. A task allocation device, characterized in that, The device is applied to a warehousing system, the warehouse of which includes a robot and multiple logical partitions. Each logical partition includes one or more physical areas. The robot is configured with area attributes, which are used to describe the logical partitions in which the robot can perform tasks. The device includes: The cargo determination module is used to determine the cargo to be dispatched corresponding to at least one target task; The robot determination module is used to determine each target robot that will perform the at least one target task based on the logical partition corresponding to the goods to be scheduled and the regional attributes of the robot. The task determination module is used to determine the tasks to be executed by each of the target robots based on the storage space corresponding to the goods to be scheduled, so as to complete the at least one task, wherein the storage space is the space in the logical partition used to store goods.

13. A task allocation device, characterized in that, include: Memory and at least one processor; The memory stores computer-executed instructions; The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the task allocation method as described in any one of claims 1-11.

14. A warehousing system, characterized in that, include: The robot, the warehouse including multiple logical partitions, and the task allocation device as described in claim 13.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by the processor, implement the task allocation method as described in any one of claims 1-11.

16. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the task allocation method as described in any one of claims 1-11.

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