JP7066029B1 - Warehouse system control methods, appliances, equipment and computer readable storage media - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a control method of a warehouse system capable of increasing the efficiency of a cargo issuing task in a warehouse. The present application relates to a control method, an apparatus, an equipment, and a computer-readable storage medium of a warehouse system. Here, the method determines a target station based on the cargo information of the task waiting to be assigned, determines candidate bins based on the cargo information of each current bin and the cargo information of the task waiting to be assigned, and determines each candidate. The candidate bin with the lowest transfer cost is determined from the bin as the target bin, the target robot is determined based on the position information of the target bin, and the target robot is controlled to transport the target bin to the target station. Including that. [Selection diagram] Fig. 1

Description

This application was filed with the China Patent Office on November 6, 2020, and is a Chinese patent application whose application number is 201201123268 and whose invention name is "control method, device, equipment and computer readable storage medium of warehouse system". It claims priority and is incorporated herein by reference in its entirety. This application was filed with the Chinese Patent Office on December 4, 2020, and the application number is 20120140115883, and the invention name is "control method, device, equipment and computer readable storage medium of warehouse system". It claims priority and is incorporated herein by reference in its entirety. This application was filed with the China Patent Office on December 4, 2020, and is a Chinese patent application whose application number is 2011140445470 and whose invention name is "control method, device, equipment and computer readable storage medium of warehouse system". It claims priority and is incorporated herein by reference in its entirety. In addition, this application was submitted to the China Patent Office on December 4, 2020, and the application number is 201201404521, and the invention name is "control method, device, equipment and computer readable storage medium of warehouse system". Claims the priority of the application, which is incorporated herein by reference in its entirety.

The present application relates to the field of warehouse technology, in particular relating to methods of controlling warehouse systems, appliances, equipment and computer readable storage media.

In a related technique, a warehouse system typically uses a transfer robot to automatically transfer bins (container boxes) on a rack to a station to complete a shipping task. However, it is difficult to guarantee the efficiency of the shipping task because the shipping task involves many factors such as bin selection, station selection, and robot selection.

Embodiments of the present application provide control methods, devices, equipment, and computer-readable storage media for warehouse systems to solve one or more technical issues in related art.

In order to achieve the above objectives, this application adopts the following technical proposals.

A first aspect of the present application provides a method of controlling a warehouse system. The control method of the warehouse system is to determine the target station based on the cargo information of the task waiting to be allocated, and to determine the candidate bin based on the cargo information of each current bin and the cargo information of the task waiting to be allocated. Then, the candidate bin having the lowest transfer cost is selected as the target bin from each of the candidate bins, the target robot is determined based on the position information of the target bin, and the target bin is transported to the target station. Includes controlling the target robot to do so.

In one embodiment, determining a target station based on the cargo information of the awaiting task is based on the number of storage spaces to be occupied by the awaiting task and the number of free storage spaces in each station. Determining a candidate station, the cargo information of bins assigned to the candidate station, the distance between each bin and the candidate station, the cargo information of bins not yet assigned to the candidate station, and the task waiting for allocation. It includes calculating the allocation efficiency value of each candidate station based on the remaining cargo information, and determining the candidate station having the largest allocation efficiency value as the target station.

In one embodiment, determining the candidate bin with the lowest transport cost from each candidate bin as the target bin is based on the cargo information of the pending task and the cargo information of the bin allocated to the target station. Determining the remaining cargo information of the awaiting task, and determining a bin that satisfies the remaining freight information of the awaiting task as a candidate bin based on the freight information of each of the current bins. This includes calculating the transport cost of the candidate bins and determining the candidate bin with the lowest transport cost as the target bin.

In one embodiment, the robot includes a first robot, and determining the target robot based on the position information of the target bin corresponds to the target bin based on the position information of the target bin. The first target robot includes the target bin, the storage space, including the determination of the target passage and the determination of the first target robot based on the position of each of the first robots in the target passage. It is used to transport from to the temporary storage space.

In one embodiment, the robot includes a second robot, and determining the target robot based on the position information of the target bin is a distance from the target bin based on the position information of the target bin. Further includes determining the closest second robot as the second target robot, the second target robot being used to transport the target bin from the temporary storage space to the target station.

In one embodiment, after controlling the target robot to transport the target bin to the target station, the method controls the second target robot to transport the target bin from the target station to the target rack. Further including controlling the second target robot to stay under the empty temporary storage space of the storage rack.

A second aspect of the present application provides a method of controlling a warehouse system. The control method of the warehouse system is to select the vacant first robot as the matching waiting first robot and to select the passage where the target bin is located as the matching waiting passage based on the position information of the target bin. Based on the fact that, for each of the matching waiting first robots, the distance between the matching waiting first robot and each matching waiting passage, and the number of assignment waiting tasks of each matching waiting passage. , Determining the corresponding target passage and the first target robot, and assigning the task of waiting for allocation of the target passage to the corresponding first target robot.

In one embodiment, selecting the passage where the target bin is located as the matching waiting passage means selecting the passage in which the allocation waiting task exists and the first robot does not exist as the first matching waiting passage. When the number of the first matching waiting passages is smaller than the number of the matching waiting first robots, the passage in which the allocation waiting task exists and the first robot exists is selected as the second matching waiting passage. include.

In one embodiment, assigning the task waiting for allocation of the target passage to the corresponding first target robot is to calculate the number of assignable tasks of the target passage and the number of assignable tasks. When it is larger than 0, the corresponding number of work areas is divided in the target passage based on the number of the first target robots, and the number of assigned tasks is less than the upper limit threshold of the tasks. Is selected as the first robot waiting for allocation, the distance between the first robot waiting for allocation and the target bin corresponding to each assignable task, and the first robot waiting for allocation can be assigned. Includes determining a target task from the assignable tasks and assigning it to the corresponding first task awaiting allocation, based on the number of work areas passed to move to the target bin corresponding to the task. ..

In one embodiment, calculating the number of assignable tasks in the target passage is the minimum of the number of allocation waiting tasks and the number of empty temporary storage spaces in the target passage, and the allocation of the target passage. All from the value obtained by adding the minimum value of the number of waiting tasks and the number of free storage spaces to obtain the first reference value, and the value obtained by multiplying the number of the matched first robots by the upper limit threshold value of the task. The second reference value is obtained by subtracting the total number of assigned tasks of the matched first robot, and the minimum value of the first reference value and the second reference value is assigned to the target passage. Includes selecting as the number of possible tasks.

A third aspect of the present application provides a method of controlling a warehouse system that includes a plurality of warehouse areas. The control method of the warehouse system is to determine the import warehouse area and the export warehouse area from the plurality of initial warehouse areas based on the number of tasks waiting to be allocated in each initial warehouse area and the current number of second robots. And, the export second robot in each of the export warehouse areas is determined, the import second robot in each of the import warehouse areas is determined from each of the export second robots, and the import second robot is used as the export warehouse area. The second target robot corresponding to each target bin in the matching waiting warehouse area is determined from the empty second robot in the matching waiting warehouse area for each matching waiting warehouse area. Including to do.

In one embodiment, determining an import warehouse area and an export warehouse area from a plurality of the initial warehouse areas based on the number of tasks waiting to be allocated in each initial warehouse area and the current number of second robots is described above. When the current number of second robots in the initial warehouse area is less than the allocated number of second robots in the initial warehouse area, the initial warehouse area is determined as the import warehouse area and the current number in the initial warehouse area is determined. When the number of the second robots is larger than the allocated number of the second robots in the initial warehouse area, the initial warehouse area is determined as the export warehouse area, and here, the second robot in the initial warehouse area is determined. The number of robots allocated is the product of the ratio of the number of unfinished tasks in the initial warehouse area to the total number of unfinished tasks in the warehouse system and the total number of second robots in the warehouse system.

In one embodiment, determining the export second robot in each export warehouse area is determined by determining the current number of second robots in the export warehouse area, the lower limit of the number of second robots, the number of second robots allocated, and so on. And, the number of the second robots in the export warehouse area is calculated based on the number of empty second robots, and the number of the second robots in the export warehouse area is calculated based on the number of the second robots in the export warehouse area. 2 Includes determining the robot.

In one embodiment, determining the transfer second robot in each transfer warehouse area from each transfer second robot is the allocation number of the second robots in the transfer warehouse area, the current number of second robots, and the second. The number of the second robots in the import warehouse area is calculated based on the upper limit of the number of robots, and the second robot in the import warehouse area with respect to the total number of the second robots in the import warehouse area. The product of the ratio of the number of migrants and the total number of migrants of the second robot in each of the migrant warehouse areas is calculated as a reference value, and the reference value and the number of migrants of the second robot in the migrant warehouse area are calculated. The minimum value among them is determined as the actual number of demands of the second robot in the transfer warehouse area, and according to the actual demand number of the second robot in the transfer warehouse area from the transfer second robot in each transfer warehouse area. This includes selecting the export second robot having the shortest distance from the import warehouse area as the import second robot in the import warehouse area.

In one embodiment, determining the corresponding second target robot of each target bin in the matching waiting warehouse area from the vacant second robot in the matching waiting warehouse area is a type of task waiting to be allocated in the matching waiting warehouse area. The second target robot corresponding to each station is determined from the vacant second robot in the matching waiting warehouse area based on the number of tasks waiting to be assigned, and the task waiting to be assigned to the station corresponds to the station. Includes matching with the second target robot.

In one embodiment, a second target robot corresponding to each station is determined from the vacant second robot in the matching waiting warehouse area based on the type of the allocation waiting task in the matching waiting warehouse area and the number of allocation waiting tasks. That is, for each type of task waiting for allocation, the ratio of the number of tasks waiting for allocation to the total number of tasks waiting for allocation, the fixed weight of the type of task waiting for allocation, and the type of task waiting for allocation. Based on the initial fluctuation weight, the first fluctuation weight of the allocation waiting task type is calculated, and one of the vacant second robots in the matching waiting warehouse area is set as the second target robot. 1 Assigning to the station corresponding to the type of task waiting for allocation with the highest variable weight, and the ratio of the number of tasks waiting for allocation to the total number of tasks waiting for allocation for each type of task waiting for allocation. Calculation of the second variable weight of the type of the task waiting for allocation based on the fixed weight of the type of the task waiting for allocation and the first variable weight of the type of the task waiting for allocation, and the allocation of the empty second robot. When both the number of waits and the number of tasks waiting for allocation are larger than 0, the first variable weight calculation step, the second target robot allocation step, and the second variable weight calculation step are circulated. , The second variable weight of the type of the task waiting for allocation is set as the initial variable weight of the type of the task waiting for allocation.

In one embodiment, matching a task waiting to be assigned to the station with a second target robot corresponding to the station is a priority of the task waiting to be assigned to the station and a target bin and station corresponding to the task waiting to be assigned. Based on the distance between and, the allocation value of each allocation waiting task is calculated, and based on the number of the second target robots in the station, the number of correspondences with the highest allocation value from the allocation waiting task. Each target task is extracted as a target task, and each target task is based on the distance between the second target robot and the target bin corresponding to each target task for each target robot. The matching value of the second target robot that matches with the second target robot is calculated, and the target task having the highest matching value is selected to match the second target robot.

According to the above-mentioned technical proposal, at least the following advantages or beneficial effects can be obtained. That is, by selecting the bin with the highest transfer efficiency from the storage rack to the target station as the target bin from a plurality of candidate bins, the transfer time for the target robot to transfer the target bin to the target station is shortened. In addition, the number of times the target robot can be transported can be shortened, and the efficiency of shipping cargo can be further improved.

The above overview is for the purposes of the specification only and is not intended to be restricted in any way. In addition to the exemplary embodiments, embodiments, and features described above, further embodiments, embodiments, and features herein are readily understood by reference to the accompanying drawings and the detailed description below. There will be.

In order to more clearly explain the technical proposals in the embodiments or related techniques of the present application, the necessary attachments used in the description of the embodiments or related techniques will be briefly described below, but the attachments in the following description. The drawings are only some of the embodiments described in the embodiments of the present application, and it is clear to those skilled in the art that other attachments can be obtained from these attachments.
It is a flowchart of the control method of the warehouse system by 1st Embodiment of this application. It is a specific flowchart for determining the import warehouse area and the export warehouse area according to the first embodiment of this application. It is a specific flowchart for determining an export robot according to 1st Embodiment of this application. It is a concrete flowchart for deciding the transfer robot by 1st Embodiment of this application. It is a flowchart of the control method of the warehouse system by 1st Embodiment of this application. It is a concrete flowchart for determining the target robot by 1st Embodiment of this application. Is a flowchart of the control method of the warehouse system according to the second embodiment of the present application. It is a specific flowchart for selecting a matching waiting passage by the 2nd Embodiment of this application. It is a concrete flowchart which assigns a target task according to 2nd Embodiment of this application. It is a specific flowchart for calculating the number of tasks which can be assigned according to the 2nd Embodiment of this application. It is a flowchart of the control method of the warehouse system by the 3rd Embodiment of this application. It is a specific flow chart for determining the import warehouse area and the export warehouse area according to the third embodiment of this application. It is a specific flowchart for determining the export 2nd robot according to 3rd Embodiment of this application. It is a specific flowchart for determining the transfer 2nd robot according to 3rd Embodiment of this application. It is a specific flow chart for matching the task waiting for allocation according to the 3rd Embodiment of this application. It is a specific flowchart for assigning the 2nd target robot according to 3rd Embodiment of this application. Is a specific flowchart for matching the target task according to the third embodiment of the present application. It is a schematic diagram of the control device of the warehouse system according to 4th Embodiment of this application. It is a schematic diagram of the control device of the warehouse system according to the 5th Embodiment of this application. It is a schematic diagram of the control device of the warehouse system according to the 6th Embodiment of this application. It is a schematic diagram of the electronic equipment by 7th Embodiment of this application. It is a specific flow chart for matching the task waiting for assignment with the target robot according to the embodiment of the first aspect of this application.

In the following, only some exemplary embodiments will be briefly described. As will be appreciated by those skilled in the art, the described embodiments may be modified in a variety of different ways without departing from the spirit or scope of the present application. Therefore, the accompanying drawings and description are considered to be non-limiting, but essentially exemplary.

Hereinafter, a method of controlling a warehouse system according to the first embodiment of the present application will be described with reference to FIGS. 1 to 6. The method of controlling the warehouse system according to the embodiment of the present application can be applied to the warehouse system and is used to realize the cargo unloading task of the warehouse system.

FIG. 1 is a flowchart showing a control method of a warehouse system according to an embodiment of the present application.

As shown in FIG. 1, the control method of the warehouse system can include the following.

In step S101, the target station is determined based on the cargo information of the task waiting for allocation.

In step S102, candidate bins are determined based on the cargo information of each current bin and the cargo information of the task waiting for allocation, and the candidate bin with the lowest transportation cost is selected as the target bin from each candidate bin.

In step S103, the target robot is determined based on the position information of the target bin.

In step S104, the target robot is controlled so as to transport the target bin to the target station.

In one example, the task awaiting allocation may include multiple job lists, and the cargo information for the task awaiting allocation may be the type and quantity of target cargo corresponding to each job list. The target station is used by the worker to sort the target cargo corresponding to the job list from the target bin. The number of stations may be plural, and one of them can be used as a target station for one task waiting for allocation, and can also be used as a target station for a task waiting for allocation. Here, the target station is the candidate station having the highest allocation efficiency value.

In one example, the bin is used to store cargo and the current bin may be a bin placed in a storage rack. Based on the cargo information for each current bin, select the current bin that at least partially matches the cargo information for the pending assignment task as a candidate bin. The transportation cost of the candidate bin can be calculated based on the distance between the candidate bin and the target station and the number of cargoes contained in the candidate bin that match the target cargo of the awaiting task. ..

It can be understood that the transport cost of the candidate bin is proportional to the distance between the candidate bin and the target station, that is, the smaller the distance between the candidate bin and the target station, the lower the transport cost of the candidate bin. In addition, the transportation cost of the candidate bin is inversely proportional to the number of cargoes in which the cargo contained in the candidate bin matches the target cargo of the task waiting for allocation, that is, the cargo contained in the candidate bin is waiting for allocation. The greater the number of cargoes that match the task's target cargo, the lower the cost of transporting the candidate bin.

In one example, the position information of the target bin may be the position information of the storage rack in which the target bin is located. The robot may be an Automated Guided Vehicle (AGV), and the transfer robot can travel along a predetermined navigation path to transport the bin between the station and the storage rack. The target robot can be specifically determined based on the position information of the storage rack in which the target bin is located.

After the target station, target bin, and target robot are determined, a bin transfer task is generated and sent to the target robot so that the target robot transports the target bin from the storage rack where the target bin is located to the target station. Is controlled by.

In the embodiment of the present application, the robot of the warehouse system includes the first robot and the second robot, and can simultaneously transmit the bin transfer task to the first target robot and the second target robot. Here, in order to accomplish the bin delivery task, the first target robot is used to transport the target bin from the target storage space of the rack to the target temporary storage space, and the second target robot is the target temporary storage space. Used to transport the target bin from to the target station.

Here, the selection of the first target robot and the assignment of tasks can be realized according to the control method of the warehouse system according to the second embodiment of the present application, and the selection of the second target robot and the assignment of tasks of the present application. It can be realized according to the control method of the warehouse system according to the third embodiment.

In the control method of the warehouse system according to the present embodiment, candidate bins are determined based on the cargo information of the bins and the cargo information of the task waiting for allocation, and the candidate bin having the lowest transportation cost is determined as the candidate bin from each candidate bin. For example, the transportation cost of each candidate bin is calculated by combining two factors, the distance between the candidate bin and the target station and the number of cargoes for which the candidate bin matches the cargo information of the task waiting to be allocated. The candidate bin with the lowest transport cost can be selected as the target bin. This makes it possible to select the bin with the highest transfer efficiency from multiple candidate bins, which is transported from the storage rack to the target station, as the target bin, and the transfer time for the target robot to transport the target bin to the target station. It is possible to reduce the number of transports of the target robot, and it is possible to improve the efficiency of cargo delivery.

In one embodiment, as shown in FIG. 2, step S101 includes the following steps.

In step S201, a candidate station is determined based on the number of storage spaces to be occupied by the task waiting to be allocated and the number of free storage spaces in each station.

In step S202, based on the cargo information of the bins assigned to the candidate stations, the distance between each bin and the candidate stations, the cargo information of the bins not yet assigned to the candidate stations, and the remaining cargo information of the task waiting to be assigned. , Calculate the allocation efficiency value of each candidate station.

In step S203, the candidate station having the largest allocation efficiency value is determined as the target station.

In one example, the station is provided with a sorting rack with multiple storage spaces for loading target cargo sorted from the target bin. The number of storage spaces to be occupied can be determined according to the number and type of target cargo of the task waiting to be allocated, and specifically, can be determined according to the number of job lists of the task waiting to be allocated. Here, the target cargo required for each job list corresponds to one storage space to be occupied. That is, the number of storage spaces to occupy is equal to the number of job lists for tasks waiting to be allocated. By selecting a station whose number of empty storage spaces is equal to or greater than the number of occupied storage spaces as a candidate station, it is ensured that the target cargo corresponding to a plurality of job lists is sufficiently placed in the empty storage space of the candidate station.

It can be understood that the bins assigned to the candidate stations are all the bins previously assigned to the candidate stations. Bins that have not yet been assigned to a candidate station can be understood to be all bins on the current storage rack that have not been assigned to that candidate station.

Illustratively, the efficiency value E of each unallocated bin corresponding to the candidate station satisfies the following equation.

E = K / (1 + h [* d] _0 / d_0max)

Here, K is the number of the first cargo of the candidate station, K is the number of the first cargo of the candidate station, d0 is the distance from the unallocated bin to the candidate station, and d0max is from the unallocated bin. It is the maximum value of the distance to the candidate station, and h is a preset value (for example, h = 0.1).

The average efficiency value W of the candidate stations can be obtained by calculating the average value of the efficiency values E of all the unallocated bins corresponding to the candidate stations. Selectably, the allocation efficiency value I of the candidate station satisfies the following equation.

I = (V + u * W_1) * (1 + P) / C

Here, V is the number of first cargoes of the candidate station, W1 is the average efficiency value of the candidate station, and P is the ratio of the priority value of the task waiting for allocation to the maximum priority value in the task waiting for allocation. Yes, C is the number of storage spaces to be occupied, and u is a preset value.

The control method of the warehouse system according to the present embodiment calculates the number of the first cargo and the number of the second cargo of each candidate station, and is based on the number of the second cargo and the distance between the candidate station and each bin. By calculating the average efficiency value of the candidate stations and calculating the allocation efficiency value of the candidate stations from the average efficiency value of the candidate stations and the number of first cargoes, the candidate station with the highest allocation efficiency value from each candidate station is finally obtained. Is selected as the target station. This combines multiple factors such as the number of cargoes that match the cargo information of the assigned and unallocated bins of the candidate station with the cargo information of the task waiting to be allocated, and the distance between each bin and the station. The distribution efficiency value of each candidate station can be comprehensively obtained. Then, by referring to the allocation efficiency value and selecting the candidate station having the highest allocation efficiency value from each candidate station as the target station of the task waiting for allocation, the cargo issuance efficiency is maximized.

In one embodiment, step S102 includes the following steps S301, S302, S303, as shown in FIG.

In step S301, the remaining cargo information of the task waiting for allocation is determined based on the cargo information of the task waiting for allocation and the cargo information of the bin allocated to the target station. Here, it can be understood that the remaining cargo information of the pending allocation task is the remaining cargo information that is not filled in the allocated bin in the pending allocation task.

In step S302, a bin that satisfies the remaining cargo information of the pending allocation task is determined as a candidate bin based on the cargo information of each current bin. Among them, the bin that satisfies the cargo information of the task waiting to be allocated may be a bin in which at least a part of the cargo currently stored matches the cargo information of the task waiting to be allocated.

In step S303, the transport cost of each candidate bin is calculated, and the candidate bin with the lowest transport cost is determined as the target bin.

In one example, the transport cost U1 of the candidate bin satisfies the following equation.

U_1 = w_1 d_1 / d_1max -w_2 s / s_max + w_3 n_1 / n_1max + w_4 m_1 / m_1max + w_5 * f1

Here, d1 is the distance from the candidate bin to the target station, d1max is the maximum value of the distance from the candidate bin to the target station, and s is the cargo of the candidate bin satisfying the cargo information of the task waiting for allocation. It is a number, smax is the maximum number of cargoes in the candidate bin that satisfies the cargo information of the task waiting to be allocated, n1 is the number of current entry / exit tasks in the passage in which the candidate bin is located, and n1max is. M1 is the maximum number of stations assigned to the candidate bin and m1max is the maximum number of stations assigned to the candidate bin. W1, w2, w3, w4, and w5 are preset coefficients, and as f1, it is 1 if the candidate bin is in the storage space, and 0 otherwise.

In one embodiment, as shown in FIG. 4, the robot includes a first robot, and step S103 includes the following steps S401 and S402.

In step S401, the target passage corresponding to the target bin is determined based on the position information of the target bin.

In step S402, the first target robot that transports the target bin from the storage space to the temporary storage space is determined based on the position of each first robot in the target passage.

Based on the position information of the first robot already existing in the target passage, the first robot closest to the target bin is selected as the first target robot. As a result, the movement distance of the first target robot to the target passage can be minimized, and the movement efficiency of the first target robot to the target passage can be maximized.

Illustratively, the position information of the target bin may be the position information of the storage rack in which the target bin is located. The aisle adjacent to the storage rack where the target bin is located is the target aisle. Here, the aisle is defined by two adjacent storage racks. The storage rack has a storage space and a temporary storage space set in different layers, and the temporary storage space can be located at the bottom layer of the storage rack. After determining the first target robot, a movement instruction is transmitted to the first target robot so as to move the first target robot from another passage to the passage entrance of the target passage. The first bin transfer task for controlling the first target robot so as to transport the target bin located in the storage space to the temporary storage space is transmitted to the first target robot.

In one embodiment, as shown in FIG. 5, the robot includes a second robot, and step S103 further comprises step S501.

In step S501, the second robot having the closest distance to the target bin is determined as the second target robot that conveys the target bin from the temporary storage space to the target station based on the position information of the target bin.

As a result, the moving distance of the second target robot to the temporary storage space where the target bin is located can be minimized, and the transport efficiency of the second target robot can be improved.

Illustratively, after determining the second target robot, the second target moves along the target passage under the temporary storage space of the storage rack to transport the target bin located in the temporary storage space to the target station. The second bin transfer task for controlling the robot is transmitted to the second target robot.

Selectably, as shown in FIG. 6, step S103 further includes steps S601, S602.

In step S601, the second target robot is controlled to transport the target bin from the target station to the target rack.

In step S602, the second target robot is controlled so as to stay under the empty temporary storage space of the storage rack.

Illustratively, in step S601, if cargo remains in the target bin after the sorting work is performed in the target station, the second target robot is controlled to transport the target bin to the temporary storage space of the storage rack. The bin return task for the purpose is transmitted to the second target robot. Further, the first robot conveys the target bin from the temporary storage space to the storage space.

Illustratively, in step S602, after the second target robot completes the transfer task of the target bin, if a new bin transfer task is not assigned, the target pause point is given to the vacant second target robot. To assign.

Specifically, from each of the current aisles, a aisle with an empty temporary storage space is selected as a candidate aisle, and based on the number of current tasks of each aisle and the distance between each aisle and the second target robot. , Calculate the stop cost value of each candidate passage, select the candidate passage with the lowest stop cost value as the stop passage, and select the stop among the stops under the temporary storage space in the empty state of the stop passage. 2 Randomly select as the target stop for the target robot. Further, a stop task that controls the second target robot so as to move to the target stop is generated and transmitted to the second target robot.

In one embodiment, step S103 further comprises determining the order in which the second target robot accesses each target station according to a preset placement order when the target bin corresponds to a plurality of target stations. Here, the preset arrangement order arranges the number of expected arrival bins at each target station in order from small to large.

It should be noted that it is necessary to process a plurality of tasks waiting for allocation at the same time, and when the target bin corresponds to a plurality of target stations, it is necessary to determine the order in which the target bin accesses the plurality of target stations. The second target robot can sequentially access a plurality of target stations according to a preset arrangement order. Further, the preset placement order may access each target station in ascending to large order based on the total number of arrived bins and expected arrival bins of each target station. ..

In another example of the invention, the preset placement order may be determined based on the priority value of the task awaiting allocation corresponding to each target station, i.e., the second target robot has a priority value. Priority access to higher target stations. Alternatively, the preset placement order may be such that the distance between the position where the target bin is currently present and each target station is arranged in the order of near to far, that is, the second target robot arranges each target. You may access the stations in order from near to far.

Hereinafter, a specific example of the control method of the warehouse system according to the present embodiment will be described with reference to FIG. 22.

As shown in FIG. 22, after receiving the job list which is the task waiting for allocation, the target station is determined according to the job list allocation station algorithm, and specifically, the average efficiency value of each candidate station and the number of the second cargo are set. Based on this, the allocation efficiency value of each candidate station can be calculated, and the candidate station with the lowest allocation efficiency value can be selected as the target station. Here, the number of second cargoes is the number of cargoes in which the remaining cargo information of the assigned rack of the candidate station and the cargo information of the job list are matched. Then, the target bin is determined according to the job list allocation bin algorithm, specifically, the bin satisfying the cargo information of the job list is determined as the candidate bin based on the cargo information of each current bin, and the transportation cost of each candidate bin is determined. Can be calculated and the candidate bin with the lowest transport cost can be determined as the target bin. If the cargo information of all candidate bins cannot meet the cargo information of the job list, that is, if the inventory required for the job list is insufficient and the allocation of the target bin fails, the job list is suspended. , Release the bound target station.

If the target bin allocation is successful and the target bin corresponds to multiple target stations at the same time, the order in which the target robots access each target station is determined based on the sequence algorithm in which the bin accesses multiple stations. , Generate a bin transport task and send it to the target robot. Then, the target robot is determined according to the task allocation algorithm, and the work points to which the target robots are less allocated at the station are selected and assigned to the target robots.

Hereinafter, the method of controlling the warehouse system according to the second embodiment of the present application will be described with reference to FIGS. 7 to 10. The control method of the warehouse system according to the present embodiment can be applied to a warehouse system in which the first robot is assigned to the passage having the assignment waiting task and the allocation waiting task is assigned to the first robot.

FIG. 7 is a flowchart showing a control method of the warehouse system according to the embodiment of the present application.

As shown in FIG. 7, the control method includes the following steps S701, S702, S703, and S704.

In step S701, the vacant first robot is selected as the matching-waiting first robot.

In step S702, the passage in which the target bin is located is selected as the matching waiting passage based on the position information of the target bin.

In step S703, for each of the matching waiting first robots, the corresponding target passage and the first matching target passage are based on the distance between the matching waiting first robot and each matching waiting passage and the number of assignment waiting tasks of each matching waiting passage. 1 Determine the target robot.

In step S704, the task of waiting for allocation of the target passage is assigned to the corresponding first target robot.

Illustratively, the vacant first robot refers to the first robot that is not currently executing a task, specifically, the first robot in a passage that has no task waiting to be assigned and the first robot that is not executing a task. It can include a first robot outside the aisle.

Illustratively, the aisle having the allocation waiting task may be the aisle having the allocation waiting issue task and / or the allocation waiting receipt task in the current state. Among them, the shipping task refers to a task of transporting a bottle from the storage space of the rack to the temporary storage space and further transporting the bin from the temporary storage space to the station. The warehousing task may be a task of transporting from the station to the temporary storage space of the rack and further transporting from the temporary storage space to the storage space.

Illustratively, the distance between the matching waiting first robot and the matching waiting passage is the Manhattan distance between the current position of the matching waiting first robot and the passage entrance of any of the matching waiting passages, that is, matching in the standard coordinate system. It may be the sum of the absolute values of the coordinate differences between the current position of the waiting first robot and the passage entrance of the matching waiting passage. The number of tasks waiting to be allocated in the matching aisle may be the sum of the current number of tasks waiting to be allocated in the matching aisle and the number of tasks waiting to be allocated. Here, the distance between the matching waiting first robot and the matching waiting passage is inversely proportional to the matching value in which the matching waiting first robot matches the matching waiting passage. That is, the smaller the distance between the matching waiting first robot and the matching waiting passage, the larger the matching value that the matching waiting first robot matches with the matching waiting passage. The number of tasks waiting to be assigned to the matching waiting passage is directly proportional to the matching value in which the matching waiting first robot matches the matching waiting passage. That is, the larger the number of tasks waiting for allocation of the matching waiting passage, the larger the matching value that the matching waiting first robot matches with the matching waiting passage.

In one example, the maximum weight matching in which the matching waiting first robot and the matching waiting passage are in perfect matching is obtained by using the KM (Kun-Munkres) algorithm.

Specifically, all the matching first robots join the vertex set X, all the matching waiting paths join the vertex set Y, and any vertex xi of the vertex set X and any vertex of the vertex set Y. By connecting yj to form a side (i, j) and setting the matching value between the matching first robot i and the matching waiting passage j as the weight value of the side (i, j), all the matching waiting numbers are obtained. 1 Build a weighted bipartite graph of the robot and the matching waiting passage. Next, the maximum weight matching in the perfect matching of the weighted two-part diagram is obtained by the KM algorithm. That is, all the vertices in the vertex set X have corresponding matching vertices from the vertex set Y, all the vertices in the vertex set Y have corresponding matching vertices from the vertex set X, and all. One matching is found so that the sum of the weight values of the sides (i, j) is the largest.

The maximum weight matching in the perfect matching obtained by the KM algorithm is the optimum matching between the matching first robot and the matching waiting passage, and the matching between the corresponding matched first robot of each set and the target passage. The sum of the values is maximized. As a result, the optimum matching result between the matching waiting first robot and the matching waiting passage can be quickly and accurately obtained, and as a whole, a high matching value between each matching waiting first robot and each matching waiting passage can be guaranteed. .. Further, the rational distribution of the first robots in each passage having the assignment waiting task is reached, and it is advantageous to improve the execution efficiency of the warehousing task and the warehousing task.

Illustratively, the matching waiting first robot and the matching waiting passage are matched to obtain the matched first robot and the corresponding target passage, and the matched first robot is moved to the passage entrance of the target passage. A movement instruction for control is transmitted to the matched first robot.

Illustratively, assigning a task waiting to be assigned to a target passage to a corresponding first robot that has been matched can sequentially assign tasks waiting to be assigned to the matched first robot according to the priority of the task waiting to be assigned. For example, when there are a plurality of tasks waiting to be assigned and the priorities of the plurality of tasks are different, the task waiting to be assigned with a higher priority is preferentially assigned to the matched first robot, and then the assignment having a normal priority is assigned. Assign the waiting task to the matched first robot.

Further, it is possible to calculate the allocation value of each allocation waiting task for the first robot and sequentially allocate a plurality of allocation waiting tasks to the first robot in the order of the allocation value from the largest to the smallest. Here, the allocation value can be calculated by the distance between the matched first robot and the position of the target bin corresponding to each allocation waiting task.

In one embodiment, the warehouse system includes a storage rack, a station, a first robot, and a second robot. There are multiple storage racks, which are arranged side by side at intervals, and a passage is defined between two adjacent storage racks. The storage rack includes a storage space and a temporary storage space, and is set in a different hierarchy from the storage space and the temporary storage space. For example, the storage space may be a plurality of storage spaces arranged at intervals in the vertical direction, and the temporary storage space is located below the plurality of storage spaces and is located at the bottom layer of the storage rack. The first robot can move along the aisle to transport the bins on the temporary storage space to the storage space or to transport the bins on the temporary storage space to the temporary storage space. The station is used by workers to sort the cargo stored in the bottles and to put the cargo in the bottles. The second robot can move between the storage rack and the station in order to transport the bins on the temporary storage space to the station or to transport the bins of the station to the temporary storage space. The first robot in the embodiment of the present application may be the first robot.

In the control method of the warehouse system according to the present embodiment, the matching waiting first robot waits for each matching based on the distance between the matching waiting first robot and each matching waiting passage and the number of assignment waiting tasks of each matching waiting passage. By calculating the matching value that matches the passage and selecting the matching waiting passage with the highest matching value as the target passage of the matching waiting first robot, the degree of matching between the first robot and the passage in the conventional warehouse system is poor. Therefore, the technical problem of poor task execution efficiency is solved. According to the method according to the embodiment of the present invention, the first robot and the passage are matched by integrating and matching the two elements of the distance between the first robot and the passage and the number of tasks waiting for allocation of the passage. The optimum matching result with and can be obtained quickly and accurately, the distribution of the first robot in each passage becomes rational, and it is advantageous for the efficiency of the warehousing task and the warehousing task by the first robot.

In one embodiment, the matching aisle includes a first matching aisle and a second matching aisle.

As shown in FIG. 8, step S702 includes the following steps S801 and S802.

In step S801, the passage having the assignment waiting task and the first robot does not exist is selected as the first matching waiting passage.

In step S802, when the number of first matching waiting passages is smaller than the number of matching waiting first robots, the passage having the allocation waiting task and the first robot exists is selected as the second matching waiting passage.

After selecting the first matching waiting passage and the second matching waiting passage, the first matching waiting passage and the second matching waiting passage may be matched with the first matching waiting robot together.

Illustratively, when the number of first matching aisles is less than the number of first matching robots, the aisles with the assignment waiting task and the first robots are elected and relative to the number of first robots in the aisles. , The ratio of the number of tasks waiting to be assigned in the passage is calculated, and the sum of the number of the first matching passage and the number of the second matching waiting passages is equal to the number of the first robots waiting for matching, or there is a task waiting to be assigned and the first. Until all the passages in which the robot exists are selected, the second matching waiting passage is set in the order of the ratio from the largest to the smallest.

When the sum of the number of first matching waiting passages and the number of second matching waiting passages is equal to the number of first matching waiting robots, the number of vertices of the vertex set X and the vertex set Y is the same, so that the KM algorithm Can be used to obtain the perfect matching result between the matching first robot and the matching waiting passage. That is, any vertex in the vertex set X has vertices uniquely matched from the vertex set Y, all vertices in the vertex set Y have vertices uniquely matched from the vertex set X, and , The sum of the weights of all the sides (i, j) in this matching is the maximum.

In one embodiment, the matching value Wij that the first robot waiting for matching matches with the matching waiting passage satisfies the following equation.

W_2 = -u_1 d_2 / d_2max + u_2 m_2 / m_2max + u_3 n_2 / n_2max

Here, d2 is the distance between the matching waiting first robot xi and the matching waiting passage yj, d2max is the maximum value of the distance between each matching waiting first robot and each matching waiting passage, and m2 is the matching value. M2max is the number of tasks waiting to be assigned in the waiting aisle yj, m2max is the maximum number from the tasks waiting to be assigned in each matching aisle, n2 is the number of compulsory priority tasks in the matching aisle yj, and n2max is the number of tasks waiting to be assigned. , The maximum value from the number of compulsory priority tasks of each matching waiting passage, and u1, u2, and u3 are preset values. For example, u1 may be 700, u2 may be 1, and u3 may be 70,000.

In the above equation, if the denominator of a certain fraction is zero, the calculation result of that fraction will be zero.

In one example, the distance d2 between the matching waiting first robot xi and the matching waiting passage yj can be calculated as follows. The position p0 of the first robot with respect to the passage where the first robot is located is acquired, the positions p1 and p2 of the two passage openings of the passage where the first robot is located are acquired, and the positions p3 of the two passage openings of the matching waiting passage. , P4 is acquired. The distance d2 between the matching waiting first robot xi and the matching waiting passage yj satisfies the following equation.

d2 = min (d01 + d13, d01 + d14, d02 + d23, d02 + d24)

Here, d01 is the Manhattan distance between the positions p0 and p1, d13 is the Manhattan distance between the positions p1 and p3, d14 is the Manhattan distance between the positions p1 and p4, and d02 is. The Manhattan distance between positions p0 and p2, d23 is the Manhattan distance between positions p2 and p3, and d24 is the Manhattan distance between positions p2 and p4.

In one embodiment, if there is a compulsory priority task in the assignment waiting task of the matching waiting passage and the first robot does not exist in the passage before matching the matching waiting first robot and the matching waiting passage. The first robot is preferentially assigned to the matching waiting passage where the compulsory priority task exists. For example, the first robot closest to the aisle can be selected to match the aisle, or the first robot in the aisle without a compulsory priority task can be selected to match the aisle.

In one embodiment, step S704 includes steps S901, S902, S903, S904, as shown in FIG.

In step S901, the number of tasks that can be assigned to the target passage is calculated.

In step S902, when the number of tasks that can be assigned is larger than 0, the corresponding number of work areas is divided in the target passage based on the number of matched first robots. The number of matched first robots is equal to the number of work areas, and each matched first robot has a one-to-one correspondence with each work area.

In step S903, the matched first robot whose number of assigned tasks is less than the upper limit threshold of the task is selected as the first robot waiting for allocation. Here, the upper limit threshold value of the task refers to the maximum value of the number of tasks that can be assigned to the matched first robot.

In step S904, the distance between the first robot waiting for allocation and the target bin corresponding to each assignable task, and the work area passed by the first robot waiting for allocation to move to the target bin corresponding to each assignable task. Based on the number of tasks, the target task is determined from the assignable tasks, and the target task is assigned to the corresponding first robot waiting for allocation.

Illustratively, in step S901, the number of assignable tasks includes the number of assignable warehousing tasks and the number of assignable issuing tasks. Here, the number of warehousing tasks that can be allocated can be calculated based on the number of warehousing tasks waiting to be allocated and the number of empty temporary storage spaces. The number of issue issues that can be allocated can be calculated from the number of issue issues waiting to be allocated and the free storage space.

Illustratively, in step S902, when the number of work areas is plural, the number of storage spaces corresponding to each work area is equal, and the matched first robot performs a warehousing task or a warehousing task in the corresponding work area. Run.

Illustratively, in step S904, the distance between the first robot awaiting allocation and the target bin corresponding to each assignable task is determined by the position of the first robot awaiting allocation and the assignable warehousing task before executing the task. The distance from the position of the temporary storage space where the target bin corresponding to is present, or the position of the first robot waiting for allocation before executing the task and the storage where the target bin corresponding to the assignable issue task exists. It may be the distance from the position of the space. The number of work areas that the first robot awaiting allocation has passed to move to the target bin corresponding to each assignable task is the current number of work areas that the first robot awaiting allocation has in the process of performing this assignable task. The number of work areas passed in the process of moving from position to target bin position.

The distance between the first robot waiting for allocation and the target bin corresponding to the task that can be assigned is inversely proportional to the allocation value for allocating the task that can be assigned to the first robot waiting for allocation. That is, the smaller the distance between the first robot waiting for allocation and the target bin corresponding to the task that can be assigned, the larger the assigned value of the task that can be assigned to the first robot waiting for allocation. The number of work areas that the allocation-waiting first robot has passed to move to the target bin corresponding to each assignable task is inversely proportional to the allocation value that allocates the assignable task to the allocation-waiting first robot. That is, the smaller the number of work areas that the first assigned robot has passed to move to the target bin corresponding to each assignable task, the larger the allocation value for allocating this assignable task to the first robot waiting for allocation. ..

The allocation value Uij, which can be selected and assigned to the first robot waiting for allocation by the assignable task, satisfies the following equation.

U_1 = -e_1 * f_2-e_2 * g / g_max

Here, f2 is the number of work areas that the first robot ai waiting for allocation has passed to execute the task that can be assigned, and g is the number of work areas that the first robot ai waiting for allocation has passed to execute the task that can be assigned. It is a moving distance, gmax is a maximum value of a distance moved to execute a task that can be assigned by each allocation waiting first robot ai, and e1 and e2 are preset values, for example, e1. May be 700 and e2 may be 1.

In the above equation, if the denominator of a certain fraction is zero, the calculation result of that fraction will be zero.

Further, when the work area in which the target bin corresponding to the assignable task exists is located at the end of the target passage and the first robot waiting for allocation is not located in the work area in which the target bin exists, the allocation waiting first robot is used. The assigned value of the task that can be assigned to one robot approaches 0.

In one example, the KM algorithm can be used to find the maximum weight matching in which the first robot awaiting allocation and the task awaiting allocation are in perfect matching.

Specifically, all the first robots waiting for allocation join the vertex set P, all the tasks waiting for allocation join the vertex set Q, and any of the vertices pi of the vertex set P and any of the vertices Q of the vertex set Q. By connecting qj to form an edge (i, j) and setting the allocation value between the first robot i waiting for allocation and the task j waiting for allocation as the weight value of the edge (i, j), all the allocation waiting first robots 1 Build a weighted two-part graph of the robot and the task waiting to be assigned. Next, the maximum weight matching in the perfect matching of the weighted two-part diagram is obtained by the KM algorithm. That is, all the vertices in the vertex set P have corresponding matching vertices from the vertex set Q, all the vertices in the vertex set Q have corresponding matching vertices from the vertex set P, and all. One matching is found so that the sum of the weight values of the sides (i, j) is the largest.

The maximum weight matching in the perfect matching obtained by the KM algorithm is the optimum allocation method between the first robot waiting for allocation and the task waiting for allocation, and the corresponding first robot waiting for allocation and the task waiting for allocation in each set. The sum of the assigned values of is maximized. This promptly and accurately obtains the optimum allocation result between the first robot waiting for allocation and the task waiting for allocation, and guarantees that each first robot waiting for allocation and each task waiting for allocation have the highest allocation value as a whole. Further, it is possible to improve the execution efficiency when the first robot executes the warehousing task and the warehousing task in the passage.

Selectably, as shown in FIG. 10, step S901 includes steps S1001, S1002, S1003.

In step S1001, the minimum value among the number of assigned waiting warehousing tasks and the number of empty temporary storage spaces in the target aisle and the minimum value among the number of allocated waiting warehousing tasks and the number of empty storage spaces in the target aisle are added. To obtain the first reference value.

In step S1002, the number of matched first robots is multiplied by the upper limit threshold value of the task, and the total number of assigned tasks of all the matched first robots is subtracted to obtain the second reference value. Here, the upper limit threshold value of the task is the maximum value of the number of tasks that can be assigned to a single matched first robot.

In step S1003, the minimum value among the first reference value and the second reference value is selected as the number of tasks to which the target passage can be assigned.

In one example, the number of assignable issue tasks and the number of assignable inbound tasks can be calculated based on the number of assignable tasks. specifically,

If the number of assignable tasks exceeds 0 and the number of issue bins in the target passage exceeds the product of the number of empty temporary storage spaces and the preset value v1, the number of assignable warehousing tasks is calculated. However, here, the number of warehousing tasks that can be allocated is the minimum value among the number of tasks that can be assigned, the number of warehousing bins in the temporary storage space, and the number of empty storage spaces, and v1 is 0.5. To be

Calculate the number of assignable issue tasks, where the number of assignable issue tasks is the difference between the number of assignable tasks and the number of assignable goods receipt tasks, the number of assignable issue tasks, and the provisional availability. It is the minimum value among the number of storage spaces and the comparison value, and the comparison value C0 includes satisfying the following equation.

C0 = max (0, j * v2-k)

Here, j is the number of empty temporary storage spaces, k is the number of shipping bins, and the preset value v2 may be 0.8.

Furthermore, calculating the number of assignable issue tasks and the number of assignable goods receipt tasks based on the number of assignable tasks means that the number of assignable tasks is greater than 0 and the issue bin of the target passage. If the number is less than or equal to the product of the number of empty temporary storage spaces and the preset value v1, the number of assignable issue tasks is calculated, where the number of assignable issue tasks is the assignable task. It is the minimum value among the number of warehousing tasks, the number of empty temporary storage spaces, and the comparison value. The comparison value C0 satisfies the following formula and calculates the number of warehousing tasks that can be allocated. Here, the number of goods receipt tasks that can be allocated is the minimum of the difference between the number of tasks that can be assigned and the number of goods issue tasks that can be assigned, the number of goods receipt bins in the temporary storage space, and the number of empty storage spaces. Including taking a value and further.

C0 = max (0, j * v2-k)

Here, j is the number of empty temporary storage spaces, k is the number of shipping bins, and the preset value v2 may be 0.8.

Hereinafter, the method of controlling the warehouse system according to the third embodiment of the present application will be described with reference to FIGS. 11 to 17. The control method of the warehouse system according to the present embodiment can be applied to a warehouse system in which a second robot is assigned to a passage having a task waiting to be assigned and a task waiting to be assigned is assigned to the second robot.

FIG. 11 is a flowchart showing a control method of the warehouse system according to the embodiment of the present application. As shown in FIG. 11, the method comprises the following steps S1101, S1102, S1103, S1104.

In step S1101, the import warehouse area and the export warehouse area are determined from the plurality of initial warehouse areas based on the number of tasks waiting to be allocated in each initial warehouse area and the current number of second robots.

In step S1102, the export second robot in each export warehouse area is determined.

In step S1103, the import second robot in each import warehouse area is determined from each export second robot, and the import second robot is arranged from the export warehouse area to the corresponding import warehouse area.

In step S1104, for each matching waiting warehouse area, the corresponding second target robot of each target bin in the matching waiting warehouse area is determined from the vacant second robot in the matching waiting warehouse area. Here, the second target robot is used to perform the corresponding assignment-waiting task, i.e., to transport the target bin from the storage space to the target station.

Illustratively, a warehouse system includes multiple warehouse warehouse areas, each warehouse warehouse area is equipped with a storage rack and a station, and a second robot is assigned to each warehouse area and performs a task corresponding to each warehouse area. do. The initial warehouse area refers to each warehouse area before the second robot is placed.

The task waiting to be allocated in the initial warehouse area refers to a task to which the second robot in the initial warehouse area is not assigned. The current number of second robots in the initial warehouse area is the number of second robots located in the initial warehouse area, and is vacant with the second robot performing a task located in the initial warehouse area. Includes 2 robots. The import warehouse area refers to the initial warehouse area where the second robot needs to be imported, and the export warehouse area refers to the initial warehouse area where the second robot needs to be exported.

Illustratively, it is calculated by calculating the product of the ratio of the number of tasks waiting to be allocated in the initial warehouse area to the total number of tasks waiting to be allocated in all initial warehouse areas and the total number of second robots in all initial warehouse areas. By comparing the product with the current number of second robots in the initial warehouse area, it is determined whether or not the second robot needs to be moved in or out of the initial warehouse area, and the initial warehouse area is moved in. Determine if it is a warehouse area or an export warehouse area.

In a specific example, each initial warehouse area includes a storage rack, a station, a first robot, and a second robot. A plurality of storage racks are arranged side by side at intervals, and a passage is defined between two adjacent storage racks. The storage rack includes a storage space and a temporary storage space, and is set in a different hierarchy from the storage space and the temporary storage space. For example, the storage space may be a plurality of storage spaces arranged at intervals in the vertical direction, and the temporary storage space is located below the plurality of storage spaces and is located at the bottom layer of the storage rack. The first robot can move along the aisle to transport the bins on the temporary storage space to the storage space or to transport the bins on the temporary storage space to the temporary storage space. The station is used by workers to sort the cargo stored in the bottles and to put the cargo in the bottles. The second robot can move between the storage rack and the station in order to transport the bins on the temporary storage space to the station or to transport the bins of the station to the temporary storage space.

Illustratively, the export second robot in each export warehouse area is determined from the vacant second robot in the export warehouse area, or the vacant second robot in the export warehouse area, and the bin reversion task. It can be determined from a second robot that is running and whose distance to the end point of the task is less than or equal to a preset distance threshold. Here, the vacant second robot refers to the second robot to which the task is not currently assigned, and the bin repositioning task means that the second robot transports the bin from one storage rack to another. Point to that.

Illustratively, determining the import second robot in each import warehouse area from each export second robot is the closest export from all the export second robots to the import warehouse area for each import warehouse area. The movement command for selecting the second robot as the transfer second robot in the transfer warehouse area and controlling the calling second robot to move from the currently located transfer warehouse area to the assigned transfer warehouse area is given. It is transmitted to the import second robot.

In the control method of the warehouse system according to the present embodiment, the import warehouse area and the export warehouse area are determined from each initial warehouse area according to the number of tasks waiting to be allocated in each initial warehouse area and the current number of second robots, and the export warehouse is determined. The second robot to move out of the area is determined, and the second robot to move in to the warehouse area is decided from the second robot to move out. Then, for each import warehouse area, the second target robot in the transfer warehouse area is determined from the transfer second robot in the transfer warehouse area, and the task of waiting for station allocation is matched with each second target robot. As a result, by allocating the number of the second robots in each initial warehouse area according to the actual situation of each initial warehouse area, the distribution number of the second robots in each initial warehouse area becomes rational, and the distribution number of the second robots in each initial warehouse area becomes rational. The task allocation becomes balanced, the work efficiency of the entire warehouse system can be improved, and the technical problem of reduced work efficiency due to the unreasonable distribution of the second robot in each warehouse area of the warehouse system in the related technology is solved. Can be resolved.

In one embodiment, step S1101 includes steps S1201 and S1202, as shown in FIG.

In step S1201, when the current number of the second robots in the initial warehouse area is smaller than the allocated number of the second robots in the initial warehouse area, the initial warehouse area is determined as the import warehouse area.

In step S1202, when the current number of the second robots in the initial warehouse area is larger than the allocated number of the second robots in the initial warehouse area, the initial warehouse area is determined as the import warehouse area.

Here, the number of allocations of the second robot in the initial warehouse area is the ratio between the number of incomplete tasks in the initial warehouse area and the total number of incomplete tasks in the warehouse system, and the total number of the second robots in the warehouse system. It is a product. That is, the number of second robots allocated in the initial warehouse area is the product of the ratio of the number of unfinished tasks in the initial warehouse area to the number of all unfinished tasks in the warehouse system and the total number of second robots in the warehouse system. be.

When the current number of the second robots in the initial warehouse area is equal to the allocated number of the second robots in the initial warehouse area, it is not necessary for the initial warehouse area to move in or out of the second robots. That is, the initial warehouse area is neither the import warehouse area nor the export warehouse area.

In one embodiment, step S1102 includes steps S1301 and S1302, as shown in FIG.

In step S1301, the number of the second robot in the export warehouse area is based on the current number of the second robots in the export warehouse area, the lower limit of the number of the second robots, the allocated number of the second robots, and the number of empty second robots. Calculate the number of exports.

In step S1302, the export second robot in the export warehouse area is determined based on the number of exports of the second robot in the export warehouse area.

Illustratively, when the number of second robots allocated to the export warehouse area is equal to or greater than the lower limit of the number of second robots in the export warehouse area, the current number of second robots and the number of second robots allocated are The difference value is calculated, and the minimum value of the difference value and the number of empty second robots is taken as the number of exports of the second robot in the export warehouse area. When the assigned number of the second robots is smaller than the lower limit of the number of the second robots in the export warehouse area, the difference value between the current number of the second robots and the lower limit of the number of the second robots is calculated. The minimum value of the difference value and the number of empty second robots is defined as the number of second robots in the export warehouse area. Here, the lower limit of the number of the second robots may be the minimum value among the number of the second robots that can be accommodated preset in the export warehouse area. The number of vacant second robots is the number of export second robots to which the task is not currently assigned in the export warehouse area, the bin relocation task is being executed, and the distance from the end point of the task is preset. It may be the sum of the number of the second robots which are equal to or less than the distance threshold.

The export number U3 of the second robot in the export warehouse area can satisfy the following equation.

U3 = max (k, max (0, k1) -max (k2, kmin))

Here, k is the number of vacant second robots in the export warehouse area, k1 is the number of current second robots in the export warehouse area, k2 is the number of second robots allocated in the export warehouse area, and kmin is. , The lower limit of the number of second robots in the export warehouse area.

Illustratively, after obtaining the number of exports of the second robot in the export warehouse area, a corresponding number of empty second robots are selected from the export warehouse area and determined as the export second robot.

In one embodiment, step S1103 includes steps S1401, S1402, S1403, S1404, as shown in FIG.

In step S1401, the number of second robots in the import warehouse area is calculated based on the allocated number of the second robots in the import warehouse area, the current number of the second robots, and the upper limit of the number of the second robots.

In step S1402, refer to the product of the ratio of the number of imports of the second robot in the import warehouse area to the total number of imports of the second robot in each import warehouse area and the total number of exports of the second robot in each export warehouse area. Let it be a value.

In step S1403, the minimum value of the reference value and the number of imported second robots in the imported warehouse area is determined as the actual demand number of the second robot in the imported warehouse area.

In step S1404, from the export second robot in each export warehouse area, the export second robot having the shortest distance from the import warehouse area according to the actual number of demands of the import warehouse area is selected as the import second robot in the import warehouse area. do.

Illustratively, in step S1401, when the assigned number of the second robots is equal to or less than the upper limit of the number of the second robots in the imported warehouse area for each import warehouse area, the allocated number of the second robots and the current second robot are used. The difference value from the number of robots is calculated, and when the difference value is larger than 0, this difference value is taken as the number of imported second robots in the import warehouse area. When the number of allocations of the second robot is larger than the upper limit of the number of allocations of the second robot in the import warehouse area, the difference between the upper limit of the number of allocations of the second robot and the current number of allocations of the second robot is set. Calculated, and when the difference value is larger than 0, the difference value is taken as the number of robots transferred to the second robot in the import warehouse area. Here, the upper limit of the number of the second robots may be the maximum value of the number of the second robots that can be accommodated preset in the import warehouse area.

The import number U4 of the second robot in the import warehouse area can satisfy the following equation.

U4 = max (0, min (p2, pmax) -p1)

Here, p1 is the current number of the second robots in the import warehouse area, p2 is the allocated number of the second robots in the import warehouse area, and pmax is the upper limit of the number of the second robots in the import warehouse area. The value.

Illustratively, in step S1404, the export second robot having the closest distance to the import warehouse area is not assigned a task in the export second robot, and the export second robot having the closest distance to the current position and the import warehouse area is not assigned. Refers to the export second robot that is executing the bin repositioning task in the robot and the export second robot and the distance between the end point position of the task and the import warehouse area is the shortest. After determining the transfer second robot in the transfer warehouse area, a movement command for controlling the movement to the target transfer warehouse area is transmitted to the transfer second robot.

In one embodiment, as shown in FIG. 15, the initial warehouse area comprises a plurality of stations, the method further comprising the following steps.

In step S1501, a second target robot corresponding to each station is determined from the empty second robot in the matching waiting warehouse area based on the type of the allocation waiting task in the matching waiting warehouse area and the number of allocation waiting tasks.

In step S1502, the task waiting for allocation of the station is matched with the second target robot corresponding to the station.

The matching waiting warehouse area includes each import warehouse area and each export warehouse area after the call of the second robot is completed, and the matching waiting warehouse area does not need to call the second robot at the initial stage. The warehouse area is also included.

Illustratively, the types of tasks waiting to be assigned include issue tasks, goods receipt tasks, and inventory tasks. Here, the shipping task is a task of transporting the bins of the storage rack to the station. The warehousing task is the task of transporting station bins to the storage rack. The inventory task is to transport the bins in the storage rack to the station for the employee to take an inventory and return the bins after the inventory to the storage rack. Further, the station type is set corresponding to the type of task waiting to be assigned, in other words, one or more stations are supported for each type of task waiting to be assigned. For example, a warehousing task corresponds to at least one warehousing station, a warehousing task corresponds to at least one warehousing station, and an inventory task corresponds to at least one inventory station. A free second robot that needs to be allocated for each type of task waiting for allocation according to the number of tasks waiting for allocation corresponding to the type of task waiting for allocation in the import warehouse area for each type of task waiting for allocation in the import warehouse area. After determining the number of robots, the vacant second robot corresponding to the number of correspondences is assigned to the station corresponding to the type of task waiting to be assigned as the second target robot, and the task waiting to be assigned corresponding to the station is matched with the second target robot in the station. do.

When the matching waiting warehouse area is the export warehouse area after a part of the second robot is exported, the empty second robot in the matching waiting warehouse area is the remaining empty second robot in the export warehouse area. You may. When the matching waiting warehouse area is the import warehouse area after a part of the second robot is imported, the empty second robot in the matching waiting warehouse area is the empty second robot before the transfer of the second robot in the import warehouse area. , And the second robot that was introduced after that.

In a specific example, the ratio of the number of assignment-waiting tasks corresponding to the allocation-waiting task type to the total number of allocation-waiting tasks corresponding to each allocation-waiting task type, and the number of empty second robots in the matching-waiting warehouse area. By calculating the product of, the number of free second robots that need to be assigned to each type of task waiting to be assigned can be obtained.

In one embodiment, step S1501 includes steps S1601, S1602, S1603, S1604, as shown in FIG.

In step S1601, for each type of task awaiting allocation, based on the ratio of the number of tasks awaiting allocation to the total number of tasks awaiting allocation, the fixed weight of the type of task awaiting allocation, and the initial variable weight of the type of task awaiting allocation. Then, the first variable weight of the type of task waiting to be assigned is calculated.

In step S1602, one of the vacant second robots in the matching waiting warehouse area is assigned as the second target robot to the station corresponding to the type of assigned waiting task having the highest first variable weight.

In step S1603, for each allocation-waiting task type, the ratio of the number of allocation-waiting tasks to the total number of allocation-waiting tasks, the fixed weight of the allocation-waiting task type, and the first variable weight of the allocation-waiting task type. Based on this, the second variable weight of the type of task waiting to be assigned is calculated.

In step S1604, when both the number of vacant second robots waiting for allocation and the number of tasks waiting to be allocated are greater than 0, the first variable weight calculation step, the second target robot allocation step, and the second variable weight calculation. The steps are circulated, and the second variable weight of the task type waiting for allocation is set as the initial variable weight of the type of task waiting for allocation.

In a particular example, step S1601, step S1602, step S1603, and step S1604 may be implemented by a smoothing weighted round robin algorithm.

Illustratively, in step S1601, the product of the ratio of the number of allocation-waiting tasks to the total number of allocation-waiting tasks and the fixed weight of the allocation-waiting task type is calculated, and the product and the allocation-waiting task type are calculated. The first variable weight of the type of task waiting to be assigned may be obtained by calculating the sum with the initial variable weight. Here, the initial variation weight of the type of task waiting to be assigned can be zero.

Illustratively, in step S1602, the type of task waiting to be assigned with the highest first variable weight is selected, and 1 is added to the number of second target robots assigned to the station corresponding to this type of task waiting to be assigned. ..

Illustratively, in step S1603, after calculating the product of the ratio of the number of assignment-waiting tasks to the total number of allocation-waiting tasks and the fixed weight of the allocation-waiting task type, the first of the allocation-waiting task types. The difference between the variable weight and the product may be calculated to obtain the second variable weight of the type of task waiting to be assigned.

Illustratively, in step S1604, when the number of waiting for allocation of the empty second robot is larger than 0, steps S1601, step S1602, and step S1603 are circulated, and the second variation weight is used as the initial variation weight in the subsequent step S1601. do. When the number of waiting for allocation of the free second robot is 0, that is, after determining the number to be assigned to each type of task waiting for allocation of all the free second robots, step S1601, step S1602, and step S1603 are stopped. ..

In one embodiment, step S1502 further includes steps S1701, S1702, S1703, as shown in FIG.

In step S1701, the allocation value of each assignment-waiting task is calculated based on the priority of the station's assignment-waiting task and the distance between the target bin corresponding to the allocation-waiting task and the station.

In step S1702, the allocation-waiting task with the highest number of assigned values is extracted as the target task from the allocation-waiting tasks according to the number of the second target robots in the station.

In step S1703, for each second target robot, the matching value of the second target robot matching each target task is calculated based on the distance between the second target robot and the target bin corresponding to each target task. , The target task with the highest matching value is selected and matched with the second target robot.

Illustratively, in step S1701, the ratio of the priority of the bin corresponding to the task waiting for allocation to the maximum value of the priority of the bin corresponding to each task waiting for allocation of the station is calculated, and the priority of the task waiting for allocation is calculated. The ratio value of the degree can be obtained. Calculate the ratio of the distance between the bin and the station corresponding to the task waiting for allocation to the maximum value of the distance between the bin and the station corresponding to each task waiting for allocation of the station, and obtain the ratio value of the distance of the task waiting for allocation. be able to. Then, the difference between the ratio value of the priority of the task waiting for allocation and the ratio value of the distance of the task waiting for allocation is calculated, and the allocation value of the task waiting for allocation is obtained.

Illustratively, in step S1703, the KM (Kun-Munkres) algorithm can be used to obtain the maximum weight matching between the target task and the second target robot in perfect matching.

Specifically, all the second target robots are joined to the vertex set X, all the target tasks are joined to the vertex set Y, and any of the vertices xi in the vertex set X and any of the vertices yy of the vertex set Y are joined. A vertices (i, j) are formed between the vertices (i, j), and by setting the matching value between the second target robot i and the target task j as the weight value of the vertices i, j), all the second target robots and all the vertices. Build a weighted two-part graph with the target task. Next, the maximum weight matching in the perfect matching of the weighted two-part diagram is obtained by the KM algorithm. That is, all the vertices in the vertex set X have corresponding matching vertices from the vertex set Y, and all the vertices in the vertex set Y have corresponding matching vertices from the vertex set X, and all in this matching. Find the matching that maximizes the sum of the weight values of the sides (i, j) of.

Here, the matching value between the second target robot i and the target task j may be the reciprocal of the distance between the target bin corresponding to the target task j and the station.

The maximum weight matching between the vertex set X and the vertex set Y in the perfect matching obtained by the KM algorithm is the optimum matching result between the second target robot and the target task, and the corresponding second target robot of each set. The sum of the matching values with the target task is maximized. As a result, the optimum matching result between the second target robot and the target task is obtained quickly and accurately, and as a whole, a high matching value between each second target robot and each target task is guaranteed, and the second target robot is high. Efficiency target It is possible to prioritize the execution of tasks and improve the execution efficiency of tasks waiting to be assigned to stations.

The control device 1800 of the warehouse system according to the fourth embodiment of the present application will be described with reference to FIG.

As shown in FIG. 18, the control device 1800 of the warehouse system includes the following modules.

The target station determination module 1801 determines the target station based on the cargo information of the task waiting for allocation.

The target bin determination module 1802 determines candidate bins based on the cargo information of each current bin and the cargo information of the task waiting for allocation, and selects the candidate bin with the lowest transportation cost from each candidate bin as the target bin.

The target robot determination module 1803 determines the target robot based on the position information of the target bin.

The target robot control module 1804 controls the target robot and conveys the target bin to the target station.

In one embodiment, the target station determination module 1801 includes the following submodules.

The candidate station determination submodule determines candidate stations based on the number of storage spaces to be occupied by the task waiting to be allocated and the number of free storage spaces in each station.

The allocation efficiency value calculation submodule is based on the cargo information of bins assigned to candidate stations, the distance between each bin and the candidate station, the cargo information of bins not assigned to candidate stations, and the remaining cargo information of the task waiting to be allocated. , Calculate the allocation efficiency value of each candidate station.

The target station determination submodule determines the candidate station with the highest allocation efficiency value as the target station.

In one embodiment, the target bin determination module 1802 includes the following submodules.

The Remaining Cargo Information Determination submodule determines the remaining cargo information for the awaiting task, based on the freight information for the awaiting task and the freight information for the assigned bins at the target station.

The candidate bin determination submodule determines as candidate bins the bins that satisfy the remaining cargo information in the pending assignment task, based on the cargo information for each current bin.

The target bin determination submodule calculates the transport cost of each candidate bin and determines the candidate bin with the lowest transport cost as the target bin.

In one embodiment, the robot includes a first robot and the target robot determination module 1803 includes the following submodules.

The target passage determination submodule determines the target passage corresponding to the target bin based on the position information of the target bin.

The first target robot determination submodule determines the first target robot for transporting the target bin from the storage space to the temporary storage space based on the position of each first robot in the target passage.

In one embodiment, the robot includes a second robot, and the target robot determination module 1803 further includes a second target robot determination submodule.

The second target robot determination submodule is a second target robot for transporting the second robot closest to the target bin from the temporary storage space to the target station based on the position information of the target bin. decide.

In one embodiment, the target robot control module 1804 is

Controlling the second target robot to transport the target bin from the target station to the target rack,

It is further used to control the second target robot and stop it under the empty temporary storage space of the storage rack.

The function of each module in the control device 1800 of the warehouse system of the fourth embodiment of the present application can refer to the description corresponding to the control method of the first embodiment described above, and is omitted here.

The control device 1900 of the warehouse system according to the fifth embodiment of the present application will be described with reference to FIG.

As shown in FIG. 19, the control device 1900 of the warehouse system includes the following modules.

The matching-waiting first robot determination module 1901 selects the vacant first robot as the matching-waiting first robot.

The matching waiting passage determination module 1902 selects the passage in which the target bin is located as the matching waiting passage based on the position information of the target bin.

The target passage and the first target robot determination module 1903 are based on the distance between the matching first robot and each matching waiting passage for each matching waiting first robot and the number of tasks waiting to be assigned to each matching waiting passage. Then, the corresponding target passage and the first target robot are determined.

The task assignment module 1904 allocates the task waiting for allocation of the target passage to the corresponding first target robot.

In one embodiment, the matching aisle determination module 1902 includes the following submodules.

The first matching waiting aisle determination submodule is a passage having an allocation waiting task, and a passage in which the first robot does not exist is selected as the first matching waiting passage, and the number of the first matching waiting passages is the first matching waiting robot. When the number is less than the number of, it is a passage having an allocation waiting task, and is used to select the passage in which the first robot exists as the second matching waiting passage.

In one embodiment, the task assignment module 1904 includes the following submodules:

The task number calculation submodule calculates the number of tasks that can be assigned to the target passage.

When the number of tasks that can be assigned is larger than 0, the work area division submodule divides the corresponding number of work areas in the target passage according to the number of the first target robots.

The allocation-waiting first robot determination submodule selects the first target robot whose number of assigned tasks is less than the upper limit threshold of the task as the allocation-waiting first robot.

The target task assignment submodule moves to the distance between the first robot waiting to be assigned and the target bin corresponding to each assignable task, and to the target bin corresponding to each assignable task by the first robot waiting to be assigned. Based on the number of work areas passed through, the target task is determined from the target task waiting to be assigned, and the task is assigned to the corresponding first robot waiting to be assigned.

In one embodiment, the assignable task count submodule includes the following units:

The first reference value calculation unit is the minimum of the number of assigned waiting tasks and the number of empty temporary storage spaces of the target passage, and the minimum of the number of assigned waiting and receiving tasks of the target passage and the number of empty storage spaces. The first reference value is obtained by adding the value and the value.

The second reference value calculation unit calculates the second reference value by multiplying the number of matched first robots by the upper limit threshold of the task and subtracting the total number of assigned tasks of all the matched first robots. ..

The task number determination unit that can be assigned selects the minimum value among the first reference value and the second reference value as the number of tasks that can be assigned in the target passage.

The function of each module of the control device 1900 of the warehouse system of the fifth embodiment of the present application can refer to the description corresponding to the control method of the second embodiment described above, and is omitted here.

The control device 2000 of the warehouse system according to the sixth embodiment of the present application will be described with reference to FIG. 20.

As shown in FIG. 20, the control device 2000 of the warehouse system includes the following modules.

The import warehouse area and export warehouse area determination module 2001 determines the import warehouse area and the export warehouse area from each initial warehouse area based on the number of tasks waiting to be allocated in each initial warehouse area and the current number of second robots.

The export second robot determination module 2002 determines the export second robot in each export warehouse area.

The import second robot determination module 2003 determines the import second robot in each import warehouse area from each export second robot, and moves the import second robot from the export warehouse area to the corresponding import warehouse area.

The second target robot determination module 2004 determines a second target robot corresponding to each target bin in the matching waiting warehouse area from the empty second robot in the matching waiting warehouse area for each matching waiting warehouse area.

In one embodiment, the import warehouse area and the export warehouse area determination module 2001 include the following submodules.

The import warehouse area determination submodule determines the initial warehouse area as the import warehouse area when the current number of second robots in the initial warehouse area is less than the allocated number of the second robots in the initial warehouse area.

The export warehouse area determination submodule determines the initial warehouse area as the export warehouse area when the current number of second robots in the initial warehouse area is larger than the allocated number of the second robots in the initial warehouse area.

Here, the number of allocations of the second robot in the initial warehouse area is the ratio of the number of incomplete tasks in the initial warehouse area to the total number of incomplete tasks in the initial warehouse system and the total number of the second robots in the warehouse system. It is a product.

In one embodiment, the export second robot determination module 2002 includes the following submodules.

The second robot export number calculation submodule is based on the current number of second robots in the export warehouse area, the lower limit of the number of second robots, the number of second robots allocated, and the number of empty second robots. Calculate the number of second robots in the area.

The export second robot determination submodule determines the export second robot in the export warehouse area based on the number of exports of the second robot in the export warehouse area.

In one embodiment, the import second robot determination module 2003 includes the following submodules.

The second robot import number calculation submodule is based on the allocated number of the second robot in the import warehouse area, the current number of the second robots, and the upper limit of the number of the second robots, and the import of the second robot in the import warehouse area. Calculate the number.

The reference value calculation submodule is the ratio of the number of second robots in the import warehouse area to the total number of second robots in each import warehouse area and the total number of second robots in each export warehouse area. Use the product as a reference value.

The second robot actual demand determination submodule determines the minimum value of the reference value and the import number of the second robot in the import warehouse area as the actual demand number of the second robot in the import warehouse area.

The import second robot determination submodule imports the export second robot closest to the import warehouse area from the export second robot in each export warehouse area based on the actual demand number of the second robots in the import warehouse area. Select as the second robot to move into the warehouse area.

In one embodiment, the second target robot determination module 2004 includes the following submodules.

The second target robot determination submodule selects the second target robot corresponding to each station from the empty second robot in the matching waiting warehouse area based on the type of the allocation waiting task in the matching waiting warehouse area and the number of allocation waiting tasks. decide.

The task matching submodule matches the task waiting to be assigned to the station with the second target robot corresponding to the station.

In one embodiment, the second target robot determination submodule includes the following units:

The first variable weight calculation unit has the ratio of the number of assignment-waiting tasks to the sum of the number of allocation-waiting tasks for each allocation-waiting task type, the fixed weight of the allocation-waiting task type, and the allocation-waiting task type. The first variable weight of the type of task waiting to be assigned is calculated based on the initial variable weight of.

The second target robot allocation unit assigns one of the empty second robots in the matching waiting warehouse area as the second target robot to the station corresponding to the type of the assignment waiting task having the highest variable weight.

The second variable weight calculation unit has the ratio of the number of assignment-waiting tasks to the sum of the number of allocation-waiting tasks for each allocation-waiting task type, the fixed weight of the allocation-waiting task type, and the allocation-waiting task type. The second variable weight of the type of task waiting to be assigned is calculated based on the first variable weight of.

When both the number of vacant second robots waiting for allocation and the number of tasks waiting to be allocated are greater than 0, the circulation unit calculates the first variable weight, the second target robot allocation step, and the second variable weight. The steps are circulated, and the second variable weight of the task type waiting for allocation is set as the initial variable weight of the type of task waiting for allocation.

In one embodiment, the task matching submodule includes the following units:

The allocation value calculation unit calculates the allocation value of each allocation waiting task based on the priority of the assignment waiting task of the station and the distance between the target bin corresponding to the allocation waiting task and the station.

The target task determination unit extracts the allocation-waiting task having the highest allocation value from the allocation-waiting tasks as the target task according to the number of the second target robots in the station.

The target task matching unit sets a matching value for each second target robot that the second target robot matches with each target task based on the distance between the second target robot and the target bin corresponding to each target task. After calculation, the target task with the highest matching value is selected and matched with the second target robot.

The function of each module of the control device 2000 of the warehouse system of the sixth embodiment of the present application can be referred to the description corresponding to the control method of the third embodiment described above, and is omitted here.

FIG. 21 is a block diagram of a configuration of electronic equipment according to an embodiment of the present application. As shown in FIG. 21, the electronic equipment includes a memory 2101 and a processor 2102, which stores instructions that can be executed on the processor 2102. The method of controlling the warehouse system in any of the above embodiments is realized by the processor 2102 executing an instruction. The number of memory 2101 and processor 2102 may be one or more. Electronic equipment can represent various forms of digital computers such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, large computers, and other suitable computers. Electronic equipment can also represent various forms of mobile devices such as personal digital processing, mobile phones, smartphones, wearable equipment, and other similar computing devices. The components presented herein, their connections and relationships, and their functions are merely exemplary and may limit the implementation of those described herein and / or required herein. Not intended.

The electronic equipment may further include a communication interface 2103 for communicating with the external equipment and transmitting data. The equipment may be connected to each other using different buses and mounted on a common motherboard, or may be mounted in other ways as needed. The processor 2102 may process an instruction executed in the electronic equipment, and may display a graphic user interface (GUI) on an external input / output equipment (for example, a display equipment connected to the interface). Contains instructions for memory or graphical information stored in memory for. In other embodiments, a plurality of processors and / or a plurality of buses can be used with a plurality of memories and a plurality of memories, if necessary. Similarly, multiple electronic installations may be connected, each of which provides partially required operation (eg, as a server array, a set of blade servers, or a multiprocessor system). In FIG. 7, the processor 701 is taken as an example. The bus can be divided into an address bus, a data bus, a control bus and the like. In FIG. 21, for ease of display, only thick lines are shown, but it is not intended that there is only one bus or that there is only one type of bus.

Optionally, in a particular embodiment, if the memory 2101, processor 2102, and communication interface 2103 are integrated on a single chip, the memory 2101, processor 2102, and communication interface 2103 may be interconnected via an internal interface. Can communicate.

The above-mentioned processor may be a central processing unit (CPU), another general-purpose processor, a digital signal processor (Digital Signal Processing, DSP), an integrated circuit for a specific application (Application Specific Integrated Circuit, ASIC). ), Field Processor Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component and the like. The general-purpose processor may be a microprocessor, an arbitrary conventional processor, or the like. In particular, the processor may be a processor that supports the ARM (Advanced RISC Machines) architecture.

Embodiments of the present application, when executed by a processor, provide a computer-readable storage medium, such as memory 2101, that stores computer instructions that implement the methods provided in any of the embodiments of the present application.

Optionally, the memory 2101 stores a storage area of a program that can store an operating system or an application required for at least one function, data generated by the use of electronic equipment related to a speech synthesis method, and the like. It can include a storage area of data that can be created. Further, the memory 2101 may include a high speed random access memory or may include a non-transient solid-state storage device. For example, it can include at least one magnetic disk storage device, flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 2101 optionally includes memory configured remotely with respect to the processor 2102, even if these remote memories are connected to electronic equipment according to the speech synthesis method via a network. good. Examples of networks above include, but are not limited to, the Internet, corporate networks, local networks, mobile communication networks and combinations thereof.

In the present specification, terms such as "one embodiment", "several embodiments", "examples", "specific examples" or "partial examples" are described in the embodiments or examples. It is meant to be included in at least one embodiment or embodiment of the present invention by combining specific features, configurations, materials or features. Also, the specific features, configurations, materials or features described may be adequately coupled in any one or more embodiments or examples. Also, as long as there is no contradiction, those skilled in the art may combine or combine different embodiments or examples of the present specification and features in different embodiments or examples.

Also, the terms "first" and "second" do not indicate or imply relatively important, but are merely for illustration purposes and imply the number of technical features shown. Not really. Therefore, the features limited to "first" and "second" can include at least one feature, either explicitly or implicitly. In the description of this application, the meaning of "plurality" means two or more, except for being explicitly limited.

A description of any process or method described in a flow chart or other manner is one or more modules, fragments or segments capable of executing the code of a command to realize a particular logical function or step of a process. Moreover, the scope of the preferred embodiments of the present invention includes other realizations, in order of approximately simultaneous or vice versa based on such function, without following the order shown or described. It involves performing the function in accordance with this, which should be understood by those skilled in the art.

The logic and / or steps shown in the flowchart or otherwise described can be considered, for example, as a sequence list of executable commands for realizing a logical function, such as a command execution system. Provided or provided for use by equipment or equipment (computer-based systems, including processor systems or computer-based systems that include command execution systems, equipment, and other systems capable of obtaining and executing commands from equipment) or commands thereof. Can be specifically implemented on any computer readable medium for use in command execution systems, devices, or equipment that are used in combination.

Each part of the present invention can be realized by hardware, software, firmware or a combination thereof. In the above embodiment, the plurality of steps or methods can be performed by software or firmware stored in memory and executed by an appropriate command execution system. All or part of the steps of the method in the above embodiments indicate at run time the hardware associated with the program stored in a computer-readable storage medium containing one or a combination of the steps of the method in the embodiment. Can be realized by.

Further, each functional unit in each embodiment of the present invention may be integrated into one processing module, or may be a separate physical individual, and two or three or more units are integrated into one module. May be done. The above-mentioned integrated module may be realized by hardware or may be realized by a software function module. When the above integrated module is realized by a software function module and sold or used as an independent product, it may be stored in a computer-readable storage medium. The storage medium may be a read-only memory, a magnetic disk, an optical disk, or the like.

The above description is merely a specific embodiment of the present invention, and the scope of protection of the present invention is not limited thereto, and can be easily conceived by those skilled in the art within the scope disclosed in the present invention. All modifications or substitutions should be within the scope of the present invention. Therefore, the scope of the present invention should be in accordance with the stated claims.

Claims (10)

The target station is determined based on the cargo information of the task waiting for allocation, the task waiting for allocation includes a plurality of job lists, and the cargo information of the task waiting for allocation includes the cargo information of the target cargo corresponding to each job list. Determining the target station based on the cargo information of the task waiting for allocation, which is the type and quantity, sorts the target cargo corresponding to each job list from the target bin and selects the candidate station having the highest allocation efficiency value as the target station. And that
Select the current bin as a candidate bin that at least partially matches the cargo information of the pending assignment task based on the cargo information of each current bin, and target the candidate bin with the lowest transport cost from each of the candidate bins. By selecting as a bin, the bin is used to store cargo, the current bin is a bin placed in a storage rack, and the cargo information of the current bin is: The type and quantity of cargo in the current bottle ,
Based on the position information of the target bin, the robot having the closest distance to the target bin is determined as the target robot , and the position information of the target bin is the position information of the target bin of the storage rack in which the target bin is located. It is location information, and
Including controlling the target robot to transport the target bin to the target station.
The transport cost of the candidate bin satisfies the formula U1 = w1 (d1 / d1max) -w2 (s / smax) + w3 (n1 / n1max) + w4 (m1 / m1max) + w5 * f1.
In the above equation, U1 is the transport cost of the candidate bin, d1 is the distance from the candidate bin to the target station, d1max is the maximum value of the distance from the candidate bin to the target station, and s is the allocation. The number of cargoes in the candidate bin satisfying the cargo information of the waiting task, smax is the maximum number of cargoes in the candidate bin satisfying the cargo information of the waiting task, and n1 is the current value of the passage in which the candidate bin is located. Is the number of warehousing tasks, n1max is the maximum number of current warehousing tasks in the passage where each candidate bin is located, m1 is the number of stations assigned to the candidate bin, and m1max is. , The maximum value of the station assigned to the candidate bin, w1, w2, w3, w4, w5 are preset coefficients, and as f1, it is 1 when the candidate bin is in the storage space. A method of controlling a warehouse system, characterized in that it is 0 otherwise . Determining the target station based on the cargo information of the waiting task is
Selecting a station whose number of free storage spaces in each station is equal to or greater than the number of occupied storage spaces of the task waiting to be allocated is selected as a candidate station.
Based on the cargo information of the bins assigned to the candidate station, the distance between each bin and the candidate station, the cargo information of the bins not yet assigned to the candidate station, and the remaining cargo information of the pending task. , The allocation efficiency value of each candidate station is calculated , and the bins allocated to the candidate station are all the bins assigned to the candidate station, and the bins not yet allocated to the candidate station are bins. , All bins on the current storage rack that have not been assigned to the candidate station, and the cargo information for bins that have not yet been assigned to the candidate station is the type of cargo in the bin that has not yet been assigned to the candidate station. And the quantity, and the remaining cargo information of the awaiting task is the type and quantity of the remaining cargo of the awaiting task.
Including determining the candidate station having the highest allocation efficiency value as the target station.
The allocation efficiency value of the candidate station satisfies the formula I = (V + u * W1) * (1 + P) / C.
In the above formula, I is the allocation efficiency value of the candidate station, V is the number of the first cargo of the candidate station, W1 is the average efficiency value of the candidate station, and P is the priority of the task waiting for allocation. The first aspect of claim 1 , wherein C is the number of storage spaces to be occupied, and u is a preset value, which is a ratio between the degree value and the maximum priority value in the task waiting for allocation . Method. Determining the candidate bin with the lowest transport cost from each of the candidate bins as the target bin is possible.
It is to determine the remaining cargo information of the allocation waiting task based on the cargo information of the allocation waiting task and the cargo information of the bin allocated to the target station, and the remaining cargo information of the allocation waiting task. Is the remaining cargo information that is not filled in the allocated bin in the task waiting for allocation.
Based on the cargo information of each of the current bins, a bin that satisfies the remaining cargo information of the pending task is determined as a candidate bin, and the bin that satisfies the cargo information of the pending task is currently stored. At least a part of the cargo is a bin that matches the cargo information of the task waiting for allocation .
The method according to claim 1 or 2, wherein the transport cost of each candidate bin is calculated, and the candidate bin having the lowest transport cost is determined as the target bin. The target robot includes the first robot and includes the first robot.
Determining the target robot based on the position information of the target bin is
The target passage corresponding to the target bin is determined based on the position information of the target bin , and the passage adjacent to the storage rack in which the target bin is located is the target passage .
Including determining the first robot closest to the target bin as the first target robot based on the position of each first robot in the target passage.
The first target robot is used to transport the target bin from the storage space to the temporary storage space.
The storage rack has a plurality of storage spaces and a temporary storage space, and the temporary storage space is located below the plurality of storage spaces and at the bottom layer of the storage rack.
The method according to any one of claims 1 to 3 , wherein the temporary storage space is a position set during transportation of the target bin from the storage space to the target station . The target robot includes a second robot.
Determining the target robot based on the position information of the target bin is
Further including determining the second robot closest to the target bin as the second target robot based on the position information of the target bin.
The method according to any one of claims 1 to 4, wherein the second target robot is used to transport the target bin from the temporary storage space to the target station. After controlling the target robot to transport the target bin to the target station, the method
Controlling the second target robot to transport the target bin from the target station to the storage rack.
The method according to claim 5, further comprising controlling the second target robot so as to stay under an empty temporary storage space of the storage rack. To select the first robot that is vacant as the first robot waiting for matching,
Based on the position information of the target bin, the passage where the target bin is located is selected as the matching waiting passage.
For each of the matching waiting first robots, the corresponding target is based on the distance between the matching waiting first robot and each matching waiting passage and the number of assignment waiting tasks of each matching waiting passage. Determining the passage and the first target robot,
The method according to claim 1, wherein the task of waiting for allocation of the target passage is assigned to the corresponding first target robot. Selecting the aisle where the target bin is located as a matching waiting aisle is not possible.
To select a passage where the task waiting for allocation exists and the first robot does not exist as the first matching waiting passage.
When the number of the first matching waiting passages is smaller than the number of the matching waiting first robots, the passage in which the allocation waiting task exists and the first robot exists is selected as the second matching waiting passage. 7. The method according to claim 7, wherein the method comprises. Assigning the task of waiting for allocation of the target passage to the corresponding first target robot may be performed.
To calculate the number of tasks that can be assigned to the target passage,
When the number of assignable tasks is larger than 0, the corresponding number of work areas is divided in the target passage based on the number of the first target robots.
To select the first target robot whose number of assigned tasks is less than the upper limit threshold of the task as the first robot waiting for allocation,
The distance between the first robot waiting for allocation and the target bin corresponding to each assignable task and the first robot waiting for allocation have passed to move to the target bin corresponding to each assignable task. The method according to claim 8, wherein a target task is determined from the assignable tasks based on the number of work areas and assigned to the corresponding first robot waiting for allocation. Calculating the number of assignable tasks in the target passage
Add the minimum value of the number of assigned waiting warehousing tasks and the number of empty temporary storage spaces of the target aisle to the minimum value of the number of allocated waiting warehousing tasks and the number of empty storage spaces of the target aisle. Obtaining the first reference value and
The second reference value is obtained by subtracting the total number of assigned tasks of all the matched first robots from the value obtained by multiplying the number of the matched first robots by the upper limit threshold of the task.
The method according to claim 9, wherein the minimum value among the first reference value and the second reference value is selected as the number of assignable tasks of the target passage.

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