A method and system for route planning for a freight robot

Abstract

The application discloses a route planning method and system for a freight robot, and comprises the following steps: generating a plurality of to-be-evaluated routes according to a starting point and an ending point; determining a passing cost of each to-be-evaluated route, the passing cost indicating the degree of travel obstruction of each route; and selecting an optimal route from the plurality of to-be-evaluated routes according to the passing cost of each to-be-evaluated route. The application improves the travel efficiency of the robot and the efficiency of a logistics handling operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of logistics robot route planning, and in particular to a route planning method and system for a freight robot. BACKGROUND

[0002] The walking surface trolley, namely the freight robot (AGV), is an automated device capable of flexible carrying of goods between designated locations. The device realizes precise grabbing, moving and placing of goods through a core controller, a moving platform and various sensors.

[0003] The path rule of the existing walking surface trolley during travel is as follows: according to a T-A table, namely a time-action table, to complete travel from a starting point to a destination. From the starting point to the destination, the trolley usually travels according to a conventional route, which is generally completed according to a landmark artificially cut or arranged to complete the travel task planned by the time-action table. In theory, the walking surface trolley will not be allowed to travel in reverse to prevent the problem of colliding with other trolleys or blocking the travel of other trolleys, which makes the travel efficiency of the walking surface trolley to be improved. SUMMARY

[0004] The present application aims to provide a route planning scheme considering the problem of reverse travel of the walking surface trolley to improve the actual travel efficiency of the route.

[0005] To solve the above technical problems, the present application provides a route planning method for a freight robot, comprising: generating a plurality of to-be-evaluated routes according to a starting point and a destination; determining a passing cost of each to-be-evaluated route, the passing cost indicating the degree of travel obstruction of each route; and selecting an optimal route from the plurality of to-be-evaluated routes according to the passing cost of each to-be-evaluated route.

[0006] Preferably, in the step of generating a plurality of to-be-evaluated routes according to a starting point and a destination, the step comprises: marking the starting point and the destination on a grid node in a freight site map composed of a plurality of travel cells; and generating a plurality of to-be-evaluated routes including a conventional route formed based on an action time table and at least one reverse route and / or unconventional route according to the starting point node and the destination node, wherein each to-be-evaluated route comprises: a starting point, a destination and a plurality of cells passed through.

[0007] Preferably, in the step of determining the degree of travel obstruction of each to-be-evaluated route, the following is included: calculating a travel obstruction value of the corresponding route according to the current congestion time of the to-be-evaluated route, the travel distance of the robot, and whether the route is a reverse route, so as to use the travel obstruction value to represent the degree of travel obstruction, wherein the travel obstruction value is a value obtained by performing cost calculation on the to-be-evaluated route; or calculating a cost coefficient experienced by each to-be-evaluated route, so as to use the cost coefficient to represent the degree of travel obstruction.

[0008] Preferably, the passing cost is determined according to the number of travel cells of the current route, the travel time, and the travel obstruction value, or is determined by the cost coefficient, wherein the passing cost value of each to-be-evaluated route is calculated by using the following expression:

[0009] costF(t i )=n*t+f(i)

[0010] or

[0011] costF(t i )=Δ*n*t

[0012] wherein i represents the serial number of the to-be-evaluated route, f(i) represents the passing cost value of the ith to-be-evaluated route, n represents the number of travel cells of the current to-be-evaluated route, t represents the travel time of one travel cell, Δ represents the cost coefficient faced when passing the ith to-be-evaluated route, and costF represents the passing cost of the current to-be-evaluated route.

[0013] Preferably, in the step of selecting the optimal route from the plurality of to-be-evaluated routes according to the passing cost of each to-be-evaluated route, the following is included: calculating the actual passing time of the route corresponding to the passing cost value according to the passing cost of each to-be-evaluated route; sorting all to-be-evaluated routes according to the degree of travel obstruction, and preferentially selecting the route with the minimum actual passing time as the optimal route.

[0014] Preferably, the freight robot includes, but is not limited to, a walking surface trolley, a platform trolley, or a shelf trolley of an intelligent vertical warehouse.

[0015] Preferably, the freight robot operates in a sorting plant, a sorting table, and an intelligent vertical warehouse.

[0016] In another aspect, the embodiment of the present application provides a computer readable storage medium storing computer executable instructions, which, when executed by a processor, implement the steps of the method described above.

[0017] In addition, the embodiment of the present application further provides a route planning system for the freight robot, comprising: a candidate route generation module configured to generate a plurality of to-be-evaluated routes according to a starting point and an ending point; a route evaluation module configured to determine a passing cost of each to-be-evaluated route, the passing cost indicating a degree of travel obstruction of each route; and a route selection module configured to select an optimal route from the plurality of to-be-evaluated routes according to the passing cost of each to-be-evaluated route.

[0018] Preferably, the freight robot operates in a sorting plant, a sorting table and an intelligent warehouse.

[0019] Compared with the prior art, one or more embodiments of the above scheme can have the following advantages or beneficial effects:

[0020] The present application provides a route planning method and system for a freight robot. The method and system complete quantitative evaluation of various factors affecting the efficiency of the travel route by quantitative calculation of the obstructive cost faced in the travel process. In this way, the present application breaks through the problem that the conventional route formed based on the time action table is used as the travel route in the traditional robot route planning, and optimizes the best travel route by comparing the cost values of the conventional route and the unconventional or reverse route, thereby improving the travel efficiency of the robot and the efficiency of the logistics handling operation.

[0021] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application will be realized and achieved by means of the structures particularly pointed out in the description and the claims. BRIEF DESCRIPTION OF DRAWINGS

[0022] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, illustrate embodiments of the present application, and are used to explain the present application together with the description. The drawings do not limit the present application. In the drawings:

[0023] Figure 1 A step flow diagram of the route planning method for the freight robot according to the embodiment of the present application.

[0024] Figure 2 A principle diagram of route optimization in the route planning method for the freight robot according to the embodiment of the present application.

[0025] Figure 3 A system structure diagram of the route planning system for the freight robot according to the embodiment of the present application. DETAILED DESCRIPTION

[0026] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in the various embodiments of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0027] Furthermore, the steps illustrated in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in a different order than that shown here.

[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms “a” and “an” as used herein are also intended to include the plural. It should also be understood that the terms “comprising” and / or “including” as used herein specify the presence of the stated features, integers, steps, operations, units, and / or components, without excluding the presence or addition of one or more other features, integers, steps, operations, units, components, and / or combinations thereof.

[0029] A mobile cargo robot (AGV) is an automated device that enables the flexible transport of goods between designated locations. Through its core controller, transfer platform, and various sensors, it achieves precise grasping, moving, and placement of goods.

[0030] The existing path pattern of the walking surface vehicle is as follows: it follows the TA table, i.e., the time-action table, to complete the journey from the starting point to the destination. From the starting point to the destination, it usually follows a conventional route, generally completing the journey planned in the time-action table by following artificially cut or arranged landmarks. Theoretically, the walking surface vehicle should not be allowed to travel in reverse to prevent collisions or obstruction of other vehicles. This means that the walking surface vehicle's efficiency needs to be improved.

[0031] To address the problems described in the background section, this invention provides a route planning method and system for freight robots. This method and system quantitatively evaluate each route by calculating the cost of the travel path, thereby selecting the optimal route. Thus, this invention improves the actual travel efficiency of the robot by selecting the optimal route.

[0032] Example One

[0033] Figure 1 This is a flowchart illustrating the steps of a route planning method for a freight robot according to an embodiment of this application. The following refers to...Figure 1 The specific step flow of the line planning method described in the embodiments of the present application is explained.

[0034] The freight robot described in the embodiments of the present application can be a robot applied to all logistics and warehousing scenarios. In the embodiments of the present application, the freight robot includes but is not limited to a walking surface trolley or an upper platform trolley or a shelf trolley of an intelligent stereoscopic warehouse.

[0035] In addition, the line planning method described in the embodiments of the present application can be applied to various logistics and warehousing scenarios. Therefore, the freight robot described in the embodiments of the present application can run in a sorting plant, a sorting table and an intelligent stereoscopic warehouse.

[0036] In step S110, a plurality of to-be-evaluated lines are generated according to the start point and the end point.

[0037] In the embodiments of the present application, the travel task of the freight robot (i.e., a walking surface trolley, AGV, Automated Guided Vehicle) is completed in a freight site map formed by a grid array composed of a plurality of travel cells. For example, the travel cells are implemented by using carpets or floors with preset size specifications, so that the freight site provides a travel space for the freight robot to walk on the carpet or the specially designed floor. The intersection of the grid lines in the freight site map forms a node.

[0038] Therefore, in step S110, first, the start point position and the end point position of the current travel task are determined, and the start point and the end point are marked on the grid node in the freight site map composed of a plurality of travel cells.

[0039] Then, according to the start point node and the end point node marked in the freight site map, a plurality of to-be-evaluated lines are generated. Among the plurality of to-be-evaluated lines, there is a regular route formed based on a motion schedule, and at least one reverse route and / or an irregular route.

[0040] In the embodiments of the present application, the irregular route is a detour path compared with the regular route generated based on the motion schedule. The reverse route is the reverse path of the regular route and all irregular routes of the current freight robot without causing a damaging abnormal influence on the actual travel route of other freight robots, so as to shorten the travel time and improve the efficiency.

[0041] It should be noted that the to-be-evaluated lines formed in the embodiments of the present application consider the reverse route and / or the irregular route, but these to-be-evaluated lines will not cause a damaging abnormal influence on the actual travel route of other robots, such as collision, blocking, etc.

[0042] In addition, the line information of each to-be-evaluated route is generated according to the to-be-evaluated route generated in step S110. The line information of each to-be-evaluated route includes a start node position, a position of each cell passed through, and an end node position.

[0043] After the line information of each to-be-evaluated route is obtained, step S120 is entered.

[0044] In step S120, the passing cost of each to-be-evaluated route is determined. The passing cost indicates the degree of travel obstruction of each route.

[0045] In step S120, the degree of travel obstruction of each to-be-evaluated route is calculated according to the line information of each to-be-evaluated route.

[0046] In the embodiment of the present application, the degree of travel obstruction can be represented by a travel obstruction value or a cost coefficient.

[0047] In the embodiment of the present application, the travel obstruction value is a quantitative cost degree value corresponding to the actual obstruction of the travel task to be completed by the current freight robot when the current freight robot travels in the current route. The smaller the travel obstruction value, the higher the completion efficiency of the current travel task faced by the freight robot, that is, the travel obstruction value is negatively correlated with the completion efficiency of the travel task. In an embodiment, the travel obstruction value can be obtained by assignment or calculation.

[0048] In an embodiment, the degree of travel obstruction of the current to-be-evaluated route is calculated according to three conditions, i.e., the current congestion time faced by the to-be-evaluated route, the actual travel distance of the robot, and whether the current route is a reverse route, so as to represent the degree of travel obstruction by a travel obstruction value. Thus, the travel obstruction parameter can be assigned according to the conditions of congestion time, travel distance, and whether the route is reversible.

[0049] Next, in step S120, the passing cost (value) of each to-be-evaluated route is further calculated according to the travel obstruction value of each to-be-evaluated route.

[0050] In the embodiment of the present application, the passing cost (value) is a comprehensive quantitative representation value of the main factors affecting the travel efficiency of the current route when the current freight robot travels in the current route.

[0051] In an embodiment, the passing cost of the current to-be-evaluated route can be determined according to the number of travel cells of the current to-be-evaluated route, the predicted travel time, and the travel obstruction value.

[0052] In the embodiment of the present application, the predicted travel time refers to an ideal travel time predicted according to the number of travel cells and the actual travel speed of the robot for moving from the starting point to the end point along the cells on the route, which does not consider other factors hindering travel such as congestion and collision.

[0053] In one specific embodiment, the passing cost value of each route to be evaluated is calculated by using the following expression:

[0054] costF(t i ) = n*t + f(i) (1)

[0055] wherein i represents the serial number of the route to be evaluated, f(i) represents the travel hindering value (in seconds s) of the ith route to be evaluated, n represents the number of travel cells of the current route to be evaluated, t represents the predicted travel time of one travel cell, t i represents the predicted travel time of the ith route to be evaluated in the case of no hindering (i.e. t i = n*t), and costF represents the passing cost of the current route to be evaluated.

[0056] In another embodiment, the step S120 can also calculate the cost coefficient of the freight robot when passing through each route to be evaluated, so as to use the cost coefficient to represent the degree of travel hindering. At this time, the step S120 will also determine the passing cost (value) of each route to be evaluated according to the cost coefficient and the predicted travel time when smoothly passing through the current route to be evaluated. The cost coefficient represents the coefficient of the travel cost when the trolley smoothly passes through the current route (for example, the cost coefficient in the case of congestion is higher than that in the case of no congestion).

[0057] Specifically, the evaluation time of the route to be evaluated after cost calculation can also be calculated by using the following expression:

[0058] costF(t i ) = Δ*t i (2)

[0059] t i = n*t (3)

[0060] wherein Δ represents the cost coefficient when passing through the ith route to be evaluated.

[0061] After the passing cost value of each route to be evaluated is calculated, the embodiment of the present application enters the step S130.

[0062] The step S130 selects the optimal route from the multiple routes to be evaluated according to the passing cost of each route to be evaluated.

[0063] In step S130, firstly, based on the passage cost of each route to be evaluated, the actual passage time (i.e., evaluation time) corresponding to the corresponding passage cost is determined. Then, all routes to be evaluated are sorted using the passage cost of each route, and the route with the shortest actual passage time is selected as the optimal route. Generally, the route with the lowest passage cost also takes the least time.

[0064] Specifically, all routes to be evaluated are first sorted according to their cost value, and the route with the lowest cost value is selected as the optimal route for the current freight robot, so that the optimal route selected by the current freight robot can complete the current travel task.

[0065] The following is for reference. Figure 2 The specific implementation principle and steps of the route planning method described in the embodiments of the present invention will be explained.

[0066] Figure 2 This is a schematic diagram illustrating the principle of route optimization in the route planning method for a freight robot according to an embodiment of this application. Figure 2 As shown, the current travel task is to move from point B to point A and back to point B, with the direction from B to A considered the forward direction (to reduce interference between vehicles). According to the forward direction rule, the AGV first completes its journey from B to C, following a regular route L1 based on the motion schedule (for example, using the travel mat unit as a reference: 0-0.3s forward ↑; 0.3-0.6s forward ↑; 0.6-0.9s left ←; 0.9-1.2s forward ↑; 1.2-1.5s forward ↑; 1.5-1.8s left ←; 1.8-2.1s forward ↑). The journey from A to B follows the forward direction rule. Simultaneously, a reverse path L2 is formed that does not cause any damage or abnormality to the actual travel of other robots. Furthermore, Figure 2 The text also shows an unconventional route, namely the long detour route L3.

[0067] The travel obstacle values ​​of paths L1, L2, and L3 are assigned based on congestion time, travel distance, and whether reversible travel is possible. The evaluation time calculation results of the passage cost value of paths L1, L2, and L3 are calculated using the above expression (1).

[0068] Example from a time perspective: Path L1 is congested, L2 is not congested, L3 is not congested, f L1 =10s, L1 evaluation time = number of traveling units * traveling time + traveling obstacle value = 8 * 0.3s + 10 = 12.4s; f L2 =0.1, L2 evaluation time = number of traveling units * traveling time + traveling obstacle value = 0.1 + 2 * 0.3s = 0.7s; f L3= 1, L3 evaluation time = through cost value + number of travel units * travel time = 1 + 12 * 0.3s = 4.6s. At this time, in the case that the to-be-evaluated route only has paths L1 and L2, the through cost value of path L1 is far greater than that of path L2, and even if reversing, the walking surface vehicle can still select the travel mode of path L2. In addition, in the case that the to-be-evaluated route has paths L1, L2 and L3, the through cost value of path L2 is the smallest, and in some cases, when a vehicle appears on the reversing road L2, the through cost value will surge to 10, and the L2 evaluation time = 10.7s, even if detouring, the walking surface vehicle can still select the travel mode of path L3.

[0069] Alternatively, the actual route through time (i.e., evaluation time) of paths L1, L2 and L3 is respectively calculated by using the above expression (2).

[0070] Path L1 is congested, L2 is not congested, and L1 = 10, L1 evaluation time = cost coefficient * 8 * 0.3s = 24; and L2 = 1, L2 evaluation time = 1 * 0.6s = 0.6. At this time, in the case that the to-be-evaluated route only has paths L1 and L2, the through cost value and evaluation time of path L1 are far greater than those of path L2, and even if reversing, the walking surface vehicle can still select the travel mode of path L2.

[0071] Example Two

[0072] Based on the route planning method described in the above embodiment one, the embodiment of the present application also provides a computer readable storage medium. The storage medium stores a computer program, and the computer program is executed to run a route planning method for a freight robot. The computer program can run computer instructions, the computer instructions include computer program codes, and the computer program codes can be in the form of source code, object code, executable file or some intermediate form, etc.

[0073] The computer readable storage medium can include any entity or device capable of carrying computer program codes, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0074] It should be noted that the contents of computer-readable storage media may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, the contents may be appropriately increased or decreased according to the requirements of legislation and patent practice. In other jurisdictions, computer-readable storage media may not include electrical carrier signals and telecommunication signals.

[0075] Example Three

[0076] Based on the route planning method described in Embodiment 1 above, this embodiment of the invention also provides a route planning system for a freight robot. This route planning system is used to implement the above-described route planning method. It should be noted that the route planning system described in this embodiment of the invention can be integrated into a controller or processor used to control the freight robot.

[0077] Figure 3 This is a schematic diagram of the system structure of a route planning system for a freight robot according to an embodiment of this application. Figure 3 As shown, the route planning system described in this embodiment of the invention includes: a candidate route generation module 31, a route evaluation module 32, and a route selection module 33.

[0078] Specifically, the candidate route generation module 31 is implemented according to the method described in step S110 above, and is configured to generate multiple routes to be evaluated based on the starting point and the ending point; the route evaluation module 32 is implemented according to the method described in step S120 above, and is configured to determine the passage cost of each route to be evaluated, which indicates the degree of obstruction to travel on each route; the route selection module 33 is implemented according to the method described in step S130 above, and is configured to select the optimal route from multiple routes to be evaluated based on the passage cost of each route to be evaluated.

[0079] Furthermore, the route planning system described in this embodiment of the invention can be applied to various logistics and warehousing scenarios. Therefore, the freight robot described in this embodiment of the invention can operate in sorting plants, sorting stations, and intelligent automated warehouses.

[0080] This invention discloses a route planning method and system for freight robots. The method and system quantitatively evaluate various factors affecting route efficiency by quantitatively calculating the costs of obstacles encountered during route travel. Thus, this invention overcomes the problem of traditional robot route planning relying solely on conventional routes formed by time-action schedules. By comparing the cost of conventional routes with unconventional or reverse routes, the optimal route is selected, improving not only the robot's travel efficiency but also the efficiency of logistics handling operations.

[0081] The above description is merely that of preferred embodiments of the application, but the scope of protection of the application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the application, which should be covered by the scope of protection of the application. Therefore, the scope of protection of the application should be subject to the scope of protection of the claims.

[0082] In the description of the application, unless otherwise specified and limited, the terms "a plurality of" means two or more; the terms "upper", "lower", "left", "right", "inner", "outer", "front end", "rear end", "head", "tail" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are merely for the purpose of facilitating the description of the application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the application. In addition, the terms "first", "second", "third" and the like are only for the purpose of description and cannot be understood as indicating or implying relative importance.

[0083] In the description of the application, it should be noted that, unless otherwise specified and limited, the terms "connected", "connected" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium. For those skilled in the art, the specific meaning of the above terms in the application can be understood according to the specific circumstances.

[0084] It should be understood that the embodiments disclosed in the present application are not limited to the specific structure, processing steps or materials disclosed herein, but should extend to equivalent alternatives of these features understood by those skilled in the relevant art. It should also be understood that the terms used herein are only for the purpose of describing the specific embodiments and do not mean limitation.

[0085] The phrase "one embodiment" or "an embodiment" appearing in the specification means that the specific feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the application. Therefore, the phrase "one embodiment" or "an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment.

[0086] Although the embodiments disclosed in the present application are as described above, the content described is only the embodiments adopted for the purpose of facilitating the understanding of the present application, and is not intended to limit the present application. Any person skilled in the art can make any modification and change in the form and details without departing from the spirit and scope of the present application, but the patent protection scope of the present application should be subject to the scope defined by the appended claims.

Claims

1. A route planning method for a freight robot, characterized in that, The movement task of the freight robot is completed on a freight yard map, which is formed by a grid array of multiple movement cells. Each movement cell uses carpet or flooring of a preset size to provide the freight robot with movement space on the carpet or specially designed flooring. Nodes are formed by the intersections of grid lines in the freight yard map. The route planning method includes: Based on the origin and destination, multiple routes to be evaluated are generated. These multiple routes to be evaluated include regular routes formed based on the action schedule and at least one reverse route and an unconventional route. The unconventional route is a detour route compared to the regular route generated based on the action schedule. The reverse route is the reverse route of the current cargo robot's regular route and all unconventional routes without causing destructive abnormalities to the actual travel routes of other cargo robots. Determine the passage cost for each route to be evaluated, whereby the passage cost indicates the degree of obstruction for each route. This includes: calculating the obstruction value of the corresponding route based on the current congestion time, robot travel distance, and whether it is a reverse route, and using the obstruction value to characterize the degree of obstruction, wherein the obstruction value is a value obtained by calculating the cost for the route to be evaluated; or calculating a coefficient of the passage cost experienced by successfully traversing the current route for each route to be evaluated, and using the calculated cost coefficient to characterize the degree of obstruction. Based on the passage cost of each route to be evaluated, the optimal route is selected from the plurality of routes to be evaluated.

2. The route planning method according to claim 1, characterized in that, The step of generating multiple routes to be evaluated based on the start and end points includes: The starting point and the ending point are marked on the grid nodes of the freight yard map, which consists of multiple travel cells; Based on the starting and ending nodes, multiple routes to be evaluated are generated. Each route to be evaluated includes multiple cells for the starting point, ending point, and route.

3. The route planning method according to claim 2, characterized in that, The transit cost is determined based on the number of travel cells on the current route, the travel time, and the travel obstacle value, or by the cost coefficient. The transit cost for each route to be evaluated is calculated using the following expression: in, i This indicates the sequence number of the route to be evaluated. Indicates the first i The travel resistance value of the route to be evaluated. n This indicates the number of cells in the current route to be evaluated. t This indicates the predicted travel time for a given cell. Indicates that in passing the first i The cost coefficient faced when evaluating a route. This represents the cost of traversing the route currently being evaluated.

4. The route planning method according to any one of claims 1 to 3, characterized in that, The step of selecting the optimal route from the plurality of routes to be evaluated based on the passage cost of each route includes: Calculate the actual travel time of each route under the corresponding travel cost based on the travel cost of each route to be evaluated; All routes to be evaluated are sorted using the aforementioned transit cost, and the route with the shortest actual transit time is selected as the optimal route.

5. The route planning method according to any one of claims 1 to 3, characterized in that, The freight robots include, but are not limited to: walking surface vehicles, platform vehicles, or shelf vehicles in intelligent automated warehouses.

6. The route planning method according to any one of claims 1 to 3, characterized in that, The cargo robots operate in sorting plants, sorting stations, and intelligent automated warehouses.

7. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1 to 6.

8. A route planning system for a freight robot, characterized in that, The movement of the cargo robot is completed on a cargo yard map, which is formed by a grid array of multiple movement cells. Each movement cell uses carpet or flooring of a preset size to provide the cargo robot with movement space on the carpet or specially designed flooring. Nodes are formed by the intersections of grid lines in the cargo yard map. The route planning system includes: The candidate route generation module is configured to generate multiple routes to be evaluated based on the starting point and the ending point. The multiple routes to be evaluated include a regular route formed based on the action schedule and at least one reverse route and an unconventional route. The unconventional route is a detour route compared to the regular route generated based on the action schedule. The reverse route is the reverse route of the current cargo robot's regular route and all unconventional routes without causing destructive abnormalities to the actual travel routes of other cargo robots. The route evaluation module is configured to determine the passage cost of each route to be evaluated, wherein the passage cost indicates the degree of obstruction of each route, including: calculating the obstruction value of the corresponding route based on the current congestion time of the route to be evaluated, the robot's travel distance, and whether it is a reverse route, so as to use the obstruction value to characterize the degree of obstruction, wherein the obstruction value is a value obtained by calculating the cost of the route to be evaluated; or calculating a coefficient of the travel cost experienced by successfully passing through the current route of each route to be evaluated, so as to use the calculated cost coefficient to characterize the degree of obstruction. The route selection module is configured to select the optimal route from the plurality of routes to be evaluated based on the passage cost of each route to be evaluated.

9. The route planning system according to claim 8, characterized in that, The cargo robots operate in sorting plants, sorting stations, and intelligent automated warehouses.

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