CN112633756A - Warehouse logistics scheduling method and related equipment - Google Patents

Warehouse logistics scheduling method and related equipment Download PDF

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CN112633756A
CN112633756A CN202011628041.7A CN202011628041A CN112633756A CN 112633756 A CN112633756 A CN 112633756A CN 202011628041 A CN202011628041 A CN 202011628041A CN 112633756 A CN112633756 A CN 112633756A
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付樟华
傅诗晴
刘擎权
朱熠耀
邓辅秦
林天麟
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Shenzhen Institute of Artificial Intelligence and Robotics
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Abstract

The application provides a warehouse logistics scheduling method and related equipment, which can reduce labor cost and improve working efficiency during warehouse logistics scheduling. The method comprises the following steps: generating a task order corresponding to each cargo area in the M cargo areas according to the task order information and the cargo storage information; allocating a grabbing robot and a freight robot to each cargo area according to the number of task orders allocated to each cargo area and the distance between each cargo area and a discharge area; sending the target task order to a target grabbing robot and a target freight robot; when the first robot detects other robots, receiving real-time position information sent by the first robot and a moving path of the first robot; judging whether a second robot which conflicts with the first robot exists in other robots or not based on the real-time position information, the moving path of the first robot and the moving paths of the other robots; and if so, sending the path planning instruction to the first robot or the second robot.

Description

Warehouse logistics scheduling method and related equipment
Technical Field
The application relates to the field of warehousing, in particular to a warehouse logistics scheduling method and related equipment.
Background
With the rapid development of the modern e-commerce logistics industry, the warehouse operation management pressure is higher and higher; in the logistics warehouse industry, the traditional operations of manual sorting, manual carrying, manual warehousing and the like are mostly adopted, so that the efficiency is low, and the problem that the labor consumption is high is always existed; meanwhile, due to manual operation, the height of the goods shelf is limited, and the goods are stored in a single mode.
In the past warehouse logistics application, amazon adopts a transfer robot to move the whole goods shelves to the packing platform for the workman to select, though some orders only need a few goods on certain goods shelves, still need carry whole goods shelves, has caused certain wasting of resources.
With the development of industrial technology, a lot of warehouses use a robot and human cooperation mode to sort and transport goods, the human is mainly responsible for goods picking work, and the robot transport vehicle is responsible for transportation work. In addition, in recent years, some studies have been made on a movable picking robot which can autonomously move to a target position of a cargo and transport the target cargo to a shipment position after picking the target cargo, but the picking robot needs to perform picking and transporting operations at the same time, and thus the work efficiency is low.
Disclosure of Invention
The application provides a warehouse logistics scheduling method and related equipment, which can reduce labor cost and improve working efficiency during warehouse logistics scheduling.
A first aspect of an embodiment of the present application provides a warehouse logistics scheduling method, including:
acquiring task order information corresponding to a target area, wherein the target area comprises N goods areas, and N is a positive integer greater than or equal to 1;
generating a task order corresponding to each cargo area in M cargo areas according to the task order information and the cargo storage information corresponding to the target area, wherein the M cargo areas are contained in the N cargo areas, M is a positive integer greater than or equal to 1, and M is less than or equal to N;
allocating a grabbing robot and a goods transporting robot to each goods area according to the number of the task orders allocated to each goods area and the distance between each goods area and a goods unloading area;
sending a target task order to a target grabbing robot and a target freight robot, so that the target grabbing robot and the target freight robot move to the position of a target cargo based on stored static map information, and move the target cargo to the unloading area through the target freight robot, wherein the target task order is a task order of any one of target cargo areas, the target cargo is any one of the target task orders, the target grabbing robot and the target freight robot are robots allocated to the target cargo areas, and the target cargo area is any one of the M cargo areas;
when a first robot detects that other robots exist in a preset range, receiving real-time position information sent by the first robot and a moving path of the first robot, wherein the first robot is any one of the target grabbing robot and the target delivery robot;
judging whether a second robot which conflicts with the first robot exists in the other robots based on the real-time position information, the moving path of the first robot and the moving paths of the other robots;
when the second robot exists in the other robots, a path planning instruction is sent to the first robot or the second robot, so that the first robot or the second robot replans a path according to the path planning instruction.
Optionally, the allocating a gripping robot and a freight robot for each cargo area according to the distance between the cargo area and the unloading area according to the number of task orders allocated to the cargo area comprises:
step 1, allocating a grabbing robot and a cargo carrying robot for each cargo area;
step 2, calculating the order task completion time length of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by using a grabbing robot and a cargo carrying robot which are distributed to each cargo area;
step 3, allocating a grabbing robot to the first goods area with the largest order task completion time in each goods area and allocating a delivery robot to the other goods areas except the first goods area in each goods area;
and 4, repeatedly executing the step 2 and the step 3 until the grabbing robot and the goods transporting robot are distributed.
Optionally, the calculating, by a grabbing robot and a transporting robot assigned to each cargo area, an order task completion duration of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area includes:
calculating the order task completion time length of each goods area by the following formula:
Figure BDA0002875417490000031
wherein t is the order task completion duration of a second cargo area, and the second cargo area is any one of the cargo areasA cargo area, n is the number of tasks in the second cargo area, djTheoretical working distance, d, for the gripping robot of the second cargo area to perform a single order taskyTheoretical working distance, n, for the cargo robots of the second cargo area to carry out the single order taskjNumber of gripping robots, n, for the second cargo areayThe number of the cargo robots of the second cargo area,
Figure BDA0002875417490000032
completing a work cycle of the single order task for the grabbing robot in the second cargo area,
Figure BDA0002875417490000033
completing a work cycle of the single order task for a cargo robot of the second cargo area.
Optionally, the method further comprises:
periodically checking the order task completion progress of each of the M cargo areas;
determining a third cargo area and a fourth cargo area based on the order task completion progress of each cargo area, wherein the third cargo area is the cargo area with the highest order task completion progress in the M cargo areas, and the fourth cargo area is the cargo area with the slowest order task completion progress in the M cargo areas;
assigning one of the cargo robots in the third cargo area to the fourth cargo area.
Optionally, the method further comprises:
judging whether a fifth goods area with completed order tasks exists in the M goods areas;
and if so, distributing the grabbing robot and the cargo robot corresponding to the fifth cargo area to the cargo area with the slowest order task completion progress in the M cargo areas.
The present application provides in a second aspect a warehouse logistics scheduling device, including:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring task order information corresponding to a target area, the target area comprises N goods areas, and N is a positive integer greater than or equal to 1;
a generating unit, configured to generate a task order corresponding to each of M cargo areas according to the task order information and the cargo storage information corresponding to the target area, where the M cargo areas are included in the N cargo areas, M is a positive integer greater than or equal to 1, and M is less than or equal to N;
the distribution unit is used for distributing the grabbing robot and the freight robot to each cargo area according to the number of the task orders distributed to each cargo area and the distance between each cargo area and the unloading area;
a sending unit, configured to send a target task order to a target grabbing robot and a target freight robot, so that the target grabbing robot and the target freight robot move to a position of a target cargo based on stored static map information, and move the target cargo to the unloading area through the target freight robot, where the target task order is a task order of any one of target cargo areas, the target cargo is any one of the target task orders, the target grabbing robot and the target freight robot are robots allocated to the target cargo areas, and the target cargo area is any one of the M cargo areas;
the receiving unit is used for receiving real-time position information sent by a first robot and a moving path of the first robot when the first robot detects that other robots exist in a preset range, wherein the first robot is any one of the target grabbing robot and the target delivery robot;
a determining unit, configured to determine whether a second robot that conflicts with the first robot exists among the other robots based on the real-time position information, the movement path of the first robot, and the movement paths of the other robots;
and the path planning unit is used for sending a path planning instruction to the first robot or the second robot when the second robot exists in the other robots, so that the first robot or the second robot replans a path according to the path planning instruction.
Optionally, the allocation unit is specifically configured to:
step 1, allocating a grabbing robot and a cargo carrying robot for each cargo area;
step 2, calculating the order task completion time length of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by using a grabbing robot and a cargo carrying robot which are distributed to each cargo area;
step 3, allocating a grabbing robot to the first goods area with the largest order task completion time in each goods area and allocating a delivery robot to the other goods areas except the first goods area in each goods area;
and 4, repeatedly executing the step 2 and the step 3 until the grabbing robot and the goods transporting robot are distributed.
Optionally, the calculating, by the allocation unit, the order task completion time length of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by using one grabbing robot and one cargo robot allocated to each cargo area includes:
calculating the order task completion time length of each goods area by the following formula:
Figure BDA0002875417490000051
wherein t is the order task completion duration of a second cargo area, the second cargo area is any one of the cargo areas, n is the task number of the second cargo area, and djTheoretical working distance, d, for the gripping robot of the second cargo area to perform a single order taskyTheoretical working distance, n, for the cargo robots of the second cargo area to carry out the single order taskjFor the second cargo areaNumber of persons, nyThe number of the cargo robots of the second cargo area,
Figure BDA0002875417490000052
completing a work cycle of the single order task for the grabbing robot in the second cargo area,
Figure BDA0002875417490000061
completing a work cycle of the single order task for a cargo robot of the second cargo area.
Optionally, the allocation unit is further configured to:
periodically checking the order task completion progress of each of the M cargo areas;
determining a third cargo area and a fourth cargo area based on the order task completion progress of each cargo area, wherein the third cargo area is the cargo area with the highest order task completion progress in the M cargo areas, and the fourth cargo area is the cargo area with the slowest order task completion progress in the M cargo areas;
assigning one of the cargo robots in the third cargo area to the fourth cargo area.
Optionally, the allocation unit is further configured to:
judging whether a fifth goods area with completed order tasks exists in the M goods areas;
and if so, distributing the grabbing robot and the cargo robot corresponding to the fifth cargo area to the cargo area with the slowest order task completion progress in the M cargo areas.
A third aspect of the embodiments of the present application provides a computer apparatus, which includes at least one connected processor and a memory, where the memory is used to store a program code, and the program code is loaded and executed by the processor to implement the steps of the warehouse logistics scheduling method according to the first aspect.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, which includes instructions that, when executed on a computer, cause the computer to perform the steps of the warehouse logistics scheduling method according to the first aspect.
In summary, it can be seen that, in the embodiment provided by the present application, when scheduling goods in a task order of a target area, a warehouse logistics scheduling device may allocate a grabbing robot and a freight robot to each goods area in the target area, which includes the obtained goods in the task order, and send static map information of the target area to each robot, and also obtain position information of each robot in real time during the operation of each robot, and when the robot conflicts with the operation path of another robot, re-plan the path of the robot. Therefore, compared with the existing method for carrying out warehouse logistics scheduling through manpower or through a sorting robot, the method not only reduces the labor cost, but also can improve the working efficiency during warehouse logistics scheduling.
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The above and other features, advantages and aspects of various embodiments of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
Fig. 1 is a schematic flow chart of a warehouse logistics scheduling method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a warehouse logistics scheduling device according to an embodiment of the present application;
FIG. 3 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present disclosure;
fig. 4 is a schematic hardware structure diagram of a server according to an embodiment of the present application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are for illustration purposes only and are not intended to limit the scope of the present application.
The terms "include" and variations thereof as used herein are inclusive and open-ended, i.e., "including but not limited to. The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present application are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this application are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that reference to "one or more" unless the context clearly dictates otherwise.
In order to better realize a warehouse logistics automation system, the warehouse logistics scheduling method is provided, and a warehouse scene of the method mainly comprises a goods storage area, a main traffic lane of a robot and a conveyor belt of a discharge area. The goods shelves at different positions in the warehouse are divided into goods shelf areas in different ranges according to a certain rule, a reasonable number of grabbing robots and carrying robots are distributed in each goods shelf area according to the distance between each goods shelf area and the unloading area, the task load capacity of each goods shelf area and other factors, the grabbing robots in each goods shelf area move to the front of the goods shelves to take down target goods on the goods shelves after receiving task information and hand over the target goods to the carrying robots corresponding to the goods shelf areas, and then the carrying robots carry the goods to the conveying belt positions of the unloading areas to unload the goods. Can realize snatching the goods from goods shelves and transport the full automatization process to the region of unloading, select and transport for current through selecting the robot realization, can improve work efficiency.
The warehouse logistics scheduling method provided by the present application is described below from the perspective of a warehouse logistics scheduling device, where the warehouse logistics scheduling device may be a server, or may also be a service unit in the server, and is not particularly limited.
Referring to fig. 1, fig. 1 is a schematic flow chart of a warehouse logistics scheduling method according to an embodiment of the present application, including:
101. and acquiring task order information corresponding to the target area.
In this embodiment, the warehouse logistics scheduling device may obtain task order information corresponding to a target area, where the target area includes N goods areas (that is, N shelf areas, and certainly, a plurality of shelves may also be stored in one goods area, and is not specifically limited), N is a positive integer greater than or equal to 1, and the task order information is a kind of goods to be transported and a quantity corresponding to the kind of goods, that is, the warehouse logistics scheduling device may obtain the kind of goods to be transported and the quantity corresponding to the kind of goods in the target area, where a manner of obtaining the task order information corresponding to the target area is not specifically limited, for example, obtaining the task order information by manual input may be also obtained by other manners.
102. And generating a task order corresponding to each cargo area in the M cargo areas according to the task order information and the cargo storage information corresponding to the target area.
In this embodiment, after obtaining the task order information, the warehouse logistics scheduling device may obtain the cargo storage information of the existing cargo in the target area to generate the task order information corresponding to each cargo area in the N cargo areas, wherein the goods storage information corresponding to the target area comprises the type and the quantity of each goods in the target area and the goods area for storing each goods, therefore, the warehouse logistics scheduling device can combine the task order information and the goods storage information to obtain a task order and issue the task order to each goods area in the M goods areas, the task order for each cargo area indicates the type of cargo and the quantity of cargo to be retrieved from the cargo area, the M cargo areas are contained in the N cargo areas, M is a positive integer greater than or equal to 1, and M is less than or equal to N, namely, the M cargo areas are cargo areas with the required cargo in the N cargo areas.
103. And allocating a grabbing robot and a freight robot for each cargo area according to the number of the task orders allocated to each cargo area and the distance between each cargo area and the unloading area.
In this embodiment, after generating the task order corresponding to each cargo area in the M cargo areas, the warehouse logistics scheduling device may first allocate the task order to each cargo area, acquire the cargo storage information of the cargo stored in the target area, and then allocate the gripping robot and the cargo transporting robot to each cargo area according to the number of the task orders allocated to each cargo area and the distance between each cargo area and the unloading area.
In one embodiment, the warehouse logistics scheduling device allocates a grabbing robot to each cargo area according to the number of the task orders allocated to each cargo area and the distance between each cargo area and the unloading area, and the freight robot comprises:
step 1, allocating a grabbing robot and a cargo carrying robot for each cargo area;
step 2, calculating the order task completion time of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by one grabbing robot and one cargo robot which are distributed to each cargo area;
step 3, allocating a grabbing robot to the first goods area with the largest order task completion time in each goods area and allocating a goods transporting robot to the other goods areas except the first goods area in each goods area;
and 4, repeatedly executing the step 2 and the step 3 until the grabbing robot and the goods transporting robot are distributed.
In this embodiment, the warehouse logistics scheduling device may first obtain the number of the grabbing robots and the number of the freight robots in inventory, then traverse the M freight areas, respectively allocate one grabbing robot and one freight robot to each of the M freight areas, calculate the order task completion duration of each freight area according to the order task number of each freight area and the distance between each freight area and the unloading area by using one grabbing robot and one freight robot allocated to each freight area, allocate one grabbing robot to the first freight area with the largest order task completion duration in each freight area, allocate one freight robot to the other freight areas except the first freight area in each freight area, and repeatedly execute the above steps until the grabbing robots and the freight robots are completely allocated.
It should be noted that the warehouse logistics scheduling package can calculate the order task completion time of each cargo area by the following formula:
Figure BDA0002875417490000101
wherein t is the order task completion duration of the second cargo area, the second cargo area is any one cargo area in each cargo area, n is the task number of the second cargo area, djTheoretical working distance, d, for the gripping robot of the second cargo area to perform a single order taskyTheoretical working distance, n, for carrying out a single order task for a cargo robot in a second cargo areajNumber of gripping robots, n, for the second cargo areayThe number of the cargo robots of the second cargo area,
Figure BDA0002875417490000102
the work cycle for completing a single order task for the gripping robot in the second cargo area,
Figure BDA0002875417490000103
completing a work cycle of a single order task for the cargo robots of the second cargo area.
It should be noted that, in the above description, when allocating the gripping robots and the cargo robots, the robot is allocated one at a time, and certainly, in practical applications, a plurality of robots may be allocated at a time according to the number of the gripping robots and the number of the cargo robots, and the specific limitation is not limited as long as the gripping robots and the cargo robots corresponding to each cargo area can be allocated according to the above manner.
104. And sending the target task order to the target grabbing robot and the target freight robot so that the target grabbing robot and the target freight robot move to the position of the target freight area based on the stored static map information, and moving the target freight to the unloading area through the target freight robot.
In this embodiment, the warehouse logistics scheduling device may send the target task order to the target grabbing robot and the target freight robot, that is, after the warehouse logistics scheduling device allocates the grabbing robot and the freight robot to each of the M freight zones and sends the static map information of the target area to each grabbing robot and each freight robot, the warehouse logistics scheduling device may send the task order of each of the M freight zones to the grabbing robot and the freight robot of each freight zone, so that when receiving the task order, the grabbing robot of each freight zone may plan a path and move from the current position to the position of the target freight, and meanwhile, the freight robot may also move from the current position to the position of the target freight according to the received task order, and the grabbing robot may hand over the target freight to the freight robot, the goods conveying robot conveys the target goods to the unloading area to cooperatively finish a goods conveying task; the target task order is any one task order in a target cargo area, the target cargo is any one cargo in the target task order, the target grabbing robot and the target cargo carrying robot are robots distributed in the target cargo area, and the target cargo area is any one cargo area in the M cargo areas; in this way, the goods in the task order corresponding to each goods area can be conveyed to the unloading area through the cooperation of the grabbing robot and the goods conveying robot.
It should be noted that, before sending the target task order to the target pick-up robot and the target delivery robot, the warehouse logistics scheduling device may further determine whether the target pick-up robot and the target delivery robot account for a target area or not, determine whether the static map information of the target area is updated or not, and if so, obtain the static map information of the target area, where the static map information includes, but is not limited to, a location of each of the M delivery areas (that is, a location of each of the M delivery areas, where a delivery area includes a shelf as an example, it is needless to say that each of the delivery areas may also include a plurality of shelves, and when each of the delivery areas includes a plurality of shelves, the static map information may include locations of a plurality of shelves of each of the delivery areas), and road information in the target area, (i.e., road information on which the pick-up robot and the delivery robot can travel) the location of the unloading area and the storage information of the goods, and then transmits the static map information of the target area to the target pick-up robot and the target delivery robot. If the static map information of the target area is stored in the target grabbing robot and the target shipping robot and is not changed, the static map information of the target area does not need to be sent.
105. When the first robot detects that other robots exist in the preset range, the real-time position information sent by the first robot and the moving path of the first robot are received.
In this embodiment, since each of the grabbing robots and each of the shipping robots cannot acquire the position information of other robots, in order to avoid collision between the robots and paths of other robots during the operation process, when the first robot detects that other robots exist within a preset range (for example, within 5 meters around), the first robot may send its own real-time position information and its own moving path to the warehouse logistics scheduling device during the operation process, and thus, the warehouse logistics scheduling device may receive its own real-time position information and moving path sent by the first robot when the first robot detects that other robots exist within the preset range, and the first robot grabs any one of the robots and the target shipping robot for the target.
106. And judging whether a second robot which conflicts with the first robot exists in other robots or not based on the real-time position information, the moving path of the first robot and the moving paths of the other robots, and if so, executing step 107.
In this embodiment, the warehouse logistics scheduling device may obtain the moving paths of the other robots after obtaining the real-time position information of the first robot and the moving paths of the first robot, then determine whether a second robot having a conflict with the moving paths of the first robot exists in the other robots according to the real-time position information, the moving paths of the first robot and the moving paths of the other robots, and if so, execute step 107. The manner of determination is not particularly limited, and it is sufficient if it can be determined whether or not there is a second robot that conflicts with the first robot among the other robots.
107. When a second robot exists in the other robots, the path planning instruction is sent to the first robot or the second robot, so that the first robot or the second robot replans the path according to the path planning instruction.
In this embodiment, when determining that a second robot having a path conflict with the first robot exists among the other robots, the warehouse logistics scheduling device may send the path planning instruction to the first robot or the second robot, so that the first robot or the second robot replans the path according to the path planning instruction, thereby avoiding the conflict; that is to say, in the operation process of each robot, when other robots appear in the preset range of the robot, the warehouse logistics scheduling device acquires the position information of the robot, the moving path of the robot and the moving paths of the other robots appearing in the preset range of the robot, and judges whether the moving positions of the robot and the other robots conflict or not according to the position information of the robot, the moving paths and the moving paths of the other robots, and when the conflicting robots exist, the warehouse logistics scheduling device sends a path planning instruction to the two conflicting robots so that the two robots plan the path again, thereby avoiding the conflict; and then checking whether the task order in each goods area is finished, if so, finishing the logistics scheduling work, otherwise, repeatedly executing the steps until the task order is finished.
It should be noted that, in practical application, the warehouse logistics scheduling device may determine which robot performs path planning again according to the priority of the robot, and the warehouse logistics scheduling device may further obtain the priorities of the first robot and the second robot, and send the path planning instruction only to the robot with the low priority, so that the robot with the low priority performs path planning again according to the path planning instruction, and thus, it may be ensured that the robot with the high priority has high-level permission, and order tasks are completed as quickly as possible. The priority is related to the demand time of the goods to be dispatched and the valuability of the goods, the priority of the robot serving the goods with high priority is correspondingly high, the warehouse logistics dispatching device can maintain a mapping relation in advance to determine the priority, the mapping relation is the mapping relation between the demand time of the goods or the valuability of the goods and the priority, and of course, the mapping relation between other goods attributes and the priority can be also used, and the method is not limited specifically.
It should be noted that the main factors affecting the total transit time of a single cargo area are the number of robots servicing the cargo area, the number of tasks in the cargo area and the distance of the cargo area to the conveyor belt. In order to ensure that each goods area can finish all tasks as soon as possible, the finishing speed of each area needs to be balanced, and it is particularly important to arrange a reasonable number of robots for each area, so that the robots need to be pre-distributed according to the characteristics of each goods area, and each area is ensured to finish tasks according to a similar schedule. After a task is executed for a certain time, calculating the task completion progress according to the completed task and the uncompleted task of each cargo area, obtaining an area with a faster progress and an area with a slower progress as alternative areas for dynamic adjustment, calculating the estimated completion condition of the alternative areas after dynamic adjustment, and selecting the condition with the best effect as a scheme for dynamic adjustment; if some areas finish the tasks of the whole area in advance, the robot can move to other areas to continue helping other areas finish the tasks.
In one embodiment, the warehouse logistics scheduling device can periodically check the completion progress of the order task of each of the M cargo areas;
determining a third cargo area and a fourth cargo area based on the order task completion progress of each cargo area, wherein the third cargo area is the cargo area with the fastest order progress completion progress in the M cargo areas, and the fourth cargo area is the cargo area with the slowest order task completion progress in the M cargo areas;
one of the cargo robots in the third cargo area is assigned to a fourth cargo area.
In this embodiment, the warehouse logistics scheduling device may periodically check the order task completion degree of each of the M cargo areas during the process of transporting the cargo by the robot, determine a third cargo area with the fastest order task completion progress and a fourth cargo area with the slowest order task completion progress, and then allocate one cargo transporting robot in the third cargo area to the fourth cargo area for use, thereby ensuring that the cargo in each cargo area is completed as soon as possible.
In addition, although the above description is given by taking the example of allocating one cargo robot, a plurality of cargo robots may be allocated in an actual operation process, and the present invention is not limited to this.
It should be further noted that, the warehouse logistics scheduling device may further determine whether a fifth goods area where the order task is completed exists in the M goods areas during the operation of the robot, and if so, allocate the grasping robot and the cargo transporting robot corresponding to the fifth goods area to the goods area where the order task is completed in the M goods areas with the slowest progress, so as to ensure that all the goods areas in the M goods areas complete the logistics scheduling task as fast as possible. In addition, in practical application, the robots in the fifth cargo area may not be all allocated to the cargo area with the slowest order task completion progress, and the robots in the fifth cargo area may be allocated to the cargo area with the slowest order task completion progress and may be allocated to other cargo areas with a slower order task completion progress, and certainly, the robots in the fifth cargo area may also be allocated to the cargo area with the fastest order task completion progress among the other cargo areas except the fifth cargo area among the M cargo areas, so as to accelerate the order task completion speed of the cargo area, so as to release more robots to be allocated to other acquisition areas.
In summary, it can be seen that, in the embodiment provided by the present application, when scheduling goods in a task order of a target area, a warehouse logistics scheduling device may allocate a grabbing robot and a freight robot to each goods area in the target area, which includes the obtained goods in the task order, and send static map information of the target area to each robot, and also obtain position information of each robot in real time during the operation of each robot, and when the robot conflicts with the operation path of another robot, re-plan the path of the robot. Therefore, compared with the existing method for carrying out warehouse logistics scheduling through manpower or through a sorting robot, the method not only reduces the labor cost, but also can improve the working efficiency during warehouse logistics scheduling.
It is to be understood that the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The names of messages or information exchanged between a plurality of devices in the embodiments of the present application are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Although the operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous.
It should be understood that the various steps recited in the method embodiments of the present application may be performed in a different order and/or in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present application is not limited in this respect.
Additionally, the present application may also be written with computer program code for performing the operations of the present application in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The present application is described above from the perspective of a warehouse logistics scheduling method, and the present application is described below from the perspective of a warehouse logistics scheduling device.
Referring to fig. 2, fig. 2 is a schematic view of a virtual structure of a warehouse logistics dispatching device according to an embodiment of the present application, where the warehouse logistics dispatching device 200 includes:
the system comprises an acquisition unit 201, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring task order information corresponding to a target area, the target area comprises N cargo areas, and N is a positive integer greater than or equal to 1;
a generating unit 202, configured to generate a task order corresponding to each cargo area in M cargo areas according to the task order information and the cargo storage information corresponding to the target area, where the M cargo areas are included in the N cargo areas, M is a positive integer greater than or equal to 1, and M is less than or equal to N;
an allocation unit 203, configured to allocate a gripping robot and a cargo-handling robot to each cargo area according to the number of task orders allocated to each cargo area and the distance between each cargo area and a discharge area;
a sending unit 204, configured to send a target task order to a target grabbing robot and a target freight robot, so that the target grabbing robot and the target freight robot move to a position of a target freight based on stored static map information, and move the target freight to the unloading area through the target freight robot, where the target task order is a task order of any one of target freight areas, the target freight is any one of the target task orders, the target grabbing robot and the target freight robot are robots allocated to the target freight areas, and the target freight area is any one of the M freight areas;
a receiving unit 205, configured to receive, when a first robot detects that there are other robots within a preset range, real-time position information sent by the first robot and a moving path of the first robot, where the first robot is any one of the target grabbing robot and the target cargo transporting robot;
a determining unit 206, configured to determine whether a second robot that conflicts with the first robot exists in the other robots based on the real-time position information, the moving path of the first robot, and the moving paths of the other robots;
a path planning unit 207, configured to send a path planning instruction to the first robot or the second robot when the second robot exists in the other robots, so that the first robot or the second robot re-plans a path according to the path planning instruction.
Optionally, the allocating unit 203 is specifically configured to:
step 1, allocating a grabbing robot and a cargo carrying robot for each cargo area;
step 2, calculating the order task completion time length of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by using a grabbing robot and a cargo carrying robot which are distributed to each cargo area;
step 3, allocating a grabbing robot to the first goods area with the largest order task completion time in each goods area and allocating a delivery robot to the other goods areas except the first goods area in each goods area;
and 4, repeatedly executing the step 2 and the step 3 until the grabbing robot and the goods transporting robot are distributed.
Optionally, the calculating, by the allocation unit 203, the order task completion time length of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by using one grabbing robot and one cargo robot allocated to each cargo area includes:
calculating the order task completion time length of each goods area by the following formula:
Figure BDA0002875417490000171
wherein t is the order task completion duration of a second cargo area, the second cargo area is any one of the cargo areas, and n isNumber of tasks of said second cargo area, djTheoretical working distance, d, for the gripping robot of the second cargo area to perform a single order taskyTheoretical working distance, n, for the cargo robots of the second cargo area to carry out the single order taskjNumber of gripping robots, n, for the second cargo areayThe number of the cargo robots of the second cargo area,
Figure BDA0002875417490000172
completing a work cycle of the single order task for the grabbing robot in the second cargo area,
Figure BDA0002875417490000181
completing a work cycle of the single order task for a cargo robot of the second cargo area.
Optionally, the allocating unit 203 is further configured to:
periodically checking the order task completion progress of each of the M cargo areas;
determining a third cargo area and a fourth cargo area based on the order task completion progress of each cargo area, wherein the third cargo area is the cargo area with the highest order task completion progress in the M cargo areas, and the fourth cargo area is the cargo area with the slowest order task completion progress in the M cargo areas;
assigning one of the cargo robots in the third cargo area to the fourth cargo area.
Optionally, the allocating unit 203 is further configured to:
judging whether a fifth goods area with completed order tasks exists in the M goods areas;
and if so, distributing the grabbing robot and the cargo robot corresponding to the fifth cargo area to the cargo area with the slowest order task completion progress in the M cargo areas.
In summary, it can be seen that, in the embodiment provided by the present application, when scheduling goods in a task order of a target area, a warehouse logistics scheduling device may allocate a grabbing robot and a freight robot to each goods area in the target area, which includes the obtained goods in the task order, and send static map information of the target area to each robot, and also obtain position information of each robot in real time during the operation of each robot, and when the robot conflicts with the operation path of another robot, re-plan the path of the robot. Therefore, compared with the existing method for carrying out warehouse logistics scheduling through manpower or through a sorting robot, the method not only reduces the labor cost, but also can improve the working efficiency during warehouse logistics scheduling.
It should be noted that the units described in the embodiments of the present application may be implemented by software, and may also be implemented by hardware. Here, the name of the unit does not constitute a limitation of the unit itself in some cases, and for example, the acquisition unit may also be described as "a unit that acquires credential information of a target user".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
Referring to fig. 3, fig. 3 is a schematic diagram of an embodiment of a computer-readable storage medium according to the present invention.
As shown in fig. 3, the embodiment provides a computer-readable storage medium 300, on which a computer program 311 is stored, and the computer program 311 is executed by a processor to implement the steps of the warehouse logistics scheduling method described in fig. 1.
In the context of this application, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may be a machine readable signal medium or a machine readable storage medium. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It should be noted that the computer readable storage medium mentioned above in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
Referring to fig. 4, fig. 4 is a schematic diagram of a hardware structure of a server according to an embodiment of the present disclosure, where the server 400 may have a relatively large difference due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 422 (e.g., one or more processors) and a memory 432, and one or more storage media 430 (e.g., one or more mass storage devices) storing an application 442 or data 444. Wherein the memory 432 and storage medium 430 may be transient or persistent storage. The program stored on the storage medium 430 may include one or more modules (not shown), each of which may include a series of instruction operations for the server. Still further, the central processor 422 may be arranged to communicate with the storage medium 430, and execute a series of instruction operations in the storage medium 430 on the server 400.
The server 400 may also include one or more power supplies 426, one or more wired or wireless network interfaces 450, one or more input-output interfaces 458, and/or one or more operating systems 441, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so forth.
The steps performed by the warehouse logistics scheduling device in the above embodiment may be based on the server structure shown in fig. 4.
It should be further noted that, according to the embodiment of the present application, the processes of the warehouse logistics scheduling method described in the flowchart in fig. 1 above may be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated in the flow chart diagram of fig. 1 described above.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
While several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the application. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the disclosure. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.

Claims (10)

1. A warehouse logistics scheduling method, comprising:
acquiring task order information corresponding to a target area, wherein the target area comprises N goods areas, and N is a positive integer greater than or equal to 1;
generating a task order corresponding to each cargo area in M cargo areas according to the task order information and the cargo storage information corresponding to the target area, wherein the M cargo areas are contained in the N cargo areas, M is a positive integer greater than or equal to 1, and M is less than or equal to N;
allocating a grabbing robot and a goods transporting robot to each goods area according to the number of the task orders allocated to each goods area and the distance between each goods area and a goods unloading area;
sending a target task order to a target grabbing robot and a target freight robot, so that the target grabbing robot and the target freight robot move to the position of a target cargo based on stored static map information, and move the target cargo to the unloading area through the target freight robot, wherein the target task order is a task order of any one of target cargo areas, the target cargo is any one of the target task orders, the target grabbing robot and the target freight robot are robots allocated to the target cargo areas, and the target cargo area is any one of the M cargo areas;
when a first robot detects that other robots exist in a preset range, receiving real-time position information sent by the first robot and a moving path of the first robot, wherein the first robot is any one of the target grabbing robot and the target delivery robot;
judging whether a second robot which conflicts with the first robot exists in the other robots based on the real-time position information, the moving path of the first robot and the moving paths of the other robots;
when the second robot exists in the other robots, a path planning instruction is sent to the first robot or the second robot, so that the first robot or the second robot replans a path according to the path planning instruction.
2. The method of claim 1, wherein the assigning a pick robot and a ship robot to each cargo area according to the number of task orders assigned to the each cargo area to the distance of the each cargo area from a discharge area comprises:
step 1, allocating a grabbing robot and a cargo carrying robot for each cargo area;
step 2, calculating the order task completion time length of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by using a grabbing robot and a cargo carrying robot which are distributed to each cargo area;
step 3, allocating a grabbing robot to the first goods area with the largest order task completion time in each goods area and allocating a delivery robot to the other goods areas except the first goods area in each goods area;
and 4, repeatedly executing the step 2 and the step 3 until the grabbing robot and the goods transporting robot are distributed.
3. The method of claim 2, wherein calculating the order task completion time for each cargo area based on the order task quantity for each cargo area and the distance of each cargo area from the drop-off area via a pick-up robot and a delivery robot assigned to each cargo area comprises:
calculating the order task completion time length of each goods area by the following formula:
Figure FDA0002875417480000021
wherein t is the order task completion duration of a second cargo area, the second cargo area is any one of the cargo areas, n is the task number of the second cargo area, and djTheoretical working distance, d, for the gripping robot of the second cargo area to perform a single order taskyTheoretical working distance, n, for the cargo robots of the second cargo area to carry out the single order taskjNumber of gripping robots, n, for the second cargo areayThe number of the cargo robots of the second cargo area,
Figure FDA0002875417480000022
completing a work cycle of the single order task for the grabbing robot in the second cargo area,
Figure FDA0002875417480000031
completing a work cycle of the single order task for a cargo robot of the second cargo area.
4. The method according to any one of claims 1 to 3, further comprising:
periodically checking the order task completion progress of each of the M cargo areas;
determining a third cargo area and a fourth cargo area based on the order task completion progress of each cargo area, wherein the third cargo area is the cargo area with the highest order task completion progress in the M cargo areas, and the fourth cargo area is the cargo area with the slowest order task completion progress in the M cargo areas;
assigning one of the cargo robots in the third cargo area to the fourth cargo area.
5. The method according to any one of claims 1 to 3, further comprising:
judging whether a fifth goods area with completed order tasks exists in the M goods areas;
and if so, distributing the grabbing robot and the cargo robot corresponding to the fifth cargo area to the cargo area with the slowest order task completion progress in the M cargo areas.
6. A warehouse logistics dispatching device, comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring task order information corresponding to a target area, the target area comprises N goods areas, and N is a positive integer greater than or equal to 1;
a generating unit, configured to generate a task order corresponding to each of M cargo areas according to the task order information and the cargo storage information corresponding to the target area, where the M cargo areas are included in the N cargo areas, M is a positive integer greater than or equal to 1, and M is less than or equal to N;
the distribution unit is used for distributing the grabbing robot and the freight robot to each cargo area according to the number of the task orders distributed to each cargo area and the distance between each cargo area and the unloading area;
a sending unit, configured to send a target task order to a target grabbing robot and a target freight robot, so that the target grabbing robot and the target freight robot move to a position of a target cargo based on stored static map information, and move the target cargo to the unloading area through the target freight robot, where the target task order is a task order of any one of target cargo areas, the target cargo is any one of the target task orders, the target grabbing robot and the target freight robot are robots allocated to the target cargo areas, and the target cargo area is any one of the M cargo areas;
the receiving unit is used for receiving real-time position information sent by a first robot and a moving path of the first robot when the first robot detects that other robots exist in a preset range, wherein the first robot is any one of the target grabbing robot and the target delivery robot;
a determining unit, configured to determine whether a second robot that conflicts with the first robot exists among the other robots based on the real-time position information, the movement path of the first robot, and the movement paths of the other robots;
and the path planning unit is used for sending a path planning instruction to the first robot or the second robot when the second robot exists in the other robots, so that the first robot or the second robot replans a path according to the path planning instruction.
7. The apparatus according to claim 6, wherein the allocation unit is specifically configured to:
step 1, allocating a grabbing robot and a cargo carrying robot for each cargo area;
step 2, calculating the order task completion time length of each cargo area according to the order task quantity of each cargo area and the distance between each cargo area and the unloading area by using a grabbing robot and a cargo carrying robot which are distributed to each cargo area;
step 3, allocating a grabbing robot to the first goods area with the largest order task completion time in each goods area and allocating a delivery robot to the other goods areas except the first goods area in each goods area;
and 4, repeatedly executing the step 2 and the step 3 until the grabbing robot and the goods transporting robot are distributed.
8. The apparatus according to claim 6 or 7, wherein the allocation unit is further configured to:
periodically checking the order task completion progress of each of the M cargo areas;
determining a third cargo area and a fourth cargo area based on the order task completion progress of each cargo area, wherein the third cargo area is the cargo area with the highest order task completion progress in the M cargo areas, and the fourth cargo area is the cargo area with the slowest order task completion progress in the M cargo areas;
assigning one of the cargo robots in the third cargo area to the fourth cargo area.
9. The apparatus according to claim 6 or 7, wherein the allocation unit is further configured to:
judging whether a fifth goods area with completed order tasks exists in the M goods areas;
and if so, distributing the grabbing robot and the cargo robot corresponding to the fifth cargo area to the cargo area with the slowest order task completion progress in the M cargo areas.
10. A computer-readable storage medium, comprising instructions which, when executed on a computer, cause the computer to perform the steps of the warehouse logistics scheduling method of any one of the preceding claims 1 to 5.
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