Line planning method and system for freight robot

Abstract

The invention discloses a route planning method and system for a freight robot, and the method comprises the steps: generating a plurality of to-be-evaluated routes according to a starting point and an ending point; determining the passing cost of each to-be-evaluated route, wherein the passing cost indicates the advancing obstruction degree of each route; and according to the passing cost of each to-be-evaluated route, selecting an optimal route from the plurality of to-be-evaluated routes. The advancing efficiency of the robot and the efficiency of logistics carrying operation are improved.

Description

Technical Field

[0001] The present invention 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 Art

[0002] An AGV, or freight robot, is an automated device that can flexibly transport goods between designated locations. It can accurately grasp, move and place goods through its core controller, transfer platform and multiple sensors.

[0003] The path rule of the existing walking surface trolley when traveling is: according to the TA table, that is, the time action table, to complete the travel from the starting point to the destination. From the starting point to the destination, it usually travels along the conventional route, generally according to the landmarks cut or arranged by humans to complete the travel task planned by the time action table. In theory, the walking surface trolley will not go in the reverse direction to prevent the problem of collision with other trolleys or blocking the travel of other trolleys, which makes the travel efficiency of the walking surface trolley need to be improved. Summary of the invention

[0004] The purpose of the present invention is to provide a route planning scheme that takes into account the problem of reverse travel of a walking surface trolley, so as to improve the actual travel efficiency of the route.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a route planning method for a freight robot, comprising: generating multiple routes to be evaluated based on a starting point and an end point; determining a passing cost for each route to be evaluated, wherein the passing cost indicates the degree of travel obstruction of each route; and selecting an optimal route from the multiple routes to be evaluated based on the passing cost of each route to be evaluated.

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

[0007] Preferably, the step of determining the degree of travel obstruction of each route to be evaluated includes: calculating the travel obstruction value of the corresponding route according to the current congestion time of the route to be evaluated, the travel distance of the robot and whether it is a reverse route, so as to use the travel obstruction value to characterize the degree of travel obstruction, and the travel obstruction value is a value obtained by cost calculation of the route to be evaluated; or calculating the cost coefficient experienced by passing through each route to be evaluated, so as to use the cost coefficient to characterize the degree of travel obstruction.

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

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

[0010] or

[0011] costF(t i )=Δ*n*t

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

[0013] Preferably, the step of selecting the optimal route from the multiple routes to be evaluated according to the passing cost of each route to be evaluated includes: calculating the actual passing time of the route under the corresponding passing cost value according to the passing cost of each route to be evaluated; sorting all the routes to be evaluated according to the degree of travel obstruction, and preferentially selecting the route with the shortest actual passing time as the optimal route.

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

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

[0016] On the other hand, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions, which can implement the steps of the method described above when executed by a processor.

[0017] In addition, an embodiment of the present invention also provides a route planning system for a freight robot, including: a to-be-evaluated route generation module, which is configured to generate multiple to-be-evaluated routes based on a starting point and an end point; a route evaluation module, which is configured to determine a passing cost for each to-be-evaluated route, wherein the passing cost indicates the degree of travel obstruction of each route; and a route selection module, which is configured to select the optimal route from the multiple to-be-evaluated routes based on the passing cost of each to-be-evaluated route.

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

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

[0020] The present invention proposes a route planning method and system for a freight robot. The method and system quantitatively evaluate various factors that affect the efficiency of the route by quantitatively calculating the obstructive costs faced during the route travel. In this way, the present invention breaks through the problem that the conventional robot route planning is based only on the conventional route formed by the time action table as the driving route. The optimal route is selected by comparing the cost value of the conventional route with the unconventional or reverse route, which not only improves the travel efficiency of the robot, but also improves the efficiency of logistics handling operations.

[0021] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0023] Figure 1 A schematic flowchart of the steps of a route planning method for a freight robot according to an embodiment of the present application.

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

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

[0026] The following will describe the implementation methods of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies 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 of the present invention and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0027] In addition, the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions. Also, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described can be performed in a sequence different from that here.

[0028] The terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "one", "one" and "item" used herein are also intended to include plural numbers. It should also be understood that the terms "include" and / or "comprise" used herein specify the existence of stated features, integers, steps, operations, units and / or components, without excluding the existence or addition of one or more other features, integers, steps, operations, units, components and / or combinations thereof.

[0029] An AGV, or freight robot, is an automated device that can flexibly transport goods between designated locations. It uses a core controller, a transfer platform, and a variety of sensors to accurately grasp, move, and place goods.

[0030] The path rule of the existing walking surface trolley when traveling is: according to the TA table, that is, the time action table, to complete the travel from the starting point to the destination. From the starting point to the destination, it usually travels along the conventional route, generally according to the landmarks cut or arranged by humans to complete the travel task planned by the time action table. In theory, the walking surface trolley will not go in the reverse direction to prevent the problem of collision with other trolleys or blocking the travel of other trolleys, which makes the travel efficiency of the walking surface trolley need to be improved.

[0031] In order to solve the problems in the above background technology, an embodiment of the present invention provides a route planning method and system for a freight robot. The method and system quantitatively evaluate each route to be evaluated by calculating the walking path cost, thereby selecting the best route. Therefore, the present invention improves the actual travel efficiency of the walking surface vehicle by selecting the best route.

[0032] Embodiment 1

[0033] Figure 1 This is a schematic diagram of the steps of the route planning method for a freight robot according to an embodiment of the present application. Figure 1 The specific steps and procedures of the route planning method described in the embodiment of the present invention are described.

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

[0035] In addition, the route planning method described in the embodiment of the present invention can be applied to a variety of logistics and warehousing scenarios. Therefore, the freight robot described in the embodiment of the present invention can be operated in a sorting plant, a sorting platform, and an intelligent stereoscopic warehouse.

[0036] Step S110, generating a plurality of routes to be evaluated according to the starting point and the end point.

[0037] In an embodiment of the present invention, the moving task of the freight robot (i.e., AGV, Automated Guided Vehicle) is completed in a freight yard map, which is formed by combining multiple moving cells in a grid array. For example, the moving cells are implemented by carpets or floors with preset size specifications, so that the freight yard provides a moving space for the freight robot to walk on carpets or special floors. The intersection of grid lines in the freight yard map forms nodes.

[0038] Therefore, in step S110, first, the starting point and the end point of the current traveling task are determined, and the starting point and the end point are marked on the grid nodes in the freight yard map composed of multiple traveling cells.

[0039] Then, a plurality of routes to be evaluated are generated according to the starting nodes and the end nodes marked in the freight yard map, wherein the plurality of routes to be evaluated include a conventional route formed based on the action schedule, and at least one reverse route and / or unconventional route.

[0040] In the embodiment of the present invention, the unconventional route is a detour route compared to the conventional route generated based on the action schedule. The reverse route is the reverse route of the conventional route of the current freight robot and all unconventional routes without causing destructive abnormal impact on the actual travel routes of other freight robots, so as to shorten the travel time and improve efficiency.

[0041] It should be noted that although the routes to be evaluated formed by the embodiments of the present invention take into account both reverse routes and / or unconventional routes, these routes to be evaluated will not cause damage or abnormal effects on the actual travel routes of other freight robots, such as collision or obstruction.

[0042] In addition, corresponding route information is generated for each route to be evaluated generated in step S110, wherein the route information of each route to be evaluated includes: the location of the starting node, the location of each cell along the route, and the location of the end node.

[0043] After obtaining the route information of each route to be evaluated, the process proceeds to step S120.

[0044] Step S120, determining the passing cost of each route to be evaluated. The passing cost indicates the degree of travel obstruction of each route.

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

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

[0047] In an embodiment of the present invention, the travel obstacle value is a quantitative cost value corresponding to the actual obstacle to the completion of the travel task that the current freight robot has to pay when traveling on the current route. The smaller the travel obstacle value, the higher the completion efficiency of the current travel task faced by the freight robot, that is, the travel obstacle value is negatively correlated with the completion efficiency of the travel task. In one embodiment, the travel obstacle value can be obtained by assignment or calculation.

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

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

[0050] In the embodiment of the present invention, the cost (value) is a comprehensive quantitative representation value of the main factors affecting the route travel efficiency considered when the current freight robot is traveling on the current route.

[0051] In one embodiment, the passing cost of the current route to be evaluated may be determined according to the number of travel cells, the predicted travel time, and the travel obstacle value of the current route to be evaluated.

[0052] In an embodiment of the present invention, the predicted travel time refers to the ideal travel time required to move directly from the starting point along the cells along the route to the end point, which is predicted based on the number of travel cells and the actual driving speed of the robot. This ideal travel time does not take into account other factors that hinder travel, such as congestion and collision.

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

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

[0055] Where i represents the serial number of the route to be evaluated, f(i) represents the travel obstacle value of the i-th route to be evaluated (in seconds), n represents the number of travel cells of the current route to be evaluated, t represents the predicted travel time of a travel cell, and t i represents the predicted travel time of the i-th evaluated route in the absence of obstacles (i.e., t i =n*t), costF represents the passing cost of the current line to be evaluated.

[0056] In another embodiment, step S120 can also calculate the cost coefficient experienced by the freight robot when passing through each route to be evaluated, so as to use the cost coefficient to characterize the degree of travel obstruction. At this time, step S120 will also determine the passing cost (value) of each route to be evaluated based on the cost coefficient faced by successfully passing the current route to be evaluated and the predicted travel time. The cost coefficient represents the coefficient of the travel cost faced by the walking surface vehicle when successfully passing the current route (for example: the cost coefficient in the case of congestion is higher than the cost coefficient in the case of a non-congested route).

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

[0058] costF(t i )=Δ*t i (2)

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

[0060] Among them, Δ represents the cost coefficient faced when passing through the i-th route to be evaluated.

[0061] After calculating the passing cost of each route to be evaluated, the embodiment of the present invention proceeds to step S130.

[0062] Step S130, selecting the best route from the multiple routes to be evaluated according to the passing cost of each route to be evaluated.

[0063] In step S130, first, according to the passing cost of each route to be evaluated, the actual passing time (i.e., evaluation time) of the corresponding route under the corresponding passing cost is determined. Then, all the routes to be evaluated are sorted by the passing cost of each route, and the route with the smallest actual passing time is preferentially selected as the optimal route. Generally speaking, the route with the lowest passing cost also takes the least time.

[0064] Specifically, all routes to be evaluated are first sorted according to the passing cost value, so that the route with the minimum passing cost value is used as the optimal travel route of the current freight robot, so that the optimal travel route selected by the current freight robot completes the current travel task.

[0065] Reference below Figure 2 , the specific implementation principle, i.e., steps, of the route planning method described in the embodiment of the present invention are explained.

[0066] Figure 2 Schematic diagram of the principle of route optimization in the route planning method for a freight robot in an embodiment of the present application. Figure 2 As shown, the current travel task is to travel from point B to point A and then return to point B, and the direction from B to A is taken as the forward direction (to reduce interference between vehicles). According to the forward regulations, the AGV first completes the travel from B to C, that is, the regular route formed based on the action schedule (as an example, the unit of the travel carpet is used as the benchmark, 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 ↑) is path L1, and when going from A to B, follow the forward regulations. At the same time, a reverse path L2 is formed that has no destructive abnormal effects on the actual travel process of other robots. In addition, Figure 2 Also shown is an unconventional route, namely a detour route L3.

[0067] The travel obstacle values ​​of paths L1, L2, and L3 are assigned according to the congestion time, travel distance, and whether or not reversible travel is possible, and the evaluation time calculation results of the passing cost values ​​of paths L1, L2, and L3 are calculated respectively using the above expression (1).

[0068] Time dimension example: path L1 is congested, L2 is not congested, L3 is not congested, f L1 = 10s, L1 evaluation time = number of travel units * travel time + travel obstacle value = 8 * 0.3s + 10 = 12.4s; f L2 = 0.1, L2 evaluation time = number of travel units * travel time + travel obstacle value = 0.1 + 2 * 0.3s = 0.7s; f L3=1, L3 evaluation time = passing cost + number of travel units * travel time = 1 + 12 * 0.3s = 4.6s. At this time, when there are only paths L1 and L2 in the route to be evaluated, the passing cost of path L1 is much greater than the passing cost of path L2. Even in the reverse direction, the walking surface car can choose the travel mode of path L2. In addition, when there are paths L1, L2 and L3 in the route to be evaluated, the passing cost of path L2 is the smallest. In some cases, when a vehicle appears on a reverse road such as L2, the passing cost will surge to 10, and the L2 evaluation time = 10.7s. Even if it takes a long detour, the walking surface car can choose the travel mode of path L3.

[0069] Alternatively, the above expression (2) is used to calculate the actual link passing time (ie, evaluation time) of the paths L1, L2, and L3 respectively.

[0070] Path L1 is congested, but L2 is not congested, △ L1 =10, L1 evaluation time = cost coefficient * 8 * 0.3s = 24; △ L2 =1, L2 evaluation time = 1*0.6s = 0.6. At this time, when there are only paths L1 and L2 to be evaluated, the passing cost and evaluation time of path L1 are much greater than the passing cost of path L2, so even if it is going in the reverse direction, the walking surface car can choose the traveling mode of path L2.

[0071] Embodiment 2

[0072] Based on the route planning method described in the first embodiment, the embodiment of the present invention 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, and the computer instructions include computer program code, which can be in source code form, object code form, executable file, or some intermediate form.

[0073] Computer-readable storage media may include: any entity or device that can carry computer program code, recording media, USB flash drives, mobile hard disks, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

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

[0075] Embodiment 3

[0076] Based on the route planning method described in the first embodiment, the present invention also provides a route planning system for a freight robot. The route planning system is used to implement the route planning method. It should be noted that the route planning system described in the embodiment of the present invention can be integrated into a controller or processor for controlling a freight robot.

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

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

[0079] In addition, the route planning system described in the embodiment of the present invention can be applied to a variety of logistics and warehousing scenarios. Therefore, the freight robot described in the embodiment of the present invention can be operated in a sorting plant, a sorting platform, and an intelligent stereoscopic warehouse.

[0080] The present invention discloses a route planning method and system for a freight robot. The method and system quantitatively evaluate various factors affecting the efficiency of the route by quantitatively calculating the obstructive costs faced during the route travel. In this way, the present invention breaks through the problem that the conventional route planning of the traditional robot is only based on the conventional route formed by the time action table as the driving route. The optimal route is selected by comparing the cost value of the conventional route with the unconventional or reverse route, which not only improves the travel efficiency of the robot, but also improves the efficiency of logistics handling operations.

[0081] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any person familiar with the technology within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0082] In the description of the present invention, unless otherwise specified, "plurality" means two or more than two; the orientations or positional relationships indicated by the terms "upper", "lower", "left", "right", "inner", "outer", "front end", "rear end", "head", "tail", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0083] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0084] It should be understood that the embodiments disclosed in the present invention are not limited to the specific structures, processing steps or materials disclosed herein, but should be extended to equivalent substitutions of these features understood by ordinary technicians in the relevant field. It should also be understood that the terms used herein are only used for the purpose of describing specific embodiments and are not meant to be limiting.

[0085] The "one embodiment" or "embodiment" mentioned in the specification means that the specific features, structures or characteristics described in conjunction with the embodiment are included in at least one embodiment of the present invention. Therefore, the phrases "one embodiment" or "embodiment" appearing in various places throughout the specification do not necessarily refer to the same embodiment.

[0086] Although the embodiments disclosed in the present invention are as above, the contents described are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A route planning method for a freight robot, characterized in that: include: Generate multiple routes to be evaluated based on the starting point and the end point; Determine a passing cost for each route to be evaluated, wherein the passing cost indicates a degree of travel obstruction of each route; According to the passing cost of each route to be evaluated, an optimal route is selected from the multiple 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 according to the starting point and the end point includes: Marking the starting point and the end point on a grid node in a freight yard map consisting of a plurality of travel cells; According to the starting point node and the ending point node, a plurality of routes to be evaluated are generated, including a conventional route formed based on the action schedule and at least one reverse route and / or an unconventional route, wherein each route to be evaluated includes: a plurality of cells of a starting point, an ending point, and a route.

3. The route planning method according to claim 2, characterized in that: The steps of determining the degree of travel obstruction for each route to be evaluated include: Calculate the travel obstacle value of the corresponding route according to the current congestion time of the route to be evaluated, the travel distance of the robot, and whether it is a reverse route, so as to use the travel obstacle value to characterize the travel obstacle degree, and the travel obstacle value is a value obtained by calculating the cost of the route to be evaluated; or The cost coefficient experienced by passing through each route to be evaluated is calculated, so as to use the cost coefficient to characterize the degree of travel obstruction.

4. The route planning method according to claim 2 or 3, characterized in that: The passing cost is determined according to the number of travel cells, the travel time and the travel obstacle value of the current route, or determined by the cost coefficient, wherein the passing cost value of each route to be evaluated is calculated using the following expression: costF(t i ) = n * t + f(i) or costF(ti) = Δ * n * t Among them, i represents the serial number of the route to be evaluated, f(i) represents the travel obstacle value of the i-th 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 a travel cell, Δ represents the cost coefficient faced when passing through the i-th route to be evaluated, and costF represents the passing cost of the current route to be evaluated.

5. The route planning method according to any one of claims 1 to 4, characterized in that: The step of selecting the best route from the plurality of routes to be evaluated according to the passing cost of each route to be evaluated includes: According to the passing cost of each route to be evaluated, the actual passing time of the route under the corresponding passing cost value is calculated; All routes to be evaluated are sorted using the passing costs, and the route with the shortest actual passing time is preferentially selected as the optimal route.

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

7. The route planning method according to any one of claims 1 to 6, characterized in that: The freight robot operates in a sorting plant, a sorting platform and an intelligent stereoscopic warehouse.

8. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the method according to any one of claims 1 to 7.

9. A route planning system for a freight robot, characterized in that: include: A candidate route generation module is configured to generate multiple routes to be evaluated based on the starting point and the end point; a route evaluation module configured to determine a passing cost of each route to be evaluated, wherein the passing cost indicates a degree of travel obstruction of each route; The route selection module is configured to select the best route from the multiple routes to be evaluated according to the passing cost of each route to be evaluated.

10. The route planning system according to claim 9, characterized in that: The freight robot operates in a sorting plant, a sorting platform and an intelligent stereoscopic warehouse.

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