An AGV path planning method, device and medium based on cold and heat degrees

Abstract

The present application discloses an AGV path planning method, device and medium based on cold and hot degrees, which relates to the technical field of logistics management and is used for planning the AGV path. Aiming at the problem of traffic jams that are prone to occur currently, an AGV path planning method based on cold and hot degrees is provided. The passing cold and hot degrees of each grid are calculated through historical passing data to represent the passing frequency of the AGV passing through the grid, and then the global grid map is divided into multiple regions with different levels in the form of passing cold and hot degrees. Therefore, when performing path planning for logistics tasks, path planning can be carried out according to the preset task priorities. The more important the task is, the shortest path planning can be carried out in the regions with more passing cold and hot degree levels to obtain the optimal path. The expected traffic conditions are taken into consideration to more reasonably plan the AGV path, effectively reducing the occurrence probability of traffic jam problems, and thereby improving the operation efficiency of the AGV system.

Description

Technical Field

[0001] The present application relates to the technical field of logistics management, and particularly to an AGV path planning method, device and medium based on cold and heat degrees. Background Art

[0002] In recent years, under the guidance of trends such as industrial Internet and intelligent manufacturing, in order to improve the operation efficiency and automation level of warehousing logistics, a transport vehicle (Automated Guided Vehicle, AGV) system has been widely used in the logistics warehouses of manufacturing enterprises and large e-commerce companies to perform material handling work. In order to ensure the efficient operation of the AGV system in various warehousing logistics scenarios, it is necessary to apply reasonable and effective path planning methods to plan reasonable driving paths for different AGVs, so as to achieve goals such as shortening the driving distance, reducing the operation cost, and reducing traffic conflicts.

[0003] Currently, when performing path planning for AGVs, the shortest distance path from the starting point to the target point is mainly used as the optimization goal, and it is achieved through methods such as the Dijkstra algorithm. However, such path planning algorithms often do not consider the traffic conditions in the driving area during the planning process. Therefore, situations such as multiple planned AGV paths overlapping are likely to occur, which in turn leads to problems such as traffic jams during the driving of AGVs and affects the logistics efficiency.

[0004] Therefore, those skilled in the art now urgently need an AGV path planning method based on cold and heat degrees to solve the problem that the current AGV path planning method is prone to overlapping planned paths and thus traffic jams occur during the actual driving of AGVs. Summary of the Invention

[0005] The purpose of the present application is to provide an AGV path planning method, device and medium based on cold and heat degrees to solve the problem that the current AGV path planning method is prone to overlapping planned paths and thus traffic jams occur during the actual driving of AGVs.

[0006] To solve the above technical problems, the present application provides an AGV path planning method based on cold and heat degrees, including:

[0007] Obtain a global grid map and task information corresponding to the AGV; wherein, the global grid map includes a plurality of interconnected grids, and each grid corresponds to a passing cold and heat degree determined according to the historical passing data of the AGV; the passing cold and heat degree represents the passing frequency of the AGV passing through this grid; the task information includes a task priority, and there is a preset corresponding relationship between the task priority and the passing cold and heat degree;

[0008] Determine the passable grids of each AGV according to the task priority;

[0009] Plan the shortest driving path for each AGV according to the passable grid.

[0010] Preferably, it further includes:

[0011] When the grid is planned as the shortest driving path, mark the grid as occupied;

[0012] Correspondingly, when all AGVs corresponding to the grid pass through the grid according to the shortest driving path, mark the grid as unoccupied.

[0013] Preferably, the corresponding relationship between the task priority and the traffic cold and heat degree is a one-to-one correspondence. The passable grid is: in the global grid map, the grid with the traffic cold and heat degree less than or equal to the task priority, and the grid with the traffic cold and heat degree greater than the task priority but marked as unoccupied.

[0014] Preferably, the corresponding relationship between the task priority and the traffic cold and heat degree is a one-to-one correspondence. The passable grid is: in the global grid map, the grid with the traffic cold and heat degree less than or equal to the task priority.

[0015] Preferably, when multiple AGVs pass through the same grid, it further includes:

[0016] Each AGV arranges the passing order according to the strategy of first come, first go.

[0017] Preferably, determining the traffic cold and heat degree of each grid according to the historical passing data includes:

[0018] According to the historical passing data, count the passing times of each grid;

[0019] According to the passing times of each grid, determine the traffic cold and heat degree of each grid by the first formula;

[0020] Among them, the first formula is:

[0021]

[0022] H i is the traffic cold and heat degree of grid i, S is the total number of grids, N i is the passing times of grid i, N a is the average passing times of each grid, N m is the maximum passing times in each grid, k is the traffic cold and heat degree level, and n is the number of levels for dividing the traffic cold and heat degree.

[0023] Preferably, the global grid map is updated periodically, and each time it is updated, the actual passing data of the previous period is used as the historical passing data to determine the traffic cold and heat degree of each grid.

[0024] To solve the above technical problems, the present application also provides an AGV path planning device based on cold and heat degrees, including:

[0025] An information acquisition module, configured to acquire a global grid map and task information corresponding to the AGV; wherein, the global grid map includes a plurality of interconnected grids, and each grid corresponds to a passage cold and heat degree determined according to the historical passage data of the AGV; the passage cold and heat degree represents the passage frequency of the AGV passing through this grid; the task information includes a task priority, and there is a preset corresponding relationship between the task priority and the passage cold and heat degree;

[0026] A grid determination module, configured to determine the passable grids of each AGV according to the task priority;

[0027] A path planning module, configured to plan the shortest driving path for each AGV according to the passable grids.

[0028] Preferably, it further includes:

[0029] A grid marking module, configured to mark the grid as an occupied state when the grid is planned as the shortest driving path; correspondingly, when all AGVs corresponding to this grid pass through the grid according to the shortest driving path, mark the grid as an unoccupied state.

[0030] A passage strategy module, configured to when multiple AGVs pass through the same grid, each AGV arranges the passage order according to the strategy of first come, first go.

[0031] To solve the above technical problems, the present application also provides an AGV path planning device based on cold and heat degrees, including:

[0032] A memory, configured to store a computer program;

[0033] A processor, configured to implement the steps of the above-mentioned AGV path planning method based on cold and heat degrees when executing the computer program.

[0034] To solve the above technical problems, the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned AGV path planning method based on cold and heat degrees are implemented.

[0035] A method for AGV path planning based on cold and heat degrees provided by this application calculates the cold and heat degrees of passing for each grid that an AGV can pass through through historical passing data, which is used to characterize the passing frequency of the AGV passing through this grid. Furthermore, the global grid map is divided into multiple regions with different levels in the form of cold and heat degrees of passing, and the average AGV flow represented by each region is different. Therefore, when performing path planning for a logistics task, path planning can be carried out according to a preset task priority. The more important the task is, the shortest path planning can be carried out in regions with more cold and heat degrees of passing levels to obtain the optimal path. On the contrary, relatively unimportant tasks avoid regions with high cold and heat degrees of passing for the shortest path planning. Thus, it is realized to take the expected traffic situation into consideration to more reasonably plan the AGV path, effectively reducing the occurrence probability of traffic jams, and further improving the operation efficiency of the AGV system.

[0036] The AGV path planning device based on cold and heat degrees and the computer-readable storage medium provided by this application correspond to the above method and have the same effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] To more clearly illustrate the embodiments of this application, the drawings required to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0038] Figure 1 It is a flowchart of a method for AGV path planning based on cold and heat degrees provided by the present invention;

[0039] Figure 2 It is a schematic diagram of a global grid map provided by the present invention;

[0040] Figure 3 It is a path planning diagram of an existing AGV path planning method;

[0041] Figure 4 It is a path planning diagram of a method for AGV path planning based on cold and heat degrees provided by the present invention;

[0042] Figure 5 It is a path planning diagram of another method for AGV path planning based on cold and heat degrees provided by the present invention;

[0043] Figure 6 It is a structural diagram of an AGV path planning device based on cold and heat degrees provided by the present invention;

[0044] Figure 7 It is a structural diagram of another AGV path planning device based on cold and heat degrees provided by the present invention. Detailed implementation manners

[0045] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present application.

[0046] The core of the present application is to provide an AGV path planning method, device and medium based on cold and heat degrees.

[0047] In order to enable those skilled in the art to better understand the solution of the present application, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0048] In today's warehousing and logistics field, AGVs are widely used in the logistics warehouses of manufacturing industries and large e-commerce due to their outstanding feature of liberating human labor. When an AGV completes the logistics transportation work, it is necessary to standardize the driving path of the AGV to complete the transportation of materials. Currently, for the path planning of AGVs, the main goal is to find the shortest path from the starting point to the target point, and the shortest path is determined through algorithms such as the Dijkstra algorithm, and then the AGV path planning is completed.

[0049] However, the above AGV path planning method will face a problem that only considering the shortest target path may lead to the problem of overlapping paths of multiple AGVs, which may further cause traffic jams during the driving process of the AGVs and affect the logistics efficiency.

[0050] To solve the above problem, the present application provides an AGV path planning method based on cold and heat degrees, as Figure 1 shown, including:

[0051] S11: Obtain the global grid map and the task information corresponding to the AGV.

[0052] Among them, the global grid map includes a plurality of interconnected grids, and each grid corresponds to a passing cold and heat degree determined according to the historical passing data of the AGV; the passing cold and heat degree represents the passing frequency of the AGV passing through this grid; the task information is also the task information of the logistics task to be executed by the AGV, including the task priority, etc., and there is a preset corresponding relationship between the task priority and the passing cold and heat degree.

[0053] The passing cold and heat degree of each grid is determined by the frequency of the passing AGVs. Specifically, a preferred implementation includes:

[0054] S111: According to the historical passing data, count the passing times of each grid.

[0055] S112: Determine the traffic cold / hot degrees of each grid according to the traffic times of each grid using the first formula.

[0056] Wherein, the first formula is:

[0057]

[0058] H i is the traffic cold / hot degree of grid i, S is the total number of grids, N i is the traffic times of grid i, N a is the average traffic times of each grid, N m is the maximum traffic times in each grid, k is the level of traffic cold / hot degree, and n is the number of levels for dividing the traffic cold / hot degree.

[0059] Exemplarily, assuming that the traffic cold / hot degree is divided into 4 levels from 1 to 4, a 10*10 global grid map is obtained as Figure 2 shown. The numbers in the grids represent the levels of traffic cold / hot degree. The higher the level, the higher the frequency of AGVs passing through the grid per unit time. In addition, since the area where AGVs can travel is not constant, to ensure the rationality of AGV path planning, this embodiment further provides a preferred implementation:

[0060] The above-mentioned global grid map is updated periodically. Each time it is updated, the actual traffic data of the previous cycle is used as historical traffic data to determine the traffic cold / hot degrees of each grid.

[0061] It is easy to understand that the task priority and the traffic cold / hot degree can adopt the principle of corresponding at the same level. That is, in the above example, the traffic cold / hot degree includes 4 levels from 1 to 4, and the corresponding traffic cold / hot degree is also 4 levels from 1 to 4, with the same levels corresponding to each other. Other corresponding principles can also be adopted. For example, if the traffic cold / hot degree has 4 levels, the task priority can have 8 levels, and every two levels correspond to one level of traffic cold / hot degree. The task priority can also be used to indicate the priority of AGV path planning. The AGV path for the material transportation task with a higher task level is preferentially planned, etc. This application does not limit the corresponding relationship between the task priority and the traffic cold / hot degree too much. However, for the convenience of description, the principle of corresponding at the same level is used for expansion in the subsequent examples.

[0062] S12: Determine the passable grids of each AGV according to the task priority.

[0063] Still taking the principle of corresponding at the same level between the task priority and the traffic cold / hot degree as an example, as Figure 2There are 4 levels in total. If there is a logistics task with a task priority of level 3, then in a possible implementation, the passable grid corresponding to the task is a grid with a passable coldness and heatness less than or equal to level 3. Similarly, if there is a logistics task with a task priority of level 2, the corresponding passable grid is a grid with a passable coldness and heatness of levels 1 and 2.

[0064] In the above preferred embodiment, the AGV corresponding to a logistics task is not allowed to pass through the grid whose traffic temperature is higher than the task priority, thereby alleviating the traffic pressure of the grid with high traffic temperature and reducing the occurrence of traffic jams.

[0065] S13: Plan the shortest driving path for each AGV based on the traversable grid.

[0066] When the traversable grid for the logistics task is determined, the shortest driving route can be planned based on the currently common shortest path planning algorithm.

[0067] To further illustrate the advantages of the AGV path planning method based on cold and hot degrees provided by the present application over the existing AGV path planning method, for example, in a Figure 3 In the application scenario shown, there are logistics tasks A and B, which move from the starting point (car A and car B) to the target point (point A and point B) respectively. For logistics task A, the shortest path is determined, such as Figure 3 As shown, for logistics task B, there are multiple shortest paths (in addition to the shortest path as the first goal, the second goal can also be the minimum number of path bends), which are represented by directed solid line segments and dotted line segments. Figure 3 It can be seen that when the AGV path of logistics task B is the path shown by the dotted line segment, there are a large number of overlapping grids in the AGV paths of logistics tasks A and logistics tasks B, which is prone to traffic jams.

[0068] As for the AGV path planning method based on cold and hot degrees in this application, Figure 4 As shown in the figure, the principle of equal correspondence between traffic temperature and task priority is adopted, and the AGV corresponding to the logistics task can only pass through the grid whose traffic temperature does not exceed its task priority. Assuming that the task priority of logistics task A is level 4 and the task priority of logistics task B is level 3, the AGV paths of logistics task A and logistics task B are as follows: Figure 4 As shown by the solid line segment. Figure 4 It is easy to see that the overlapping parts of the AGV paths of logistics task A and logistics task B are greatly reduced, thereby reducing the possibility of traffic jams.

[0069] It is also necessary to point out that Figure 3Shown in [reference] is an existing AGV path planning method, and there should be no grid with a traffic cold / hot level. Figure 3 Each grid in [reference] retains the traffic cold / hot level to indicate that its map situation is the same as that in Figure 2 and Figure 4 shown in [reference], which is convenient for comparison with a method for AGV path planning based on cold / hot level provided in this application.

[0070] A method for AGV path planning based on cold / hot level provided in this application models the drivable area of the AGV in advance to obtain a global grid map, calculates the frequency of AGVs passing through each grid per unit time, and then quantifies it into the traffic cold / hot level. Further, when obtaining a logistics task, a corresponding task priority is set for each logistics task, and the passable grid area of the current logistics task is determined through the task priority, so as to determine the shortest path according to the shortest path algorithm. The above method ensures that the planned AGV path is as short as possible, enables logistics tasks to obtain different passing permissions according to their respective priorities, avoids logistics tasks with low task priorities occupying grids with frequent AGV passes, thereby alleviating traffic congestion, making the AGV path planning more intelligent, improving logistics efficiency, and better meeting the needs of actual logistics transportation.

[0071] It is easy to understand that in actual logistics transportation, the AGV paths to be planned are not unique, and usually, AGV path planning for multiple logistics tasks is required. At this time, this embodiment provides a preferred implementation, and the above method further includes:

[0072] S21: When a grid is planned as the shortest driving path, mark the grid as occupied.

[0073] That is, when any grid is covered by any AGV path, the grid is marked as occupied, and a grid can be covered by multiple AGV paths.

[0074] S22: When all AGVs corresponding to the grid pass through the grid according to the shortest driving path, mark the grid as unoccupied.

[0075] That is, after an AGV passes through the grid, the AGV path corresponding to the AGV is regarded as completed. When all AGV paths covering the grid are in the completed state, reset the grid to the unoccupied state.

[0076] The marking of whether a grid is occupied can provide guidance for subsequent AGV path planning and also provide data support for relevant personnel to master the logistics situation.

[0077] For example, in a possible AGV path planning method, when the number of times a certain grid is marked within a preset time exceeds a preset upper limit, its pass heat and coldness is increased. Similarly, when the number of times a certain grid is marked within a preset time is lower than a preset lower limit, its pass heat and coldness is decreased. Furthermore, grids with different pass heat and coldness have different corresponding preset upper and lower limits.

[0078] Alternatively, when the number of grids marked by different AGV paths at the same time exceeds the first preset threshold, its traffic hotness and coldness can be ignored, and the grid will not be used as a subsequent passable grid for AGV path planning until the number of AGV paths marking the grid is lower than the first preset threshold again.

[0079] In addition, it can be seen from the above embodiments that the present application sets the traffic hotness and task priority so that when performing AGV path planning, only the shortest path planning is allowed in the grid area that is passable by the current logistics task, so as to achieve the effect of alleviating traffic congestion.

[0080] The above embodiment provides a method for determining passable grids according to task priority and the traffic heat of each grid, and taking grids with traffic heat less than or equal to the task priority as passable grids to ensure the effect of alleviating traffic congestion.

[0081] However, there are some specific application scenarios where low task priorities need to bypass a large number of grids with high traffic hotness and coldness, but these grids are not occupied by other AGV paths, which will cause a certain degree of resource waste. Therefore, this embodiment, based on the above embodiment of marking grids occupied by AGV paths, also provides a preferred implementation scheme, in which the traffic hotness and coldness and task priorities are in a one-to-one correspondence (i.e., a same-level correspondence). At this time, the passable grids determined according to the task priority are specifically:

[0082] In the global grid map, each grid whose traffic heat is less than or equal to the task priority, and each grid whose traffic heat is greater than the task priority but marked as unoccupied.

[0083] Based on this embodiment, Figure 3 , Figure 4 The logistics tasks A and B in the example are re-planned for the AGV path, and the results are as follows Figure 5 The new AGV path shown in Figure 1 shows that Figure 4 The AGV planning path shown in the figure effectively shortens the path length of logistics task B. At the same time, since the grids occupied by logistics task B that are higher than its task priority are not occupied by other AGV paths, traffic jams will not occur, and the technical effect brought by this method can be guaranteed.

[0084] In addition, it is easy to understand that when there are too many AGV paths existing at the same time, the above embodiments can be further improved. For example, the judgment criterion for the grid with high traffic cold and heat that can be used is not whether it is occupied, but whether the number of AGV paths marked for this grid exceeds a second preset threshold. If it exceeds, it is unavailable; if it does not exceed, it is still regarded as a passable grid.

[0085] A preferred solution provided by this embodiment marks the grids occupied by the planned AGV paths to facilitate relevant personnel to master the actual logistics situation. At the same time, it also provides guidance for subsequent AGV path planning. On this basis, this embodiment also provides a preferred implementation scheme. When performing AGV path planning, grids with a traffic cold and heat level higher than the task priority and not occupied by other AGV paths can be used as passable grids for this logistics task, so as to shorten the AGV path length as much as possible on the premise of ensuring the reduction of traffic jams, and further improve the efficiency of AGV logistics transportation.

[0086] The AGV path planning method based on cold and heat provided by the above embodiments can effectively reduce the possibility of traffic jams when AGV actually conducts logistics transportation. However, in some extreme cases, there may still be a problem that two AGVs meet and then get blocked or the passing order needs to be judged.

[0087] For example, when performing AGV path planning for a logistics task with a task priority of level 3, a grid with an unoccupied traffic cold and heat level of 4 is used. And before this logistics task is completed, a new logistics task with a task priority of level 4 also conducts AGV path planning and uses the above-mentioned level 4 grid, and the two vehicles meet. At this time, how to solve the problem of the two vehicles meeting is another challenge affecting the logistics transportation efficiency.

[0088] Based on the above problems, this embodiment provides a preferred implementation scheme. When multiple AGVs pass through the same grid, this method further includes:

[0089] S31: Each AGV arranges the passing order according to the strategy of "first come, first go".

[0090] That is, when multiple AGVs drive into the same grid at the same time, according to the order of entry of each AGV into this grid, the AGV that enters this grid first exits first, and the later one enters and exits later, so as to allocate the passing order of multiple AGVs driving into the same grid.

[0091] Alternatively, the passing order of the AGVs can be determined by the task priority, that is, the AGV with a higher task priority passes through the grid first, and the AGV with a lower task priority passes through the grid later. This method takes into account the different importance of each task in the actual logistics and can solve the problem of two AGVs entering the same grid simultaneously.

[0092] In practical applications, the above two methods can also be combined. For example, first determine the passing order of the AGVs by task priority, and for those with the same task priority, determine the passing order according to the time of entering the grid; or first arrange the passing order according to the time of entering the grid, and when multiple AGVs enter the grid simultaneously, allocate the passing order according to the task priority. This embodiment is not limited to how to determine the passing order of the AGVs in the specific implementation, and can be any one or a combination of the above several passing strategies.

[0093] It should also be noted that there is no restriction on the order or logical relationship between steps S11, S12, S13 and steps S21, S22 of the above embodiment and step S31 of this embodiment. Therefore, different sequence numbers are used for distinction. It is easy to see that steps S11, S12, S13 are the methods for completing the AGV path planning for one logistics task; steps S21, S22 are the marking and restoration of the grid in real time according to the actual situation during the AGV path planning; and step S31 is the solution to the situation of multiple vehicles meeting when the AGV path planning is completed and the AGV starts the actual logistics task.

[0094] A preferred solution provided by this embodiment arranges the passing order among multiple AGVs meeting in the same grid through the strategy of first come, first go, avoiding the chaos of logistics, further reducing the risk of traffic jams, and improving the actual logistics transportation efficiency.

[0095] In the above embodiment, a method for AGV path planning based on cold and heat degrees is described in detail. The present application also provides an embodiment corresponding to an AGV path planning device based on cold and heat degrees. It should be noted that the present application describes the embodiments of the device part from two perspectives, one is from the perspective of functional modules, and the other is from the perspective of hardware.

[0096] From the perspective of functional modules, this embodiment provides an AGV path planning device based on cold and heat degrees, as Figure 6 shown, including:

[0097] An information acquisition module 41, configured to acquire a global grid map and task information corresponding to an AGV; wherein, the global grid map includes a plurality of interconnected grids, and each grid corresponds to a traffic cold and hot degree determined according to the historical traffic data of the AGV; the traffic cold and hot degree represents the traffic frequency of the AGV passing through the grid; the task information includes a task priority, and there is a preset corresponding relationship between the task priority and the traffic cold and hot degree;

[0098] A grid determination module 42, configured to determine the passable grids of each AGV according to the task priority;

[0099] A path planning module 43, configured to plan the shortest driving path for each AGV according to the passable grids.

[0100] Preferably, it further includes:

[0101] A grid marking module, configured to mark the grid as an occupied state when the grid is planned as the shortest driving path; correspondingly, when all AGVs corresponding to the grid pass through the grid according to the shortest driving path, mark the grid as an unoccupied state.

[0102] A traffic strategy module, configured to, when multiple AGVs pass through the same grid, arrange the passing order of each AGV according to the strategy of first come, first go.

[0103] Since the embodiments of the device part correspond to the embodiments of the method part, for the embodiments of the device part, please refer to the description of the embodiments of the method part, and will not be elaborated here.

[0104] The provided AGV path planning device based on cold and hot degree in this embodiment acquires a global grid map obtained by pre-modeling the drivable area of the AGV through the information acquisition module, and calculates the frequency of AGVs passing through each grid per unit time, and then quantifies it into a traffic cold and hot degree; further, when acquiring a logistics task, set a corresponding task priority for each logistics task, and determine the passable grid area of the current logistics task according to the task priority through the grid determination module, so that the path planning module can determine the shortest path according to the shortest path algorithm. On the premise of ensuring that the planned AGV path is as short as possible, the logistics tasks can obtain different passing authorities according to their respective priorities, avoiding the situation that logistics tasks with low task priorities occupy grids with frequent AGV traffic, thereby alleviating traffic congestion, making the AGV path planning more intelligent, improving logistics efficiency, and better meeting the needs of actual logistics transportation.

[0105] Figure 7 This is a structural diagram of an AGV path planning device based on cold and hot degree provided in another embodiment of the present application, as Figure 7As shown in the figure, an AGV path planning device based on cold and heat degrees includes: a memory 50 for storing computer programs;

[0106] a processor 51 for implementing the steps of an AGV path planning method based on cold and heat degrees as described in the above embodiment when executing the computer program.

[0107] An AGV path planning device based on cold and heat degrees provided in this embodiment may include, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, etc.

[0108] Among them, the processor 51 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 51 may be implemented in at least one hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 51 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the wake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 51 may be integrated with a graphics processing unit (GPU), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 51 may further include an artificial intelligence (AI) processor, and the AI processor is used to process computational operations related to machine learning.

[0109] The memory 50 may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory 50 may further include a high-speed random access memory and a non-volatile memory, such as one or more disk storage devices and flash storage devices. In this embodiment, the memory 50 is at least used to store the following computer program 501. After the computer program is loaded and executed by the processor 51, it can implement the relevant steps of an AGV path planning method based on cold and heat degrees disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 50 may further include an operating system 502 and data 503, etc., and the storage method may be temporary storage or permanent storage. Among them, the operating system 502 may include Windows, Unix, Linux, etc. The data 503 may include, but is not limited to, an AGV path planning method based on cold and heat degrees, etc.

[0110] In some embodiments, an AGV path planning device based on cold and heat degrees may further include a display screen 52, an input / output interface 53, a communication interface 54, a power supply 55, and a communication bus 56.

[0111] Those skilled in the art can understand that Figure 7 the structure shown in does not constitute a limitation on an AGV path planning device based on cold and heat degrees, and may include more or fewer components than those shown in the figure.

[0112] An AGV path planning device based on cold and heat degrees provided by an embodiment of the present application includes a memory and a processor. When the processor executes a program stored in the memory, the following method can be implemented: an AGV path planning method based on cold and heat degrees.

[0113] The AGV path planning device based on cold and heat degrees provided in this embodiment obtains a global grid map obtained by pre-modeling the drivable area of the AGV through the processor, and calculates the frequency of the AGV passing through each grid within a unit time, and quantifies the passing cold and heat degrees; further, when obtaining a logistics task, sets a corresponding task priority for each logistics task, determines the passable grid area of the current logistics task through the task priority, and determines the shortest path within the passable grid area according to the shortest path algorithm. It realizes the effect of avoiding logistics tasks with low task priorities from occupying grids with frequent AGV passages, thereby alleviating traffic congestion. At the same time, the shortest path algorithm can also ensure that the AGV path is relatively short, the AGV path planning is more intelligent, improves logistics efficiency, and better meets the actual logistics transportation needs.

[0114] Finally, the present application also provides an embodiment corresponding to a computer-readable storage medium. A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps recorded in the above method embodiment are implemented.

[0115] It can be understood that if the method in the above embodiments is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods described in various embodiments of the present application. And the foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0116] A computer-readable storage medium provided in this embodiment, when the computer program stored therein is executed, can realize obtaining a global grid map obtained by pre-modeling the drivable area of the AGV, and calculating the frequency of the AGV passing through each grid within a unit time, and quantifying the cold and hot degrees of passage; and by setting task priorities for each logistics task, it can be realized that the passable grid area of the current logistics task can be determined through the task priority, and the passing permissions of logistics tasks of different importance can be determined, and the shortest path can be determined according to the shortest path algorithm within the passable grid area. It can avoid the situation that logistics tasks with low task priorities occupy grids with frequent AGV passages, thereby alleviating the traffic congestion effect. At the same time, the shortest path algorithm can also ensure that the AGV path is relatively short, the AGV path planning is more intelligent, improve the logistics efficiency, and better meet the actual logistics transportation needs.

[0117] The above has introduced in detail a method, device and medium for AGV path planning based on cold and hot degrees provided by this application. The embodiments in the specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of this application, several improvements and modifications can be made to this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0118] It should also be noted that in this specification, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

Claims

1. An AGV path planning method based on cold and heat degrees, characterized in that, Including: Obtain the global grid map and the task information corresponding to the AGV; wherein, the global grid map includes a plurality of interconnected grids, and each grid corresponds to a passage cold and heat degree determined according to the historical passage data of the AGV; the passage cold and heat degree represents the passage frequency of the AGV passing through this grid, and the higher the passage cold and heat degree value, the higher the passage frequency of this grid; the task information includes a task priority, and the task priority is used to indicate the priority of the AGV path planning. The more important the task, the higher the task priority, and the corresponding task level is higher. The AGV path of the material transportation task with a high task level is preferentially planned; there is a one-to-one correspondence between the task priority and the passage cold and heat degree; In the global grid map, select the grids with the passage cold and heat degree less than or equal to the task priority as the passable grids for each AGV according to the task priority; Plan the shortest driving path for each AGV according to the passable grids.

2. The AGV path planning method based on cold and heat degrees according to claim 1, characterized in that, It also includes: When a grid is planned as the shortest driving path, mark this grid as the occupied state; Correspondingly, when all AGVs corresponding to this grid pass through this grid according to the shortest driving path, mark this grid as the unoccupied state.

3. The AGV path planning method based on cold and heat degrees according to claim 2, wherein, The correspondence between the task priority and the passage cold and heat degree is a one-to-one correspondence. The passable grids are: in the global grid map, the grids with the passage cold and heat degree less than or equal to the task priority, and the grids with the passage cold and heat degree greater than the task priority but marked as the unoccupied state.

4. The AGV path planning method based on cold and heat degrees according to claim 1, characterized in that When multiple AGVs pass through the same grid, it also includes: Each AGV arranges the passage order according to the strategy of first come, first go.

5. The AGV path planning method based on cold and heat degrees according to any one of claims 1 to 4, characterized in that, Determining the passage cold and heat degree of each grid according to the historical passage data includes: According to the historical passage data, count the passage times of each grid; Determine the passage cold and heat degree of each grid according to the passage times of each grid by the first formula; Wherein, the first formula is: H i is the passing cold and heat degree of grid i, S is the total number of grids, N i is the passing times of grid i, N a is the average passing times of each grid, N m is the maximum passing times in each grid, k is the level of the passing cold and heat degree, and n is the number of levels for dividing the passing cold and heat degree.

6. The AGV path planning method based on cold and heat degrees according to claim 5, characterized in that The global grid map is updated periodically. Each time it is updated, the actual passage data of the previous cycle is used as the historical passage data to determine the passage cold and heat degree of each grid.

7. An AGV path planning device based on cold and heat degrees, characterized in that, Including: An information acquisition module, used to obtain the global grid map and the task information corresponding to the AGV; wherein, the global grid map includes a plurality of interconnected grids, and each grid corresponds to a passage cold and heat degree determined according to the historical passage data of the AGV; the passage cold and heat degree represents the passage frequency of the AGV passing through this grid, and the higher the passage cold and heat degree value, the higher the passage frequency of this grid; the task information includes a task priority, and the task priority is used to indicate the priority of the AGV path planning. The more important the task, the higher the task priority, and the corresponding task level is higher. The AGV path of the material transportation task with a high task level is preferentially planned; there is a one-to-one correspondence between the task priority and the passage cold and heat degree; A grid determination module, used to select the grids with the passage cold and heat degree less than or equal to the task priority as the passable grids for each AGV in the global grid map according to the task priority; A path planning module, configured to plan the shortest driving path for each AGV according to the passable grids.

8. An AGV path planning device based on cold and heat degrees, characterized in that, It includes: A memory, configured to store computer programs; A processor, configured to implement the steps of the AGV path planning method based on cold and heat degrees as described in any one of claims 1 to 6 when executing the computer programs.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the AGV path planning method based on cold and heat degrees as described in any one of claims 1 to 6 are implemented.

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