Warehouse scheduling method, device, electronic equipment and medium

Abstract

The present disclosure relates to a method, device, electronic device and medium for warehouse scheduling, which can be applied to the field of warehouse logistics. The above-mentioned warehouse scheduling method includes: obtaining pending handling tasks; determining whether the task processing limit value of the idle handling subject is less than the total number of the above-mentioned pending handling tasks; when the above-mentioned task processing limit value is less than the above-mentioned total number, determining the processing priority corresponding to each pending handling task according to the similarity between the first task path vector of the pending handling task and the second task path vector of the handling task in the processing state; according to the above-mentioned processing priority, determining the target pending task adapted to the above-mentioned task processing limit value in the above-mentioned pending handling tasks; determining the target matching combination between the above-mentioned target pending task and the above-mentioned idle handling subject; and according to the above-mentioned target matching combination, sending the corresponding target pending task to the above-mentioned idle handling subject.

Description

Technical Field

[0001] The present disclosure relates to the technical field of warehousing and logistics, and in particular to a method, device, electronic equipment and medium for warehousing scheduling. Background Art

[0002] With the increase in e-commerce transaction volume, the supporting warehousing logistics has gradually become intelligent. In a three-dimensional warehouse (referred to as a three-dimensional warehouse), goods are transported and stored on pallets. For example, in the outbound process, the stacker takes the pallet from the storage location and transports it to the conveyor line, which transports the pallet to the outbound port of the conveyor line. The forklift driver drives the forklift to transport the pallet to the outbound destination.

[0003] Currently, most of the inbound and outbound operations are performed by manually driving forklifts. Usually, a large-size display screen is set at the outbound port to display the inbound task information in real time. Some are also equipped with prompting devices to prompt the forklift driver to perform the operation. There are subjective factors in the operation mode of manually driving forklifts, which may lead to deviations in the operation results and low operation efficiency. At the same time, in the process of task scheduling by the scheduling system, there are still problems of unreasonable scheduling and low task processing efficiency. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the embodiments of the present disclosure provide a method, device, electronic device and medium for warehouse scheduling.

[0005] In the first aspect, an embodiment of the present disclosure provides a method for warehouse scheduling. The above-mentioned warehouse scheduling method includes: obtaining pending handling tasks; determining whether the task processing limit value of the idle handling subject is less than the total number of the above-mentioned pending handling tasks; when the above-mentioned task processing limit value is less than the above-mentioned total number, determining the processing priority corresponding to each pending handling task according to the similarity between the first task path vector of the pending handling task and the second task path vector of the handling task in the processing state; according to the above-mentioned processing priority, determining the target pending task adapted to the above-mentioned task processing limit value among the above-mentioned pending handling tasks; determining the target matching combination between the above-mentioned target pending task and the above-mentioned idle handling subject; and according to the above-mentioned target matching combination, sending the corresponding target pending task to the above-mentioned idle handling subject.

[0006] According to an embodiment of the present disclosure, the above-mentioned method of determining the processing priority corresponding to each pending handling task based on the similarity between the first task path vector of the pending handling task and the second task path vector of the handling task in the processing state includes: calculating the similarity between the first task path vector of each pending handling task and the second task path vector of the handling task in the processing state; sorting the similarities calculated for each pending handling task to obtain a sorting result; and according to the sorting result, determining that the lower the similarity, the higher the processing priority corresponding to the pending handling task.

[0007] According to an embodiment of the present disclosure, the elements in the first task path vector of the above-mentioned handling task to be processed include: the task values ​​of the starting position and the ending position of each handling path of the handling task passed by the planned path of the handling task to be processed; the above-mentioned handling task includes the above-mentioned handling task to be processed and the above-mentioned handling task in the processing state; the elements in the second task path vector of the above-mentioned handling task in the processing state include: the task values ​​of the starting position and the ending position of each handling path of the above-mentioned handling task passed by the planned path of the handling task in the processing state.

[0008] According to an embodiment of the present disclosure, when a specific starting position or a specific ending position has not been passed by a handling task to be processed, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned first task path vector is 0; when a specific starting position or a specific ending position is passed by a handling task to be processed, each time it is passed, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned first task path vector is increased by 1. When a specific starting position or a specific ending position has not been passed by a handling task in a processing state, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned second task path vector is 0; when a specific starting position or a specific ending position is passed by a handling task to be processed, each time it is passed, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned second task path vector is increased by 1. The above-mentioned similarity includes cosine similarity.

[0009] According to an embodiment of the present disclosure, the above-mentioned warehouse scheduling method further includes: when the above-mentioned task processing limit value is greater than or equal to the above-mentioned total number, determining the above-mentioned to-be-processed handling task as the above-mentioned target to-be-processed task.

[0010] According to an embodiment of the present disclosure, determining a target matching combination between the above-mentioned target tasks to be processed and the above-mentioned idle transport entities includes: determining the distance information required for each of the above-mentioned idle transport entities to execute each of the above-mentioned target tasks to be processed; determining a target matching combination based on the above-mentioned distance information, wherein the above-mentioned target matching combination minimizes the total distance required for all the matched idle transport entities to execute the corresponding target tasks to be processed.

[0011] According to an embodiment of the present disclosure, a target matching combination is determined according to the above-mentioned distance information, including: based on an integer programming model, taking the minimum value of the total distance required for all idle transport entities under the candidate matching relationship to execute the corresponding target pending tasks as a linear programming target; taking the task processing limit value corresponding to each of the above-mentioned idle transport entities as a first constraint condition; taking the number of transport entities supported by each target pending task as a second constraint condition; taking the sum of the values ​​of all candidate matching relationships corresponding to the smaller of the task processing limit value of the above-mentioned idle transport entities and the total number of the above-mentioned pending transport tasks as a third constraint condition; taking the integer value corresponding to the candidate matching relationship as a fourth constraint condition; under the constraints of the above-mentioned first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition, solving the optimal solution of the matching relationship corresponding to the above-mentioned linear programming target, and the above-mentioned optimal solution of the matching relationship is taken as the above-mentioned target matching combination.

[0012] According to an embodiment of the present disclosure, the above-mentioned determination of the distance information required for each of the above-mentioned idle transport entities to execute each of the above-mentioned target tasks to be processed includes: determining, according to the task execution path constructed by the above-mentioned idle transport entities in the navigation map, the distance information required for each of the above-mentioned idle transport entities to execute the above-mentioned target tasks to be processed from their current location, and based on the above-mentioned task execution path.

[0013] According to an embodiment of the present disclosure, the above-mentioned determination of the distance information required for each of the above-mentioned idle transport entities to execute each of the above-mentioned target tasks to be processed includes: determining whether there is a target obstacle in the straight line between the starting position and the ending position of the above-mentioned target tasks to be processed; in the case that the above-mentioned target obstacle does not exist in the above-mentioned straight line, the distance from the current position of the above-mentioned idle transport entity to the execution starting point of the above-mentioned target tasks to be processed is added with the Euclidean distance between the starting position and the ending position of the above-mentioned target tasks to be processed to obtain the required distance information; in the case that the above-mentioned target obstacle exists in the above-mentioned straight line, according to the task execution path constructed by the above-mentioned idle transport entities in the navigation map, the distance information required for each of the above-mentioned idle transport entities to execute the above-mentioned target tasks to be processed from the current position to the execution starting point of the above-mentioned target tasks to be processed and based on the above-mentioned task execution path is determined.

[0014] According to an embodiment of the present disclosure, the above-mentioned obtaining of pending handling tasks includes: receiving handling tasks sent by the vertical warehouse management device, and placing the above-mentioned handling tasks into a task pool; the above-mentioned handling tasks include one or more of outbound handling tasks and inbound handling tasks; obtaining pending handling tasks from the above-mentioned task pool.

[0015] According to an embodiment of the present disclosure, the idle transport subject includes: a transport robot in an idle state, the transport robot being an autonomous mobile robot based on real-time positioning and map building technology. The map of the transport robot is marked with the physical locations of the exit and destination storage locations corresponding to the transport tasks to be processed, or the physical locations of the initial storage locations and entry corresponding to the transport tasks to be processed.

[0016] According to an embodiment of the present disclosure, the above-mentioned idle transporting entity includes: a manually operated transporting equipment, which has navigation and positioning functions as well as communication functions; or the manual operator who operates the transporting equipment listens to instructions through the outbound delivery control software installed in the mobile device to perform the operation, and the outbound delivery control software has navigation and positioning functions as well as communication functions.

[0017] In the second aspect, an embodiment of the present disclosure provides a method for data processing. The above-mentioned data processing method can be applied to a vertical warehouse management device. The above-mentioned data processing method includes: obtaining information on the entry and exit of items, the above-mentioned information on the entry and exit of items includes one or more of item exit requirement information and item entry requirement information; generating a handling task based on the above-mentioned information on the entry and exit of items, the above-mentioned handling task includes one or more of an outbound handling task and an inbound handling task; detecting whether the intelligent handling switch is in the on state; when the above-mentioned intelligent handling switch is in the on state, sending the above-mentioned handling task to a warehouse scheduling device, so that the above-mentioned warehouse scheduling device executes the warehouse scheduling method as described above.

[0018] According to an embodiment of the present disclosure, the data processing method further includes: when the intelligent transport switch is in an off state, sending the transport task to a display screen for display, and controlling a prompt device to issue a prompt to a manually operated transport device.

[0019] In a third aspect, an embodiment of the present disclosure provides a method for handling operations. The above-mentioned method for handling operations includes: receiving a target task to be processed sent by a storage scheduling device; marking the physical locations corresponding to the above-mentioned starting location and ending location in a navigation map according to the information of the starting location and ending location of the above-mentioned target task to be processed; constructing a task execution path according to the physical locations corresponding to the marked starting location and ending location; and executing the above-mentioned target task to be processed based on the above-mentioned task execution path.

[0020] In a fourth aspect, an embodiment of the present disclosure provides a storage scheduling device. The storage scheduling device includes: a task acquisition module, a processing limit determination module, a task priority determination module, a priority task determination module, a matching combination determination module and a first communication module. The task acquisition module is used to acquire pending handling tasks. The processing limit determination module is used to determine whether the task processing limit value of the idle handling subject is less than the total number of the pending handling tasks. The task priority determination module is used to determine the processing priority corresponding to each pending handling task according to the similarity between the first task path vector of the pending handling task and the second task path vector of the handling task in the processing state when the task processing limit value is less than the total number. The priority task determination module is used to determine the target pending task adapted to the task processing limit value in the pending handling tasks according to the processing priority. The matching combination determination module is used to determine the target matching combination between the target pending task and the idle handling subject. The first communication module is used to send the corresponding target pending task to the idle handling subject according to the target matching combination.

[0021] In a fifth aspect, an embodiment of the present disclosure provides a vertical warehouse management device. The vertical warehouse management device includes: an in-and-out information acquisition module, a task generation module, a detection module and a second communication module. The in-and-out information acquisition module is used to acquire item in-and-out information, and the item in-and-out information includes one or more of item out-of-warehouse requirement information and item in-warehouse requirement information. The task generation module is used to generate a handling task based on the item in-and-out information, and the handling task includes one or more of an out-of-warehouse handling task and an in-warehouse handling task. The detection module is used to detect whether the intelligent handling switch is in the on state. The second communication module is used to send the handling task to the warehouse scheduling device when the intelligent handling switch is in the on state.

[0022] According to an embodiment of the present disclosure, the second communication module is also used to send the transport task to the display screen for display when the intelligent transport switch is in the off state, and control the prompt device to issue a prompt to the manually operated transport device.

[0023] In a sixth aspect, an embodiment of the present disclosure provides a handling device. The handling device includes: a task receiving module, a position marking module, a path building module and a handling module. The task receiving module is used to receive the target task to be processed sent by the warehouse scheduling device. The position marking module is used to mark the physical positions corresponding to the starting position and the ending position in the navigation map according to the information of the starting position and the ending position of the target task to be processed. The path building module is used to build a task execution path according to the physical positions corresponding to the marked starting position and the ending position. The handling module is used to execute the target task to be processed according to the task execution path.

[0024] In a seventh aspect, an embodiment of the present disclosure provides an electronic device. The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory is used to store computer programs; and the processor is used to implement the above-mentioned storage scheduling method, data processing method, or handling operation method when executing the program stored in the memory.

[0025] In an eighth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for warehouse scheduling, the method for data processing, or the method for handling operations described above is implemented.

[0026] The above technical solution provided by the embodiments of the present disclosure has at least some or all of the following advantages:

[0027] When the task processing limit of the idle transport subject is less than the total number of the above-mentioned transport tasks to be processed, the processing priority corresponding to each transport task to be processed is determined according to the similarity between the first task path vector of the transport task to be processed and the second task path vector of the transport task in the processing state; according to the above-mentioned processing priority, the target transport task to be processed that is adapted to the above-mentioned task processing limit is determined among the above-mentioned transport tasks to be processed; on the premise of meeting the task acceptance capacity as much as possible, it can help to stagger the routes corresponding to the ongoing tasks to avoid congestion in the transport routes; by sending the corresponding target tasks to be processed to the above-mentioned idle transport subjects according to the target matching combination, the transport subjects in the idle state and the corresponding tasks are matched, thereby improving the task processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0030] Figure 1A The system architecture of the method and device for warehouse scheduling and data processing applicable to the embodiments of the present disclosure is schematically shown;

[0031] Figure 1B The following schematically shows an operation scenario diagram in a warehouse scheduling process provided by an embodiment of the present disclosure;

[0032] Figure 2 A flowchart of a storage scheduling method provided by an embodiment of the present disclosure is schematically shown;

[0033] Figure 3 A flowchart of a storage scheduling method provided by another embodiment of the present disclosure is schematically shown;

[0034] Figure 4 The detailed implementation flow chart of operation S230a of the embodiment of the present disclosure is schematically shown;

[0035] Figure 5 The detailed implementation flow chart of operation S250 of the embodiment of the present disclosure is schematically shown;

[0036] Figure 6 The detailed implementation flow chart of operation S512 of the embodiment of the present disclosure is schematically shown.

[0037] Figure 7 The flowchart of the data processing method provided by the embodiment of the present disclosure is schematically shown;

[0038] Figure 8 A flow chart schematically shows a method for handling operations provided by an embodiment of the present disclosure;

[0039] Fig. 9 The structural block diagram of the storage scheduling device provided by the embodiment of the present disclosure is schematically shown;

[0040] Fig.10 The structure block diagram of the vertical library management device provided by the embodiment of the present disclosure is schematically shown;

[0041] Fig.11 The structure block diagram of the transport equipment provided by the embodiment of the present disclosure is schematically shown; and

[0042] Fig.12 The structural block diagram of the electronic device provided by the embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0043] Currently, most of the inbound and outbound operations are performed by manually driving forklifts. Usually, a large-size display screen is set at the outbound port to display the inbound and outbound task information in real time, and some are also equipped with prompting devices to prompt the forklift driver to perform the operation.

[0044] In the manual forklift-based handling method, it is usually necessary to manually observe the outbound task information on the display screen or wait for prompt information to perform the operation, which is highly subjective. For example, there are the following problems: the forklift driver is prone to misread the information on the large screen, or remember it incorrectly, resulting in the wrong destination of the handling, thereby increasing the cost of subsequent manual search and sorting; the forklift driver may not receive the reminder of the handling task in time and cannot immediately perform the handling task; the vacant storage space of the destination flow is selected by the forklift driver independently, which is not convenient for subsequent review and other process search and management; different forklift drivers have different execution degrees and driving skills for handling and picking up pallets, and the operating specifications cannot be completely consistent. For the dispatching system, when multiple forklifts are working at the same time, it is not easy to dispatch them uniformly, and there will be mutual interference. At the same time, in the process of task scheduling by the dispatching system, for the dispatching in multi-task scenarios, there are still problems of unreasonable scheduling and low task processing efficiency.

[0045] In view of this, the embodiments of the present disclosure provide a method, device, electronic device and medium for warehouse scheduling. The above-mentioned warehouse scheduling method includes: obtaining pending handling tasks; determining whether the task processing limit value of the idle handling subject is less than the total number of the above-mentioned pending handling tasks; when the above-mentioned task processing limit value is less than the above-mentioned total number, determining the processing priority corresponding to each pending handling task according to the similarity between the first task path vector of the pending handling task and the second task path vector of the handling task in the processing state; according to the above-mentioned processing priority, determining the target pending task adapted to the above-mentioned task processing limit value among the above-mentioned pending handling tasks; determining the target matching combination between the above-mentioned target pending task and the above-mentioned idle handling subject; and according to the above-mentioned target matching combination, sending the corresponding target pending task to the above-mentioned idle handling subject.

[0046] The data processing method provided by the embodiment of the present disclosure can be applied to a vertical warehouse management device, and the method includes: obtaining information on the entry and exit of items, the information on the entry and exit of items including one or more of item exit requirement information and item entry requirement information; generating a handling task based on the entry and exit information of items, the handling task including one or more of an outbound handling task and an inbound handling task; detecting whether the intelligent handling switch is in the on state; and when the intelligent handling switch is in the on state, sending the handling task to a warehouse scheduling device, so that the warehouse scheduling device executes the warehouse scheduling method as described above.

[0047] The method for handling operations provided by the embodiment of the present disclosure includes: receiving a target task to be processed sent by a warehouse scheduling device; marking the physical positions corresponding to the start position and the end position in a navigation map according to information of the start position and the end position of the target task to be processed; constructing a task execution path according to the physical positions corresponding to the marked start position and the end position; and executing the target task to be processed based on the task execution path.

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0049] Figure 1A The system architecture of the method and device for warehouse scheduling and data processing applicable to the embodiments of the present disclosure is schematically shown; Figure 1B A schematic diagram of an operation scenario in a warehouse scheduling process provided by an embodiment of the present disclosure is schematically shown.

[0050] Reference Figure 1A As shown, the system architecture 100 of the warehouse scheduling and data processing method and device applicable to the embodiment of the present disclosure includes: a vertical warehouse equipment 110, a handling robot 121, a manually operated handling equipment 122, a storage area 130, a vertical warehouse management device 140 and a warehouse scheduling device 150.

[0051] In the embodiments of the present disclosure, referring to Figure 1AAs shown in the communication link indicated by the solid lightning shape in the figure, the vertical warehouse equipment 110 is connected to the vertical warehouse management device 140 through a network, the vertical warehouse management device 140 is connected to the storage scheduling device 150 through a network, and the storage scheduling device 150 is connected to the handling robot 121 through a network. The network is a medium that provides a communication link and can include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0052] The current manually operated handling equipment 122 relies on manual operation control of the handling equipment 122, including specific route planning, selection of cargo placement, etc., which are all decided manually; the handling equipment 122 is only responsible for transporting, loading and unloading cargo under manual control.

[0053] The warehouse scheduling method provided by the embodiment of the present disclosure can be executed by the warehouse scheduling device 150 in the system architecture 100, the data processing method provided can be executed by the warehouse management device 140 in the system architecture 100, and the operation method provided can be executed by the transport robot 121.

[0054] The above-mentioned transport robot 121 can autonomously build maps and locate navigation based on environmental information, and can autonomously drive to the destination point. Taking the outbound process as an example, all the physical locations of the outbound port and the destination storage location have been created and marked in the robot's map; correspondingly, for the inbound process, the physical locations corresponding to the inbound port and the initial storage location are also created and marked in the robot's map.

[0055] According to the concept of the present disclosure, in some other embodiments, referring to Figure 1A As shown by the dotted lightning in the figure, after the manually operated transport equipment 122 is improved, for example, the transport equipment 122 is equipped with navigation and positioning functions and communication functions, or the person who operates the transport equipment 122 listens to instructions through a mobile device such as a warehouse control software installed in a smart phone to perform operations, in this case, the operating method provided in the embodiment of the present disclosure can be executed by the manually operated transport equipment 122.

[0056] Reference Figure 1A and Figure 1B As shown, the vertical warehouse equipment 110 includes shelves 111, stackers 112, inlet and outlet conveyor lines 113, main conveyor lines 114 and inlet and outlet 115. When performing outbound or inbound operations, the vertical warehouse management device 140 sends a handling task to the warehouse scheduling device 150. The warehouse scheduling device 150 executes the warehouse scheduling method provided by the embodiment of the present disclosure, obtains a target matching combination, and sends the corresponding target pending task to the idle handling subject according to the target matching combination. Correspondingly, the idle handling subject can be a handling robot 121 or the improved manually controlled handling equipment 122 described above. Figure 1B The transport robot 121 or the improved manually controlled transport device 122 performs the method of transport operation provided by the embodiment of the present disclosure.

[0057] In the embodiment of the present disclosure, each storage location in the storage area 130 is digitally managed, for example, referring to Figure 1B As shown, taking the outbound process as an example, the destination flow area in the storage area 130 and the destination storage locations in the area are digitally managed, and the destination storage locations in each destination flow area are numbered and set with status and other information. The destination flow information includes name and number, such as area A, area B, area C, area D, etc.; the destination storage location information includes: number, status, coordinate point, destination flow number, etc. For example, the destination storage locations in area A are A1, A2, A3, etc., the destination storage locations in area B are B1, B2, B3, etc., the destination storage locations in area C are C1, C2, C3, etc., and the destination storage locations in area D are D1, D2, D3, etc.

[0058] The coordinate points in the storage location information refer to the coordinate positions in the navigation map. For example, the navigation map is built into the transport robot 121, or the navigation map is built into the improved manually operated transport equipment 122, or is located in the outbound control software installed by the person who operates the transport equipment 122 through a mobile device such as a smart phone.

[0059] The statuses in the storage location information may include the following categories: Free: There is no pallet stored in the storage location, and it can be selected as the destination storage location for outbound transportation; Pre-occupied: After selecting an idle destination storage location for outbound transportation, it must be pre-occupied first to prevent contention for destination storage location resources; Occupied: The pallet has been placed in the destination storage location; Disabled: It cannot be used as a destination storage location for outbound transportation, and is used in some special scenarios. It is temporarily set to disabled manually, such as temporarily storing other goods, storage location construction, etc.

[0060] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0061] The first exemplary embodiment of the present disclosure provides a method for warehouse scheduling, which can be executed by the warehouse scheduling device 150 in the system architecture 100 .

[0062] Figure 2 A flowchart of a warehouse scheduling method provided by an embodiment of the present disclosure is schematically shown.

[0063] Reference Figure 2 As shown in the solid line portion, the embodiment of the present disclosure provides a method for warehouse scheduling, including the following operations: S210, S220, S230a, S240a, S250 and S260.

[0064] In operation S210, a transport task to be processed is obtained.

[0065] According to an embodiment of the present disclosure, the above-mentioned obtaining of pending handling tasks includes: receiving handling tasks sent by the vertical warehouse management device, and placing the above-mentioned handling tasks into a task pool; the above-mentioned handling tasks include one or more of outbound handling tasks and inbound handling tasks; obtaining pending handling tasks from the above-mentioned task pool.

[0066] In operation S220, it is determined whether the task processing limit value of the idle transporting body is less than the total number of the transporting tasks to be processed.

[0067] The task processing limit of an idle transport subject refers to the maximum number of tasks that all idle transport subjects can process. For example, assuming that each idle transport subject can only process s tasks in each transport process, s is an integer, then the task processing limit of k idle transport subjects is equal to s×k, and the task processing limit of the idle transport subject is denoted as m, and the set of idle transport subjects is denoted as I. The total number of transport tasks to be processed is denoted as n, and the set of transport tasks to be processed is denoted as J.

[0068] In a simple example, s=1, then m=k, that is, the task processing limit m of k idle transport entities is equal to the total number of idle transport entities.

[0069] According to an embodiment of the present disclosure, the idle transport subject includes: a transport robot in an idle state, which is an autonomous mobile robot based on real-time positioning and map building technology. The map of the transport robot is marked with the physical location of the exit and destination storage location corresponding to the transport task to be processed, or the physical location of the initial storage location and the entrance corresponding to the transport task to be processed, referring to Figure 1A As shown in the example of the transfer robot 121.

[0070] According to another embodiment of the present disclosure, the idle transporting body includes: a manually operated transporting device, the transporting device has a navigation and positioning function and a communication function; or a human operator who operates the transporting device listens to instructions through a warehouse outbound control software installed in a mobile device to perform operations, the warehouse outbound control software has a navigation and positioning function and a communication function, Figure 1A The manually operated handling equipment 122 is shown in the example.

[0071] When the task processing limit value is less than the total number, that is, when m<n, operations S230a and S240a are performed.

[0072] In operation S230a, the processing priority corresponding to each of the to-be-processed transport tasks is determined according to the similarity between the first task path vector of the to-be-processed transport task and the second task path vector of the transport task in the processing state.

[0073] The element values ​​in the task path vector are the task passing values ​​corresponding to the starting position and ending position of each transport path of the transport tasks to be processed and the transport tasks in the processing state (which can also be described as being processed). For example, all the starting positions (starting points) and ending positions (end points) in the transport path are numbered, corresponding to the sequence numbers of the elements in the task path vector, and the values ​​corresponding to the tasks passing at these positions are used as element values.

[0074] According to an embodiment of the present disclosure, the elements in the first task path vector of the above-mentioned handling task to be processed include: the task values ​​of the starting position and the ending position of each handling path of the handling task passed by the planned path of the handling task to be processed; the above-mentioned handling task includes the above-mentioned handling task to be processed and the above-mentioned handling task in the processing state; the elements in the second task path vector of the above-mentioned handling task in the processing state include: the task values ​​of the starting position and the ending position of each handling path of the above-mentioned handling task passed by the planned path of the handling task in the processing state.

[0075] When the specific starting position or the specific ending position has not been passed by the handling task to be processed, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned first task path vector is 0; when the specific starting position or the specific ending position is passed by the handling task to be processed, each time it is passed, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned first task path vector is increased by 1. When the specific starting position or the specific ending position has not been passed by the handling task in the processing state, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned second task path vector is 0; when the specific starting position or the specific ending position is passed by the handling task to be processed, each time it is passed, the element value corresponding to the above-mentioned specific starting position or the above-mentioned specific ending position in the above-mentioned second task path vector is increased by 1. The above-mentioned similarity includes cosine similarity.

[0076] For example, there are three pending transport tasks, namely, task R 1 ~R 3 , Task R 1 :Add item Ca 1 Transport from exit 1 to destination storage location B2, task R 2 :Add item Ca 2 Transport from exit 2 to destination storage location C1, task R 3 :Add item Ca 3From the outbound port 3 to the destination storage location C2; for example, there are three transport tasks being processed, namely, task R 4 、Task R 5 and Task R 6 , Task R 4 :Add item Ca 4 Transport from exit 1 to destination storage location B1, task R 5 :Add item Ca 5 Transport from exit 2 to destination storage location A1, task R 6 :Add item Ca 5 From the outbound port 2 to the destination storage location C1. Then all tasks R 1 ~R 6 There are 3 starting positions and 5 ending positions corresponding to the transportation path. The 3 starting positions are: exit 1, exit 2, and exit 3; the 5 ending positions are: destination storage location A1, destination storage locations B1 and B2, and destination storage locations C1 and C2.

[0077] The order of the elements is as follows: outbound port 1, outbound port 2, outbound port 3, destination storage location A1, destination storage location B1, destination storage location B2, destination storage location C1, destination storage location C2. For the pending transport task, task R 1 The corresponding first task path vector can be expressed as W 11 : [1, 0, 0, 0, 0, 1, 0, 0], task R 2 The corresponding first task path vector can be expressed as W 12 : [0, 1, 0, 0, 0, 0, 1, 0], task R 3 The corresponding first task path vector can be expressed as W 13 :[0, 0, 1, 0, 0, 0, 1]; for the handling task in the processing state, task R 4 ~R 6 The overall corresponding second task path vector can be expressed as W 2 :[1(There is a task R 4 After), 2 (there are two tasks R 5 and R 6 Pass), 0, 1 (there is a task R 5 Pass), 1(there is a task R 4 Pass), 0, 1 (there is a task R 6 In this paragraph, the content in brackets is used for explanation and understanding, and can actually be obtained according to the definition of the task path vector.

[0078] In operation S230a, according to the first task path vector W of each pending transport task, 11 , W 12, W 13 The second task path vector W of the handling task in the processing state 2 The similarity between them can determine the processing priority of each pending handling task.

[0079] In operation S240a, a target task to be processed that is adapted to the task processing limit value is determined from among the transport tasks to be processed according to the processing priority.

[0080] According to the processing priority, m target tasks to be processed are selected from n pending transport tasks, the number of which is equal to the task processing limit value, and the set of target tasks to be processed is recorded as J T , J T It is a subset of the set J of the handling tasks to be processed or is the same as the set J.

[0081] In operation S250, a target matching combination between the target to-be-processed task and the idle transporting entity is determined.

[0082] Task matching is performed between m target pending tasks and k idle transport entities, that is, each idle transport entity is matched with one or several target pending tasks, and the task matching relationship between all idle transport entities and the corresponding matched target pending tasks is the target matching combination. Assuming that each idle transport entity can only handle one task in each transport process, then m = k, and there are m! matching combinations in total, "m!" represents the factorial of m, m! = m×(m-1)×...2×1, and this operation selects one from the m! candidate matching relationships as the target matching combination. It can be understood that when each idle transport entity can handle s tasks in each transport process, m = k×s.

[0083] In operation S260, according to the target matching combination, the corresponding target to-be-processed task is sent to the idle transport entity.

[0084] Based on the above operations S210~S260, when the task processing limit value of the idle transport subject is less than the total number of the above-mentioned transport tasks to be processed, the processing priority corresponding to each transport task to be processed is determined according to the similarity between the first task path vector of the transport task to be processed and the second task path vector of the transport task in the processing state; according to the above-mentioned processing priority, the target transport task to be processed that is adapted to the above-mentioned task processing limit value is determined among the above-mentioned transport tasks to be processed; on the premise of meeting the task acceptance capacity as much as possible, it can help to stagger the routes corresponding to the ongoing tasks to avoid congestion in the transport paths; by sending the corresponding target tasks to be processed to the above-mentioned idle transport subjects according to the target matching combination, the transport subjects in the idle state and the corresponding tasks are matched, thereby improving the task processing efficiency.

[0085] Figure 3 A flowchart of a warehouse scheduling method provided by another embodiment of the present disclosure is schematically shown.

[0086] Reference Figure 3 As shown, the warehouse scheduling method provided in the embodiment of the present disclosure includes, in addition to the above-mentioned operations S210, S220, S230a, S240a, S250 and S260, also includes operation S230b.

[0087] When the task processing limit is greater than or equal to the total number, that is, when the result of S220 is "No", that is, when m≥n, operation S230b is performed to determine the pending transport task as the target pending task. In this embodiment, operation S250 is performed after operation S230b.

[0088] Figure 4 The detailed implementation flow chart of operation S230a of the embodiment of the present disclosure is schematically shown.

[0089] According to the embodiments of the present disclosure, referring to Figure 4 As shown, in the above operation S230a, the processing priority corresponding to each to-be-processed transport task is determined according to the similarity between the first task path vector of the to-be-processed transport task and the second task path vector of the transport task in the processing state, including the following operations: S410, S420 and S430.

[0090] In operation S410 , the similarity between the first task path vector of each to-be-processed transport task and the second task path vector of the transport task in the processing state is calculated.

[0091] In one embodiment, the similarity is cosine similarity.

[0092] The first task vector of the i-th pending handling task is expressed as: W 1i , referring to the task R described above 1 ~R 3 The first task path vector W corresponding to each 11 , W 12 , W 13 As shown, the second path vector of the handling task in the processing state is represented by W 2 , then the first task vector W of the i-th handling task to be processed 1i The second task path vector W of the handling task in the processing state 2 The similarity between 1i, W 2 ) satisfies the following expression:

[0093]

[0094] Among them, |||| represents the modulus of the vector, and · represents the dot product between vectors.

[0095] In operation S420, the similarities calculated for each of the to-be-processed transport tasks are sorted to obtain a sorting result.

[0096] In operation S430, according to the sorting result, it is determined that the lower the similarity, the higher the processing priority of the to-be-processed transport task corresponding to the to-be-processed transport task.

[0097] The smaller the similarity of the transportation paths between the pending transportation tasks and the ongoing tasks, the higher the priority they will be. On the premise of meeting the task acceptance capacity as much as possible, the routes corresponding to the ongoing tasks can be staggered for scheduling, avoiding congestion in the transportation paths and improving task processing efficiency.

[0098] Figure 5 The detailed implementation flowchart of operation S250 of the embodiment of the present disclosure is schematically shown.

[0099] According to an embodiment of the present disclosure, referring to Figure 5 As shown, the operation S250, determining the target matching combination between the target task to be processed and the idle transport subject, includes the following operations: S511 and S512.

[0100] In operation S511, the distance information required for each of the idle transport entities to execute each of the target tasks to be processed is determined.

[0101] According to an embodiment of the present disclosure, the distance information required for each of the above-mentioned idle transport entities to execute each of the above-mentioned target tasks to be processed is determined, including: according to the task execution path constructed by the above-mentioned idle transport entities in the navigation map, determining the distance information required for each of the above-mentioned idle transport entities from the current position to the execution starting point of the above-mentioned target tasks to be processed, and executing the above-mentioned target tasks based on the above-mentioned task execution path.

[0102] According to another embodiment of the present disclosure, the above-mentioned determination of the distance information required for each of the above-mentioned idle transport entities to execute each of the above-mentioned target tasks to be processed includes:

[0103] Determine whether there is a target obstacle in the straight line between the starting position and the ending position of the target task to be processed; for example, an obstacle whose size and location are sufficient to affect the execution of the task by the idle transport body is a target obstacle;

[0104] In the case where the target obstacle does not exist in the straight line, the distance from the idle transport body to the execution starting point of the target task to be processed and the Euclidean distance between the starting position and the ending position of the target task to be processed are added to obtain the required distance information;

[0105] In the case where the above-mentioned target obstacle exists in the above-mentioned straight route, according to the task execution path constructed by the above-mentioned idle transporting body in the navigation map, the distance information required for each above-mentioned idle transporting body to execute the above-mentioned target task to be processed from its current position is determined, and based on the above-mentioned task execution path, the distance information required to execute the above-mentioned target task to be processed is determined.

[0106] In operation S512, a target matching combination is determined according to the distance information, and the target matching combination minimizes the total distance required for all matched idle transport entities to execute the corresponding target tasks to be processed.

[0107] In this embodiment, based on the above operations S511 to S512, the matching relationship corresponding to the minimum total distance required for all idle transport entities to perform the target task to be processed is used as the target matching combination, which helps to improve the efficiency of each idle transport entity in performing the task.

[0108] Figure 6 The detailed implementation flow chart of operation S512 of the embodiment of the present disclosure is schematically shown.

[0109] According to another embodiment of the present disclosure, referring to Figure 6 As shown, in the above operation S512, the target matching combination is determined according to the above distance information, including the following operations: S611, S612a, S612b, S612c, S612d, S613.

[0110] In operation S611, based on the integer programming model, the minimum value of the total distance required for all idle transport entities under the candidate matching relationship to execute the corresponding target to-be-processed tasks is used as a linear programming target.

[0111] The linear programming objective is the objective function of the integer programming model. The linear programming objective can be expressed as the following expression:

[0112]

[0113] Among them, x ij represents the candidate matching relationship between the fth idle transport subject and the jth target to-be-processed task, x ij =1 means that the i-th idle transport entity is matched with the j-th target task to be processed; x ij =0 means that the i-th idle transport entity is not matched with the j-th target task to be processed; d ijrepresents the distance that the i-th idle transport agent performs the j-th target pending task; k represents the total number of idle transport agents; m represents the set of target pending tasks J T The total number of tasks in .

[0114] In operation S612a, the task processing limit value corresponding to each of the idle transport entities is used as a first constraint condition.

[0115] The first constraint can be expressed as:

[0116]

[0117] Where I represents the set of idle transport entities, and s represents the task processing limit value corresponding to each idle transport entity; It represents any meaning (a common symbol in mathematical analysis). For example, the above embodiment takes s=1 as an example, which means that an idle transport entity can only match one target task to be processed.

[0118] In operation S612b, the number of transport entities supported by each target task to be processed is used as the second constraint condition.

[0119] For example, if the number of transport entities supported by each target task to be processed is 1, the second constraint can be expressed as:

[0120]

[0121] Among them, J T Represents the set of target pending tasks, Formula (4) indicates that a target pending task can only be matched by an idle transport subject.

[0122] In operation S612c, the smaller of the sum of the values ​​of all candidate matching relationships corresponding to the task processing limit value of the idle transport entity and the total number of the transport tasks to be processed is used as the third constraint condition.

[0123] For example, the third constraint can be expressed as:

[0124]

[0125] In this embodiment, since m=sk, and m is smaller than n, min(sk, n)=m.

[0126] In operation S612d, the integer value corresponding to the candidate matching relationship is used as the fourth constraint condition.

[0127] The fourth constraint can be expressed as:

[0128]

[0129] Referring to the description of formula (2), x ij =1 means that the i-th idle transport entity is matched with the j-th target task to be processed; x ij =0 indicates that the i-th idle transport entity is not matched with the j-th target task to be processed.

[0130] In operation S613, under the constraints of the first constraint, the second constraint, the third constraint and the fourth constraint, the optimal solution of the matching relationship corresponding to the linear programming objective is solved, and the optimal solution of the matching relationship is used as the objective matching combination.

[0131] The embodiment of the present disclosure provides a method for data processing. The method for data processing of the embodiment can be executed by the library management device 140 in the system architecture 100 .

[0132] Figure 7 The flowchart of the data processing method provided by the embodiment of the present disclosure is schematically shown.

[0133] Reference Figure 7 As shown in the solid line frame, the data processing method provided by the embodiment of the present disclosure includes the following operations: S710, S720, S730 and S740a.

[0134] In operation S710, item in-and-out information is obtained, wherein the item in-and-out information includes one or more items of item out-of-warehouse requirement information and item in-warehouse requirement information.

[0135] In operation S720, a transport task is generated according to the above-mentioned information on the entry and exit of the goods. The above-mentioned transport task includes one or more of an outbound transport task and an inbound transport task.

[0136] In operation S730, it is detected whether the intelligent transport switch is in an on state.

[0137] When the intelligent transport switch is in the on state, operation S740a is performed to send the transport task to the warehouse scheduling device, so that the warehouse scheduling device executes the warehouse scheduling method as described above.

[0138] According to the embodiments of the present disclosure, referring to Figure 7 As shown in the dotted box, the data processing method further includes operation S740b, in which, when the intelligent transport switch is in the off state, the transport task is sent to the display screen for display, and the prompt device is controlled to issue a prompt to the manually operated transport device.

[0139] In the embodiment of the present disclosure, in the vertical warehouse, each conveyor line outlet is equipped with a large display screen, which displays the warehouse task information: outlet number, pallet number, task type, destination flow (different physical areas divided according to different business types on site), and an audio-visual device (an example of a prompt device) is configured next to the display screen. Figure 1B As shown, in the outbound state, whenever the main conveyor line 114 delivers the pallet to the outbound port 115 (the corresponding port in the inbound state), the outbound task information will be sent to the display screen for display, and the sound and light equipment will be turned on to remind the forklift driver that there is an outbound transportation task. The forklift driver will transport the pallet to the destination point according to the content displayed on the large screen, and independently select a free storage location to put it down. After the photoelectric equipment configured at the outbound port detects that the pallet has been moved away, it will clear the content displayed on the large screen and turn off the sound and light equipment.

[0140] Based on the setting of the intelligent handling switch, it can be decided in a modular manner whether to use a handling robot (such as a forklift robot) or improved handling equipment for handling. If the handling robot fails or there are other situations that are not convenient for automated handling, the intelligent handling switch can be turned off and handling can be carried out by manually operating the handling equipment (such as an ordinary manually operated forklift).

[0141] The third exemplary embodiment of the present disclosure also provides a method for handling operations. The method of this embodiment can be performed by the handling robot 121 or the improved manually controlled handling equipment 122 in the system architecture 100, and the detailed description of the first embodiment can be referred to, which will not be repeated here.

[0142] Figure 8 A flow chart schematically shows a method for handling operations provided by an embodiment of the present disclosure.

[0143] Reference Figure 8 As shown, the method of handling operations provided by the embodiment of the present disclosure includes the following operations: S810, S820, S830 and S840.

[0144] In operation S810, a target task to be processed sent by a warehouse scheduling device is received.

[0145] In operation S820, based on the information of the starting position and the ending position of the target task to be processed, the physical positions corresponding to the starting position and the ending position are marked in the navigation map.

[0146] In operation S830 , a task execution path is constructed according to the physical locations corresponding to the marked start and end locations.

[0147] In operation S840, the target to-be-processed task is executed based on the task execution path.

[0148] Taking the transport robot 121 as an example of the execution subject, when executing the target pending task, the transport robot 121 changes the status of the destination storage location (corresponding to the end position of the task) in the destination flow area to pre-occupied, and after transporting the pallet at the exit corresponding to the start position of the task to the destination storage location, changes the status of the destination storage location to occupied.

[0149] If the destination storage location pallet is moved away by the subsequent outbound process, the handling robot 121 can release the occupied destination storage location in the destination flow management interface and change the status of the destination storage location to free. It can also be released by scanning the storage location barcode with a handheld device. The status of the destination storage location can be shared between the storage scheduling device 150 and the handling robot 121.

[0150] A fourth exemplary embodiment of the present disclosure provides a warehouse scheduling device.

[0151] Fig. 9 The structural block diagram of the warehouse scheduling device provided by the embodiment of the present disclosure is schematically shown.

[0152] Reference Fig. 9 As shown, the warehouse scheduling device 900 provided by the embodiment of the present disclosure includes: a task acquisition module 910, a processing limit determination module 920, a task priority determination module 930, a priority task determination module 940, a matching combination determination module 950 and a first communication module 960.

[0153] The task acquisition module 910 is used to acquire the transport tasks to be processed.

[0154] The processing limit determination module 920 is used to determine whether the task processing limit value of the idle transporting subject is less than the total number of the transporting tasks to be processed.

[0155] The task priority determination module 930 is used to determine the processing priority corresponding to each pending transport task according to the similarity between the first task path vector of the pending transport task and the second task path vector of the transport task in the processing state when the task processing limit value is less than the total number.

[0156] The priority task determination module 940 is used to determine the target to-be-processed task that is adapted to the task processing limit value among the to-be-processed transport tasks according to the processing priority.

[0157] The matching combination determination module 950 is used to determine the target matching combination between the target to-be-processed task and the idle transport subject.

[0158] The first communication module 960 is used to send the corresponding target to-be-processed tasks to the idle transport entity according to the target matching combination.

[0159] Each functional module in this embodiment may further include a submodule for implementing the corresponding operation of the first embodiment.

[0160] A fifth exemplary embodiment of the present disclosure provides a vertical warehouse management device.

[0161] Fig.10 The structural block diagram of the vertical library management device provided by the embodiment of the present disclosure is schematically shown.

[0162] Reference Fig.10 As shown, the vertical warehouse management device 1000 provided in the embodiment of the present disclosure includes: an in-and-out warehouse information acquisition module 1010 , a task generation module 1020 , a detection module 1030 and a second communication module 1040 .

[0163] The above-mentioned in-and-out information acquisition module 1010 is used to obtain the in-and-out information of items, and the above-mentioned in-and-out information of items includes one or more of the information of item out-of-warehouse requirement and the information of item in-warehouse requirement.

[0164] The task generation module 1020 is used to generate a transport task according to the in-and-out information of the items, and the transport task includes one or more of an out-of-warehouse transport task and an in-warehouse transport task.

[0165] The detection module 1030 is used to detect whether the intelligent transport switch is in an on state.

[0166] The second communication module 1040 is used to send the transport task to the warehouse scheduling device when the intelligent transport switch is in the on state.

[0167] According to an embodiment of the present disclosure, the second communication module 1040 is also used to send the transport task to the display screen for display when the intelligent transport switch is in the off state, and control the prompt device to issue a prompt to the manually operated transport device.

[0168] A sixth exemplary embodiment of the present disclosure provides a transport device.

[0169] Fig.11 The structural block diagram of the transport equipment provided by the embodiment of the present disclosure is schematically shown.

[0170] Reference Fig.11 As shown, the transport device 1100 provided in the embodiment of the present disclosure includes: a task receiving module 1110 , a position marking module 1120 , a path building module 1130 and a transport module 1140 .

[0171] The task receiving module 1110 is used to receive the target to-be-processed tasks sent by the storage scheduling device.

[0172] The position marking module 1120 is used to mark the physical positions corresponding to the start position and the end position in the navigation map according to the information of the start position and the end position of the target task to be processed.

[0173] The path construction module 1130 is used to construct a task execution path according to the physical locations corresponding to the marked start and end locations.

[0174] The transport module 1140 is used to execute the target task to be processed according to the task execution path.

[0175] Any multiple of the functional modules mentioned in the storage scheduling device, the vertical warehouse management device and the handling equipment of the above-mentioned embodiments can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. At least one of the functional modules mentioned in the storage scheduling device, the vertical warehouse management device and the handling equipment can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the functional modules mentioned in the storage scheduling device, the vertical warehouse management device and the handling equipment can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0176] A seventh exemplary embodiment of the present disclosure provides an electronic device.

[0177] Fig.12 The structural block diagram of the electronic device provided by the embodiment of the present disclosure is schematically shown.

[0178] Reference Fig.12As shown, the electronic device 1200 provided in the embodiment of the present disclosure includes a processor 1201, a communication interface 1202, a memory 1203 and a communication bus 1204, wherein the processor 1201, the communication interface 1202 and the memory 1203 communicate with each other through the communication bus 1204; the memory 1203 is used to store computer programs; the processor 1201 is used to implement the warehouse scheduling method, data processing method or handling operation method as described above when executing the program stored in the memory.

[0179] The eighth exemplary embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned storage scheduling method, data processing method or handling operation method.

[0180] The computer-readable storage medium may be included in the device / apparatus described in the above embodiment; or it may exist independently without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0181] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0182] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0183] The foregoing is merely a specific embodiment of the present disclosure, which enables those skilled in the art to understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features applied herein.

Claims

1. A method for warehouse scheduling, characterized in that: include: Get pending transport tasks; Determine whether the task processing limit value of the idle transport subject is less than the total number of the transport tasks to be processed; In the case where the task processing limit value is less than the total number, the processing priority corresponding to each handling task to be processed is determined according to the similarity between the first task path vector of the handling task to be processed and the second task path vector of the handling task in the processing state; wherein the similarity between the first task path vector and the second task path vector represents the degree of overlap between the routes corresponding to the handling task to be processed and the handling task in the processing state; the lower the similarity value, the higher the processing priority of the corresponding handling task to be processed; According to the processing priority, determining a target task to be processed that is adapted to the task processing limit value among the handling tasks to be processed; Determine a target matching combination between the target task to be processed and the idle transport subject; and According to the target matching combination, the corresponding target to-be-processed task is sent to the idle transport entity.

2. The method according to claim 1, characterized in that The determining the processing priority corresponding to each to-be-processed transport task according to the similarity between the first task path vector of the to-be-processed transport task and the second task path vector of the transport task in the processing state comprises: Calculate the similarity between the first task path vector of each to-be-processed handling task and the second task path vector of the handling task in the processing state; Sorting the similarities calculated for each pending handling task to obtain a sorting result; According to the sorting result, it is determined that the lower the similarity, the higher the processing priority of the corresponding pending transport task.

3. The method according to claim 1 or 2, characterized in that: The elements in the first task path vector of the handling task to be processed include: the starting position and the ending position of each handling path of the handling task are passed by the planned path of the handling task to be processed; the handling task includes the handling task to be processed and the handling task in the processing state; The elements in the second task path vector of the handling task in the processing state include: the starting position and the ending position of each handling path of the handling task are passed by the planned path of the handling task in the processing state.

4. The method according to claim 3, characterized in that When the specific starting position or the specific ending position is not passed by the to-be-processed transport task, the element value corresponding to the specific starting position or the specific ending position in the first task path vector is 0; when the specific starting position or the specific ending position is passed by the to-be-processed transport task, each time it is passed, the element value corresponding to the specific starting position or the specific ending position in the first task path vector is increased by 1; When the specific starting position or the specific ending position is not passed by the handling task in the processing state, the element value corresponding to the specific starting position or the specific ending position in the second task path vector is 0; when the specific starting position or the specific ending position is passed by the handling task to be processed, each time it is passed, the element value corresponding to the specific starting position or the specific ending position in the second task path vector is increased by 1; The similarity includes cosine similarity.

5. The method according to claim 1, characterized in that Also includes: When the task processing limit value is greater than or equal to the total number, the to-be-processed transport task is determined as the target to-be-processed task.

6. The method according to claim 1 or 5, characterized in that: The determining of a target matching combination between the target task to be processed and the idle transport subject includes: Determine the distance information required for each of the idle transport entities to execute each of the target tasks to be processed; A target matching combination is determined according to the distance information, wherein the target matching combination minimizes the total distance required for all matched idle transport entities to execute corresponding target tasks to be processed.

7. The method according to claim 6, characterized in that Determining a target matching combination according to the distance information includes: Based on the integer programming model, the minimum total distance required for all idle transport entities under the candidate matching relationship to execute the corresponding target pending tasks is taken as the linear programming goal; Taking the task processing limit value corresponding to each of the idle transport entities as the first constraint condition; The number of transport entities supported by each target task to be processed is used as the second constraint condition; The smaller of the sum of the values ​​of all candidate matching relationships corresponding to the task processing limit value of the idle transport entity and the total number of the transport tasks to be processed is used as the third constraint condition; Taking the integer value corresponding to the candidate matching relationship as the fourth constraint condition; Under the constraints of the first constraint condition, the second constraint condition, the third constraint condition and the fourth constraint condition, the optimal solution of the matching relationship corresponding to the linear programming objective is solved, and the optimal solution of the matching relationship is used as the objective matching combination.

8. The method according to claim 6, characterized in that The determining of the distance information required for each idle transport entity to execute each target task to be processed includes: According to the task execution path constructed by the idle transport body in the navigation map, the distance information required for each idle transport body from its current position to the execution starting point of the target task to be processed is determined, and the distance information required for executing the target task to be processed based on the task execution path is determined.

9. The method according to claim 6, characterized in that The determining of the distance information required for each idle transport entity to execute each target task to be processed includes: Determine whether there is a target obstacle in the straight line between the starting position and the ending position of the target task to be processed; In the case where the target obstacle does not exist in the straight route, the distance from the idle transport body to the execution starting point of the target task to be processed is added to the Euclidean distance between the start position and the end position of the target task to be processed to obtain the required distance information; In the case where the target obstacle exists in the straight route, the distance information required for each idle transport body to execute the target task to be processed from its current position to the execution starting point of the target task to be processed is determined according to the task execution path constructed by the idle transport body in the navigation map, and based on the task execution path, the distance information required for each idle transport body to execute the target task to be processed is determined.

10. The method according to claim 1, characterized in that The obtaining of the pending handling tasks includes: Receive the transport task sent by the vertical warehouse management device, and put the transport task into the task pool; the transport task includes one or more of the outbound transport task and the inbound transport task; Obtain the pending transport tasks from the task pool.

11. The method according to claim 1, characterized in that: The idle transport body comprises: A transport robot in an idle state, wherein the transport robot is an autonomous mobile robot based on real-time positioning and map building technology, and the physical locations of the exit and destination storage locations corresponding to the pending transport task are marked in the navigation map of the transport robot, or the physical locations of the initial storage location and entry corresponding to the pending transport task are marked; or Manually operated handling equipment, the handling equipment having navigation, positioning and communication functions; or the manual operator who operates the handling equipment listens to instructions through the outbound control software installed in the mobile device to perform the operation, the outbound control software having navigation, positioning and communication functions.

12. A storage scheduling device, characterized in that: include: Task acquisition module, used to obtain pending handling tasks; A processing limit determination module, used to determine whether the task processing limit value of the idle transport subject is less than the total number of the transport tasks to be processed; A task priority determination module is used to determine the processing priority corresponding to each to-be-processed transport task according to the similarity between the first task path vector of the to-be-processed transport task and the second task path vector of the transport task in the processing state when the task processing limit value is less than the total number; the similarity between the first task path vector and the second task path vector represents the degree of overlap between the routes corresponding to the to-be-processed transport task and the transport task in the processing state; the lower the similarity value, the higher the processing priority of the corresponding to-be-processed transport task; A priority task determination module, used to determine a target task to be processed that is adapted to the task processing limit value among the handling tasks to be processed according to the processing priority; A matching combination determination module, used to determine a target matching combination between the target to-be-processed task and the idle transport subject; as well as The first communication module is used to send the corresponding target to-be-processed task to the idle transport entity according to the target matching combination.

13. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; A processor, for implementing the method according to any one of claims 1 to 11 when executing a program stored in a memory.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

Images