Route planning method and device

Abstract

The invention provides a route planning method and device, and relates to the field of intelligent storage. The method comprises the steps of determining seed tasks which must be executed by a robot according to priorities of tasks and distances between the robot and storage positions corresponding to the tasks, determining a to-be-planned task set based on the seed tasks, and determining a to-be-planned task set according to a result of selecting each task and each road section which enable the route of an objective function to be shortest under the condition that constraint conditions are met. And determining a task set needing to be executed by the robot and an execution route. Therefore, under the condition that the task priority is guaranteed, the overall route is shortest, and the overall efficiency is maximized.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent warehousing, and in particular to a robot route planning method and device. Background Art

[0002] Smart warehousing refers to the use of advanced technology and intelligent systems to achieve warehouse management and logistics operations. It integrates technologies such as the Internet of Things, artificial intelligence, and big data analysis to automatically and intelligently complete the storage, sorting, distribution, and management of items in the warehouse, thereby improving the efficiency and accuracy of the warehouse.

[0003] In smart warehousing, robots play an important role. They can automatically perform various tasks, such as moving goods and sorting commodities, according to preset programs or instructions. The use of robots greatly reduces the time and cost of manual operation and improves the operational efficiency of warehousing.

[0004] In some related technologies, the robot is planned to execute the task route according to the time sequence of the tasks, so that the tasks issued first are executed first. The overall route planned in this way may be relatively long, affecting the overall efficiency. Summary of the invention

[0005] In the disclosed embodiment, the seed tasks that the robot must perform are determined according to the priority of the tasks and the distance between the robot and the storage location corresponding to the tasks. Based on the seed tasks, the set of tasks to be planned is determined. According to the result of selecting the tasks and the sections that make the route of the objective function the shortest under the condition of satisfying the constraints, the set of tasks and the execution route that the robot needs to perform are determined. Thus, the overall route is made shortest and the overall efficiency is maximized while ensuring the priority of the tasks.

[0006] Some embodiments of the present disclosure propose a route planning method, including: determining a seed task that the robot must perform based on the priority of the task and the distance between the robot and the storage location corresponding to the task; determining a first task set based on the seed task; constructing a first objective function to achieve the shortest route based on whether each road section between each task and each storage location corresponding to the first task set is selected and the distance of each road section; determining a first constraint condition of the first objective function; and determining a second task set and an execution route that the robot needs to perform based on the result that each task and each road section that makes the route of the first objective function the shortest while satisfying the first constraint condition are selected.

[0007] In some embodiments, determining the seed task that the robot must perform includes: selecting the storage location closest to the robot as the seed storage location from the storage locations corresponding to a group of tasks with the highest priority; and determining the task corresponding to the seed storage location as the seed task that the robot must perform.

[0008] In some embodiments, determining the first task set includes: adding a seed task to the first task set; and selecting a task from non-seed tasks of the same task type as the seed task to add to the first task set.

[0009] In some embodiments, the first constraint includes that all storage slots of the seed task must be selected.

[0010] In some embodiments, the first constraint condition also includes one or more of the following: all storage locations of a task are selected at the same time or not selected at the same time; the starting point is the current position of the robot and has only outgoing edges; a storage location is selected at most once; a storage location, when selected, has outgoing edges and incoming edges.

[0011] In some embodiments, when the seed task involves a picking task, the first constraint condition also includes one or more of the following: the destination point is a dumping point and has only incoming edges; at most n tasks are selected, where n is the number of idle temporary storage devices of the robot, and each temporary storage device is used to place the goods corresponding to a task.

[0012] In some embodiments, it also includes: determining the remaining unexecuted tasks in the second task set; adding the remaining tasks and other tasks of the same task type as the remaining tasks to the third task set; constructing a second objective function to achieve the shortest route based on whether the various sections between the various tasks and storage locations corresponding to the third task set are selected and the distances of the various sections; determining the second constraint condition of the second objective function; and determining the fourth task set and execution route that the robot needs to execute based on the result of selecting the various tasks and various sections that make the route of the second objective function the shortest while satisfying the second constraint condition.

[0013] In some embodiments, the second constraint includes: all storage locations corresponding to the remaining tasks must be selected.

[0014] In some embodiments, the second constraint also includes one or more of the following: all storage locations of a task are selected or not selected at the same time; the starting point is the current position of the robot and has only outgoing edges; a storage location is selected at most once; a storage location, when selected, has outgoing edges and incoming edges.

[0015] In some embodiments, when the seed task involves a picking task, the second constraint condition also includes one or more of the following: the destination point is a dumping point and has only incoming edges; at most m tasks are added, where m is the number of remaining temporary storage devices of the robot, and each temporary storage device is used to place the goods corresponding to a task.

[0016] In some embodiments, it also includes: determining the priority of the task based on at least one of the wave mode, task type, order type, and confluence time corresponding to the task.

[0017] Some embodiments of the present disclosure provide a route planning device, comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute a route planning method based on instructions stored in the memory.

[0018] Some embodiments of the present disclosure provide a route planning device, including: a module for executing a route planning method.

[0019] Some embodiments of the present disclosure provide a computer-readable storage medium having a computer program stored thereon, which implements the steps of a route planning method when executed by a processor.

[0020] Some embodiments of the present disclosure provide a computer program product, including a computer program, which implements the steps of the route planning method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The following is a brief introduction to the drawings required for use in the embodiments or related technical descriptions. The present disclosure can be more clearly understood according to the following detailed description with reference to the drawings.

[0022] Obviously, the drawings described below are only some embodiments of the present disclosure, and a person skilled in the art can obtain other drawings based on these drawings without creative work.

[0023] Figure 1 Schematic diagram showing shelves and robots according to some embodiments of the present disclosure.

[0024] Figure 2 and Figure 3 Schematic diagrams of the picking robot according to some embodiments of the present disclosure are shown in front view and rear view respectively.

[0025] Figure 4 A schematic diagram showing warehouse map data according to some embodiments of the present disclosure.

[0026] Figure 5 A schematic diagram showing an overall route planning method according to some embodiments of the present disclosure.

[0027] Figure 6 A schematic diagram showing an initial route planning method according to some embodiments of the present disclosure.

[0028] Figure 7 A schematic diagram showing initial route planning results according to some embodiments of the present disclosure.

[0029] Figure 8 A schematic diagram showing an additional route planning method according to some embodiments of the present disclosure.

[0030] Fig. 9 A schematic diagram showing additional route planning results according to some embodiments of the present disclosure.

[0031] Fig.10 A schematic diagram showing the structure of a route planning device according to some embodiments of the present disclosure.

[0032] Fig.11 A schematic diagram showing the structure of a route planning device according to some embodiments of the present disclosure.

[0033] Fig.12 A schematic diagram showing a route planning system according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0034] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

[0035] Those skilled in the art can understand that the terms "first" and "second" in the embodiments of the present disclosure are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0036] It should also be understood that in the embodiments of the present disclosure, “plurality” may refer to two or more than two, and “at least one” may refer to one, two, or more than two.

[0037] It should also be understood that any component, data or structure mentioned in the embodiments of the present disclosure can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0038] In addition, the term "and / or" in the present disclosure is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present disclosure generally indicates that the associated objects before and after are in an "or" relationship.

[0039] It should also be understood that the description of the various embodiments in the present disclosure focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced to each other, and for the sake of brevity, they will not be described one by one.

[0040] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0041] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0042] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0043] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0044] In addition, in order to avoid obscuring the present disclosure due to unnecessary details, only the processing steps and / or device structures closely related to at least the scheme according to the present disclosure are shown in the drawings, and other details that are not closely related to the present disclosure are omitted. It should also be noted that similar reference numerals and letters in the drawings indicate similar items, and therefore once an item is defined in one drawing, it does not need to be discussed again for subsequent drawings.

[0045] Figure 1 Schematic diagram of a shelf and a robot according to some embodiments of the present disclosure. Figure 1 As shown, a plurality of storage locations 11 are provided on the shelf 10, and each storage location 11 is composed of an inclined support plate, and goods can be placed in the storage location 11. A robot 20 is provided in the lane between two shelves 10. The robot 20 runs along the walking mechanism 12 provided on the shelf 10 so as to pick and / or count the goods in each storage location 11. Among them, the inventory is a video inventory of the goods in the storage location, and there is no need to pick the goods in the storage location. As needed, the robot 20 may have the function of picking goods and the function of counting goods at the same time or not at the same time. Among them, the robot 20 with the function of picking goods is also called a picking robot.

[0046] Figure 2 and Figure 3 The three-dimensional schematic diagrams of the front view and the rear view of the picking robot in some embodiments of the present disclosure are respectively shown. Figure 2 and Figure 3As shown, the picking robot has a picking mechanism 21 and a temporary storage device 22. The temporary storage device 22 is also figuratively called a temporary storage backpack. After the picking mechanism 21 picks up each item, it can move to dock with a temporary storage device 22 and send the item to the temporary storage device 22 for temporary storage. Each temporary storage device 22 corresponds to a picking task, and each picking task can include one or more items, and multiple items can come from the same or different storage locations. When the picking tasks of all temporary storage devices 22 are completed, the picking robot can run to the dumping point to unload the goods in the temporary storage device 22. If the picking task is a customer order task, the unloaded goods will continue to complete the packaging and other tasks and be shipped out. If the picking task is a non-customer order task, such as internal warehouse allocation or return tasks to suppliers, the unloaded goods can be transferred to other warehouses or shelves or designated return locations.

[0047] Initialize warehouse map data based on the actual deployment of racks and their storage locations, dumping points and other facilities in the warehouse. Figure 4 The schematic diagram of the warehouse map data shown takes the lower left corner of the aisle as the origin (0, 0), the direction along the aisle extension as the x-axis, and the direction perpendicular to the aisle extension as the y-axis. According to the physical distance, the xy coordinates of each storage location (represented by a circle) are set, and the xy coordinates of the dumping point (represented by a box) of the aisle are set.

[0048] The priority of each task is determined according to at least one of the wave mode, task type, order type, and confluence time corresponding to the task. Thus, the priority information of the task is determined comprehensively from multiple dimensions. For example, the priority score of each task is determined according to at least one of the wave mode, task type, order type, and confluence time corresponding to the task; the priority scores of each task are grouped and sorted according to the size of the priority scores of the tasks to determine the priority level of each task.

[0049] The wave mode indicates the level of the time interval between the end time of the task wave and the current time. The shorter the time interval, the higher the level of the time interval, and the greater the priority score of the wave mode. Multiple task waves may belong to the same wave mode. For example, the wave mode includes an approaching wave mode, a normal wave mode, and a cross-day wave mode. If the end time of the task wave is less than 2 hours from the current time, it belongs to the approaching wave mode. If the end time of the task wave is greater than or equal to 2 hours and less than 24 hours from the current time, it belongs to the normal wave mode. If the end time of the task wave is greater than 24 hours from the current time, it belongs to the cross-day wave mode, but is not limited to the examples given.

[0050] Task types include, for example, customer order tasks, non-customer order tasks, and inventory tasks. Customer order tasks are tasks for customer orders, usually involving picking and outbound tasks. Non-customer order tasks, such as internal warehouse allocation or returns to suppliers, usually involve picking tasks. Inventory tasks are video inventory of goods in storage locations, without picking the goods in the storage locations. Therefore, compared to inventory tasks, customer order tasks and non-customer order tasks both involve picking tasks. Set priority scores for various task types according to business needs. For example, set the priority scores from large to small, in the order of customer order tasks, non-customer order tasks, and inventory tasks.

[0051] Order types include, for example, orders involving a single piece of goods, orders involving multiple pieces of goods, and orders for precise delivery. According to business needs, set priority scores for various order types. For example, set the priority scores from large to small, in the order of precise delivery orders, orders for a single piece of goods, and orders involving multiple pieces of goods.

[0052] The merging time means that for a merging order, if one aisle task of the merging order has been assigned to a robot, the priority score of another aisle task of the merging order is increased to the highest value.

[0053] If the priority of each task is determined based on multiple factors including the corresponding wave mode, task type, order type, and confluence time, the weight of each item can be set. The weighted sum operation is performed based on the weight of each item and the priority score of each item to obtain the priority score of each task. For example, y = θ 1 α+θ 2 β+θ 3 γ+θ 4 δ, where y represents a task and its priority score, αβγδ represent the priority scores of wave mode, task type, order type, and confluence time, respectively, and θ 1 θ 2 θ 3 θ 4 Respectively represent the weights of wave mode, task type, order type, and confluence time. According to the priority scores of the tasks, the priority scores of each task are grouped and sorted to determine the priority level of each task. For example, tasks with priority scores in the first range have the first priority level, T 1 ={y 1 y 2 y 3 ....}, the tasks with priority scores in the second range have the second priority level, T 2 ={y 4 y 5 y 6....}, tasks with priority scores in the third range have the third priority level, T 3 ={y 7 ....}. A collection of tasks at the same priority level, each task can be sorted from high to low according to the priority score.

[0054] According to the warehouse map data and the priority of each task, combined with the working status of the robot, according to the route planning method, the tasks and routes are planned for each robot. Figure 5 In the route planning method shown, the working states of the robot include, for example, idle, on-task, and locked; a robot in an idle state can undertake all types of business, and tasks and routes can be planned for the robot in an idle state based on all types of task pools; a robot in a task can undertake tasks of the same type as the current task, and tasks and routes can be planned for robots in tasks with idle temporary storage devices based on the same type of task pool as the current task; for locked robots and robots without idle temporary storage devices, there is no need to plan tasks and routes. The planned tasks and routes can be sent to the robot for execution. The route planning method is described in detail below.

[0055] Figure 6 A schematic diagram of a route planning method according to some embodiments of the present disclosure is shown. The route planning method according to this embodiment can be used, for example, to plan a route for an idle robot. The route planning method according to this embodiment can be executed, for example, by a route planning device.

[0056] like Figure 6 As shown, the working status of the robot in each lane is queried. If there is an idle robot, a route can be planned for the robot according to the following method.

[0057] In step 610, the seed task that the robot must perform is determined based on the priority of the task and the distance between the robot and the storage location corresponding to the task, thereby ensuring that the seed task with a higher priority and a shorter distance is performed first.

[0058] From the storage locations corresponding to a group of tasks with the highest priority, select the storage location closest to the robot as the seed storage location, and the seed storage location as the must-pass point; determine the task corresponding to the seed storage location as the seed task that the robot must perform.

[0059] Based on the task priority T determined above 1 T 2 T 3 For example, the highest priority group of tasks is T 1 ={y 1 y 2 y 3 ....}, the corresponding storage set is P 1 ={p1 p 2 p 3 p 4 ....}, the storage location closest to the robot in the storage location set is assumed to be p 1 , then the seed storage position is p 1 , the task y corresponding to the seed storage 1 For the seed task.

[0060] At step 620 , a first task set is determined based on the seed task.

[0061] Add the seed task to the first task set; and select tasks from non-seed tasks of the same task type as the seed task and add them to the first task set, thereby finding other tasks of the same type as the seed task.

[0062] Furthermore, if the number of non-seed tasks of the same task type as the seed task is relatively large, exceeding the expected limit on the number of tasks in the first task set, tasks can be selected and added to the first task set based on their priorities, with tasks of higher priority and the same task type being given priority.

[0063] For example, find the task y with the seed 1 Other tasks of the same type 5 y 7 , then the first task set is T 1 ={y 1 y 5 y 7 ....}, the corresponding storage set is P 1 ={p 1 p 5 p 7 ....}.

[0064] In step 630, a first objective function for achieving the shortest route is constructed based on whether each road section between each task and each storage location corresponding to the first task set is selected and the distance between each road section.

[0065] Define the decision variables:

[0066]

[0067] definition The distance cost of line segment ij.

[0068] Define the first objective function:

[0069]

[0070] Among them, min means taking the minimum value.

[0071] At step 640 , a first constraint of the first objective function is determined.

[0072] The first constraint condition includes: (1) All storage locations of seed tasks must be selected, thereby ensuring that seed tasks with high priority and close to the robot are executed first.

[0073] Among them, the first constraint condition also includes one or more of the following: (2) All storage locations of a task are selected or not selected at the same time, so that when a task involves multiple storage locations, the task is either completed or not executed, avoiding partial execution and improving task execution efficiency; (3) The starting point is the current position of the robot and has only outgoing edges; (4) A storage location is selected at most once, so that all tasks involved in a storage location are executed at the same time, avoiding the situation where the storage location is picked multiple times by multiple tasks, improving task execution efficiency; (5) When a storage location is selected, it has outgoing edges and incoming edges. By setting the outgoing edges and incoming edges, a directional section is obtained. Therefore, according to the decision variable x i,j Select the storage location based on the value of , and select the picking order of the storage location route based on the direction.

[0074] Among them, when the seed task involves a picking task, the first constraint condition also includes one or more of the following: (6) The destination point is a dumping point and has only one incoming edge; (7) At most n tasks are selected, where n is the number of idle temporary storage devices of the robot, and each temporary storage device is used to place the goods corresponding to a task. As mentioned above, customer order tasks and non-customer order tasks involve picking tasks, and picking tasks require temporary storage devices and dumping points, while inventory tasks do not require temporary storage devices and dumping points, so these constraints can be omitted.

[0075] Therefore, the first constraints (1)-(5) are not only applicable to tasks involving picking up goods, such as customer order tasks, non-customer order tasks, etc., but also to inventory tasks, and the first constraints (6)-(7) are applicable to tasks involving picking up goods.

[0076] In step 650, the second task set and execution route to be performed by the robot are determined based on the result of selecting each task and each road section that makes the route of the first objective function shortest while satisfying the first constraint condition. The second task set is a subset of the first task set, and can be specifically determined based on the first objective function and its first constraint condition.

[0077] Assume that the first task set is T 1 ={y 1 y 5 y 7 ....}, the corresponding storage set is P 1 ={p 1 p5 p 7 ....}, p 1 is the seed storage position, y 1 For seed tasks, such as Figure 7 As shown, assuming that the second task set is also T 2 ={y 1 y 5 y 7 ....}, the corresponding storage set is P 4 ={p 1 p 5 p 7 ....}, the shortest route is: robot current point → p 1 →p 5 →p 7 →Dumping point.

[0078] According to the priority of the task and the distance between the robot and the storage location corresponding to the task, the seed task that the robot must perform is determined. Based on the seed task, the set of tasks to be planned is determined. According to the result of selecting each task and each section that makes the route of the objective function the shortest while satisfying the constraints, the set of tasks and the execution route that the robot needs to perform are determined. Thus, while ensuring the priority of the task, the overall route is made shortest and the overall efficiency is maximized.

[0079] Figure 8 A schematic diagram of a route planning method according to some embodiments of the present disclosure is shown. The route planning method according to this embodiment can be used, for example, to plan a route for a robot in a task. The route planning method according to this embodiment can be executed, for example, by a route planning device.

[0080] like Figure 8 As shown, the robot in the task can add tasks and re-plan the route according to the following route planning method.

[0081] At step 810 , remaining unexecuted tasks in the second task set are determined.

[0082] Assume that the remaining unexecuted tasks in the second task set are The corresponding storage location set is

[0083] In step 820 , the remaining tasks and other tasks of the same task type as the remaining tasks are added to a third task set.

[0084] Assume that the third task set is T 3 ={y 7 y 8}, the corresponding storage set is P 3 ={p 7 p 8....}, where the remaining tasks y 7 and additional task y 8 The tasks are of the same type.

[0085] In step 830, a second objective function for achieving the shortest route is constructed based on whether each road section between each task corresponding to the third task set and each storage location is selected and the distance between each road section.

[0086] Define the decision variables:

[0087]

[0088] definition The distance cost of line segment ij.

[0089] Define the second objective function:

[0090]

[0091] Among them, min means taking the minimum value.

[0092] At step 840, a second constraint of the second objective function is determined.

[0093] The second constraint condition includes: (1) all storage spaces corresponding to the remaining tasks, such as must be selected. Thus, ensuring that the remaining tasks are executed.

[0094] Among them, the second constraint condition also includes one or more of the following: (2) All storage locations of a task are selected or not selected at the same time, so that when a task involves multiple storage locations, the task is either completed or not executed, avoiding partial execution and improving task execution efficiency; (3) The starting point is the current position of the robot and has only outgoing edges; (4) A storage location is selected at most once, so that all tasks involved in a storage location are executed at the same time, avoiding the situation where the storage location is picked multiple times by multiple tasks, improving task execution efficiency; (5) When a storage location is selected, it has outgoing edges and incoming edges. By setting the outgoing edges and incoming edges, a directional section is obtained. Therefore, according to the decision variable x i,j Select the storage location based on the value of , and select the picking order of the storage location route based on the direction.

[0095] In the case where the seed task involves a pickup task, the second constraint condition also includes one or more of the following: (6) The destination point is a dumping point and has only one incoming edge; (7) A maximum of m tasks are added, where m is the number of remaining temporary storage devices of the robot, and each temporary storage device is used to place the goods corresponding to a task. The remaining temporary storage devices are temporary storage devices that have not been assigned tasks. As mentioned above, customer order tasks and non-customer order tasks involve pickup tasks. Pickup tasks require temporary storage devices and dumping points, while inventory tasks do not require temporary storage devices and dumping points. In this case, these constraints do not need to be set.

[0096] Therefore, the second constraints (1)-(5) are not only applicable to tasks involving picking up goods, such as customer order tasks, non-customer order tasks, etc., but also to inventory tasks, and the second constraints (6)-(7) are applicable to tasks involving picking up goods.

[0097] In step 850, according to the result of selecting each task and each road section that makes the route of the second objective function shortest while satisfying the second constraint condition, a fourth task set and an execution route to be performed by the robot are determined. The fourth task set is a subset of the third task set, and can be specifically determined according to the second objective function and its second constraint condition.

[0098] If all tasks in the second task set have not been executed, the tasks in the second task set and the additional tasks are re-determined according to the method of this embodiment to be executed and their execution routes. If some tasks in the second task set have been executed, the unexecuted tasks in the second task set and the additional tasks are re-determined according to the method of this embodiment to be executed and their execution routes.

[0099] For example, suppose the third task set is T 3 ={y 7 y 8}, the corresponding storage set is P 3 ={p 7 p 8 ....},like Fig. 9 As shown, assuming that the fourth task set is also T 4 ={y 7 y 8}, the corresponding storage set is P 4 ={p 7 p 8 ....}, the shortest route corresponding to the fourth task set is: robot current point → p 8 →p 7 →Dumping point.

[0100] According to the priority of the task and the distance between the robot and the storage location corresponding to the task, the seed task that the robot must perform is determined. Based on the seed task, the set of tasks to be planned is determined. According to the result of selecting each task and each section that makes the route of the objective function the shortest while satisfying the constraints, the set of tasks and the execution route that the robot needs to perform are determined. Thus, while ensuring the priority of the task, the overall route is made shortest and the overall efficiency is maximized.

[0101] According to the remaining unexecuted tasks in the second task set and other tasks of the same task type as the remaining tasks, the task set to be planned is determined, and according to the result of selecting each task and each road section that makes the route of the objective function the shortest under the condition of satisfying the constraint conditions, the task set and execution route that the robot needs to execute are determined. Thus, not only can new tasks of the same type be dynamically added, but the route can also be guaranteed to be the shortest.

[0102] Fig.10 A schematic diagram showing the structure of a route planning device according to some embodiments of the present disclosure is shown. Fig.10 As shown, the route planning device 1000 of this embodiment includes: a memory 1010 and a processor 1020 coupled to the memory 1010 , and the processor 1020 is configured to execute the route planning method in any of the aforementioned embodiments based on instructions stored in the memory 1010 .

[0103] The route planning device 1000 may further include an input / output interface 1030 , a network interface 1040 , a storage interface 1050 , etc. These interfaces 1030 , 1040 , 1050 , the memory 1010 , and the processor 1020 may be connected via a bus 1060 , for example.

[0104] The memory 1010 may include, for example, a system memory, a fixed non-volatile storage medium, etc. The system memory may store, for example, an operating system, an application program, a boot loader, and other programs.

[0105] Among them, the processor 1020 can be implemented by discrete hardware components such as a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistors.

[0106] Among them, the input and output interface 1030 provides a connection interface for input and output devices such as a display, a mouse, a keyboard, and a touch screen. The network interface 1040 provides a connection interface for various networked devices. The storage interface 1050 provides a connection interface for external storage devices such as SD cards and USB flash drives. The bus 1060 can use any bus structure among a variety of bus structures. For example, the bus structure includes but is not limited to the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MCA) bus, and the Peripheral Component Interconnect (PCI) bus.

[0107] Fig.11 A schematic diagram showing the structure of a route planning device according to some embodiments of the present disclosure is shown. Fig.11 As shown, the route planning device 1100 of this embodiment includes: a module for executing a route planning method.

[0108] The initial planning module 1110 is configured to determine the seed task that the robot must perform based on the priority of the task and the distance between the robot and the storage location corresponding to the task; determine the first task set based on the seed task; construct a first objective function for achieving the shortest route based on whether each road section between each task and each storage location corresponding to the first task set is selected and the distance of each road section; determine the first constraint condition of the first objective function; and determine the second task set and execution route that the robot needs to perform based on the result that each task and each road section that makes the route of the first objective function the shortest while satisfying the first constraint condition are selected.

[0109] From the storage locations corresponding to a group of tasks with the highest priority, select the storage location closest to the robot as the seed storage location; and determine the task corresponding to the seed storage location as the seed task that the robot must perform.

[0110] Adding a seed task to a first task set; and selecting a task from non-seed tasks of the same task type as the seed task to add to the first task set.

[0111] The additional planning module 1120 is configured to determine the remaining unexecuted tasks in the second task set; add the remaining tasks and other additional tasks of the same task type as the remaining tasks to the third task set; construct a second objective function to achieve the shortest route based on whether the various sections between the various tasks and storage locations corresponding to the third task set are selected and the distances of the various sections; determine the second constraint condition of the second objective function; and determine the fourth task set and execution route that the robot needs to execute based on the result of selecting the various tasks and various sections that make the route of the second objective function the shortest while satisfying the second constraint condition.

[0112] The priority determination module 1130 is configured to determine the priority of the task according to at least one of the wave mode, task type, order type, and confluence time corresponding to the task.

[0113] Fig.12 A schematic diagram of a route planning system according to some embodiments of the present disclosure is shown. Fig.12 As shown, the route planning system 1200 of this embodiment includes: a route planning device 1210 and a robot 1220. The route planning device 1210 is, for example, the route planning device 1000 or 1100. The route planning device 1210 can provide route planning services for multiple robots 1220.

[0114] It should be understood by those skilled in the art that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more (non-transient) computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, cloud storage, etc.) containing computer program code. A computer program product should be understood as a software product that implements its solution mainly through a computer program.

[0115] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0116] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0118] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A route planning method, comprising: Determine the seed task that the robot must perform according to the priority of the task and the distance between the robot and the storage location corresponding to the task; Based on the seed task, determining a first task set; Constructing a first objective function for achieving the shortest route according to whether each road section between each task and each storage location corresponding to the first task set is selected and the distance between each road section; Determining a first constraint condition of a first objective function; According to the result of selecting each task and each road section that makes the route of the first objective function shortest while satisfying the first constraint condition, a second task set and an execution route that the robot needs to perform are determined.

2. The method according to claim 1, wherein: Determine the seed tasks that the robot must perform including: From the storage locations corresponding to the highest priority group of tasks, select the storage location closest to the robot as the seed storage location; The tasks corresponding to the seed storage locations are determined as the seed tasks that the robot must perform.

3. The method according to claim 1, wherein: Determining the first task set includes: Adding the seed task to the first task set; Selecting tasks from non-seed tasks of the same task type as the seed task and adding them to the first task set.

4. The method according to claim 1, wherein: The first constraint includes: all storage locations of the seed task must be selected.

5. The method according to claim 4, wherein: The first constraint also includes one or more of the following: All storage slots of a task are selected or not selected at the same time; The starting point is the robot's current position, and there are only outgoing edges; A storage slot is selected at most once; A storage location, when selected, has outgoing edges and incoming edges.

6. The method according to claim 5, wherein: When the seed task involves a pickup task, the first constraint condition also includes one or more of the following: The destination point is a dumping point and has only incoming edges; A maximum of n tasks are selected, where n is the number of idle temporary storage devices of the robot, and each temporary storage device is used to place the goods corresponding to a task.

7. The method according to any one of claims 1 to 6, further comprising: Determining remaining unexecuted tasks in the second task set; Add the remaining tasks and other tasks of the same task type as the remaining tasks to the third task set; According to whether each road section between each task and each storage location corresponding to the third task set is selected and the distance between each road section, a second objective function for achieving the shortest route is constructed; determining a second constraint condition of the second objective function; According to the result of selecting each task and each road section that makes the route of the second objective function the shortest while satisfying the second constraint condition, a fourth task set and an execution route that the robot needs to perform are determined.

8. The method according to claim 7, wherein: The second constraint condition includes: all storage locations corresponding to the remaining tasks must be selected.

9. The method according to claim 8, wherein: The second constraint may also include one or more of the following: All storage slots of a task are selected or not selected at the same time; The starting point is the robot's current position, and there are only outgoing edges; A storage slot is selected at most once; A storage location, when selected, has outgoing edges and incoming edges.

10. The method according to claim 9, wherein: When the seed task involves a pickup task, the second constraint condition also includes one or more of the following: The destination point is a dumping point and has only incoming edges; A maximum of m tasks can be added, where m is the number of remaining temporary storage devices of the robot, and each temporary storage device is used to place the goods corresponding to a task.

11. The method according to any one of claims 1 to 10, further comprising: The priority of the task is determined according to at least one of the wave mode, task type, order type, and confluence time corresponding to the task.

12. A route planning device, comprising: Memory; And a processor coupled to the memory, wherein the processor is configured to execute the route planning method according to any one of claims 1 to 11 based on instructions stored in the memory.

13. A route planning device, comprising: A module for executing the route planning method according to any one of claims 1 to 11.

14. A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the route planning method according to any one of claims 1 to 11 are implemented.

15. A computer program product, comprising a computer program, which implements the steps of the route planning method according to any one of claims 1 to 11 when executed by a processor.

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