Order splitting method, device and medium suitable for delivery robots with bins of different sizes

Abstract

The present invention discloses a method, device and medium for distributing orders for delivery robots with bins of different sizes, the method comprising: classifying goods according to the sizes that can be accommodated in the bins, obtaining the number of goods of each size, and setting rules for placing goods in the bins of the delivery robots; obtaining the total number of robots that deliver goods based on the number of goods of each size and the rules for placing goods in the bins of the delivery robots; converting the order distributing problem into a numerical optimization problem, constructing the objective function and constraint conditions of the numerical optimization problem based on the total number of robots that deliver goods and the total number of goods; solving the numerical optimization problem, considering the constraint conditions when solving, and obtaining a goods distribution plan; and assigning the distribution tasks to each robot for sequential execution based on the goods distribution plan. The present invention can improve the delivery efficiency of express delivery and promote the intelligent development of the entire logistics industry.

Description

Technical Field

[0001] The present invention relates to the technical field of robot order splitting and scheduling, and in particular to an order splitting method, device and medium suitable for a delivery robot with compartments of different sizes. Background Art

[0002] With the rapid development of e-commerce, the demand for express delivery services is increasing. Consumers not only want to receive packages quickly, but also want the accuracy and safety of delivery services to be guaranteed. Express delivery companies must ensure that every package can be delivered accurately to customers. This requires efficient order splitting and delivery strategies in the delivery process, especially in the last mile delivery, to cope with the growing express delivery volume.

[0003] At the same time, delivery robots are widely used in express delivery. Traditionally, the compartment design of these delivery robots is uniform, designed to accommodate most standard packages. However, as market demand changes, the size and weight of packages have shown a trend of diversification, and delivery robots gradually need to adapt to compartments of different sizes. This change has brought new challenges to the robot delivery system, because the original order splitting method is difficult to effectively handle these diverse needs.

[0004] Currently, the order splitting method for delivery robots with different sized compartments is not mature yet, and there is a lack of systematic and intelligent solutions on the market. Traditional order splitting methods often rely on manual operations, which are inefficient and prone to errors, and cannot adapt to the rapidly changing express delivery environment. This puts express delivery companies under tremendous pressure in terms of resource utilization and delivery efficiency, affecting the overall service quality and customer satisfaction. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an order splitting method, equipment and medium suitable for delivery robots with compartments of different sizes, which can perform intelligent and reasonable express distribution for compartments of different sizes. The delivery robot can efficiently store and transport parcels in different compartments, thereby improving the efficiency and flexibility of the entire delivery process.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for splitting orders for a delivery robot with bins of different sizes, comprising the following steps:

[0008] S1: Classify the goods according to the size that the cell can accommodate, obtain the quantity of goods of each size, and set the rules for placing the goods in the cell of the delivery robot;

[0009] S2. Obtain the total number of robots delivering goods based on the number of goods of each size and the rules for placing goods in the delivery robot compartments;

[0010] S3: Convert the order splitting problem into a numerical optimization problem, and construct the objective function and constraints of the numerical optimization problem based on the total number of robots delivering goods and the total number of goods;

[0011] S4: Solve the numerical optimization problem, taking the constraints into consideration, and obtain the cargo distribution plan;

[0012] S5: Based on the cargo delivery plan, the delivery tasks are assigned to each robot for sequential execution.

[0013] To optimize the above technical solutions, the specific measures taken also include:

[0014] Furthermore, in S1, the rules for placing goods into the delivery robot compartment are specifically:

[0015] Each compartment of the robot can only hold one item. The specifications of the robots in the same scenario must be consistent. The size of the items must not exceed the robot's maximum compartment. As long as the size of the compartment is not exceeded, the items are allowed to be placed in the compartment.

[0016] Furthermore, S3 is specifically:

[0017] Find the distance between two cargo delivery points, taking the distance as the cost,

[0018] The optimization goal is set to minimize the total distance of distribution, and the objective function is:

[0019] ;

[0020] Where N is the total number of goods, K is the total number of robots delivering goods, is the cost between the distribution point of cargo i and the distribution point of cargo j, Indicates whether robot k is assigned to take the route from the delivery point of cargo i to the delivery point of cargo j. ;

[0021] The constraints include:

[0022] The number of robots departing from the post station shall not exceed the number of robots that can deliver all the goods; the delivered goods shall not exceed the maximum capacity of the robots; for each robot, before arriving at the goods delivery point, it can only depart from one of all the goods delivery points, and there cannot be multiple departure points; for each robot, after departing from the goods delivery point, it can only reach one goods delivery point; each cargo is delivered only once; each cargo can be delivered.

[0023] Furthermore, in S4, the numerical solver used to solve the numerical optimization problem is OR-TOOLS; the parameters of the numerical solver are configured under limited computing resources, and the parameters include the method of obtaining initial values, local search options and solution time limit.

[0024] Furthermore, S5 is specifically:

[0025] S5.1. Get the order splitting result;

[0026] S5.2, determine whether there is an idle robot, if so, proceed to step S5.3, otherwise, wait for an idle robot;

[0027] S5.3. Allocate the goods to the robot based on the order splitting result, and the robot delivers the goods;

[0028] S5.4, determine whether the robot has been to the last cargo delivery point; if so, return to the post station, otherwise continue delivery;

[0029] S5.5. Determine whether there are any goods in the robot compartment. If so, take out the goods as stranded goods and wait for the next delivery. Otherwise, determine whether the results of this order splitting have been processed. If so, proceed to step S5.6. Otherwise, return to step S5.3.

[0030] S5.6. Re-sort the stranded goods and return to step S5.1.

[0031] Furthermore, the step of obtaining the distance between two cargo delivery points specifically includes:

[0032] First determine whether the two cargo delivery points are on the same floor. If they are on the same floor, use the Euclidean distance as the cost. If the two points are not on the same floor, first calculate the Euclidean distance from the starting point to the elevator point on the starting floor , the Euclidean distance from the elevator point on the final floor to the final destination , and the cost of taking the elevator ; The cost between two points across floors .

[0033] The present invention also proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the order splitting method applicable to delivery robots with compartments of different sizes as described above is implemented.

[0034] The present invention also proposes a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the above-mentioned order splitting method applicable to a delivery robot with compartments of different sizes.

[0035] The beneficial effects of the present invention are as follows: the present invention can dynamically adjust the order splitting strategy according to the characteristics of the package, the usage of the compartment and the delivery demand; the delivery robot can efficiently store and transport packages in different compartments, thereby improving the efficiency and flexibility of the entire delivery process, providing consumers with better services, and promoting the intelligent development of the entire logistics industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flow chart of the order splitting method proposed by the present invention and applicable to a delivery robot with bins of different sizes;

[0037] Figure 2 Schematic diagram of a delivery robot with compartments of different sizes according to an embodiment of the present invention;

[0038] Figure 3 is a schematic diagram of different cargo sizes in an embodiment of the present invention;

[0039] Figure 4 This is a flowchart of assigning tasks to each robot for sequential execution in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0041] Embodiment 1

[0042] The present invention proposes a method for splitting orders applicable to delivery robots with bins of different sizes. The flowchart of the method is as follows: Figure 1 As shown, the following steps are included:

[0043] S1: The goods are classified according to the size that the cells can accommodate, the quantity of goods of each size is obtained, and the rules for placing the goods in the cells of the delivery robot are set; the rules for setting the goods to be placed in the cells of the delivery robot are specifically:

[0044] Each compartment of the robot can only hold one item. The specifications of the robots in the same scenario must be consistent. The size of the items must not exceed the robot's maximum compartment. As long as the size of the compartment is not exceeded, the items are allowed to be placed in the compartment.

[0045] like Figure 2All the bins shown in the figure are classified by size in this embodiment, and there are a total of 4 types of bins. From small to large, they are defined as S, M, L, and XL. Specifically, the robot on the left has 4 S bins, 2 M bins, and 2 L bins, while the robot on the right has 2 L bins and 1 XL bin. The present invention example takes a delivery robot with 2 L bins and 1 XL bin as an example. The robot is shown in the figure. Figure 2 Without loss of generality, the results can be extended to delivery robots with other compartment configurations.

[0046] In this embodiment, since the goods are express parcels, the goods are bound to the compartments. During the delivery process, the goods and the compartments are in a one-to-one relationship, so only one express can be placed in each compartment. If multiple express are placed, the binding relationship will be disordered. When there is a one-to-one relationship between the express and the compartment, the express can be traced one-to-one if necessary later.

[0047] In this example, robots in the same scene need to be of the same type. Figure 2 There are actually three types of delivery robots, because the three robots have different compartment configurations. The compartments of the delivery robot on the left are 4S+2M+2L, the compartment of the robot in the middle is 4L, and the robot on the left is 2L+2XL. These three types of robots cannot exist in the same station at the same time, otherwise it will be impossible to solve. However, multiple robots of the same type can exist in the same station, such as the existence of three robots on the right at the same time.

[0048] Due to the size limit of the cell, goods that exceed the cell size cannot be placed in the cell. Therefore, when the post station chooses whether to use robots for delivery, it should determine whether the size of the goods exceeds the size of the robot's largest cell. Otherwise, robots cannot be used for delivery and manual delivery is required.

[0049] As attached Figure 3 As shown, the example of the present invention classifies the goods. According to the four types of compartments described in S1, the goods need to be divided into five categories, namely S goods, M goods, L goods, XL goods, and out-of-range goods. Out-of-range goods indicate that their size has exceeded the size of the XL compartment. XL goods indicate that they can only be placed in the XL compartment and not in the L compartment; L goods indicate that they can be placed in the L compartment but not in the M compartment; M goods indicate that they can be placed in the M compartment but not in the S compartment; and S goods indicate goods that can be placed in the S compartment. In practice, goods can be classified manually or automatically. If a manual method is used, the goods should be classified according to the smallest compartment in which they can be placed.

[0050] During the order splitting process, as long as the compartment can accommodate the goods, for example, S goods can be placed not only in S compartments, but also in M, L or XL compartments. This method can avoid the situation where the same user has multiple small goods, but the S compartment is full, then other specifications of the compartment can be used, such as M compartment. The benefit of this operation is that it is possible to reduce the number of deliveries and improve the efficiency of delivery. This requirement is the main difference from the ordinary CVRP (capacitated vehicle routing problem) problem.

[0051] This example uses the post station in an office building as the usage scenario, and introduces the following scenario of express delivery to the post station. According to the survey, it will arrive at the post station at a fixed time every day, and there are generally two waves a day, a morning wave and an afternoon wave. At other times, there is generally no express delivery to the express station. After the courier receives a wave of goods, it will be sorted and delivered. In the invention example, the post station staff is used to enter (goods order number and size) and classify the goods, and the method of the present invention is used to divide the orders, and the robot then delivers the goods. The present invention assigns each cargo to the corresponding robot for delivery according to certain optimization criteria.

[0052] S2. The total number of robots delivering goods is obtained based on the number of goods of each size and the rules for placing goods in the delivery robot compartments. In this embodiment, a robot with two L compartments and one XL compartment is used, so the vehicle capacity is defined as , .

[0053] Need to arrange A robot is used for delivery. It should be the number of robots that can deliver all the goods. For this example, .

[0054] The present invention mainly solves the following order splitting problems:

[0055] a) Which cargo should be assigned to which robot;

[0056] b) which goods are better to be delivered with which goods;

[0057] c) How to deliver all goods as quickly as possible;

[0058] d) How to meet the requirement of placing small goods into large compartments when splitting orders, such as placing S goods into L compartments.

[0059] Next, the present invention converts these order splitting problems into optimization problems, and then uses an optimization solver to solve the problems.

[0060] S3: Convert the order splitting problem into a numerical optimization problem, and construct the objective function and constraints of the numerical optimization problem based on the total number of robots delivering goods and the total number of goods;

[0061] S31: The original requirement is to minimize the total time. Assuming that the robot's movement speed is constant, the time is proportional to the distance, so the distance can be used directly as the cost. In order to reduce the amount of calculation during optimization, this embodiment calculates the cost between the two cargo delivery points in advance, and defines the cost between the delivery point of cargo i and the delivery point of cargo j as Define the station as point.

[0062] Generally, office buildings use cross-floor delivery robots, and the goods delivery locations may be on the same floor or across floors. In this embodiment, we first determine whether the two points are on the same floor. If they are on the same floor, we directly use the Euclidean distance as the cost. If the two points are not on the same floor, first calculate the Euclidean distance from the starting point to the elevator point on the starting floor. , the Euclidean distance from the elevator point on the final floor to the final destination , and the cost of taking the elevator Since the cost of taking an elevator is difficult to calculate, an estimated cost is used in the embodiment. is 100. Then the cost between two points across the floor .

[0063] S32: Set the optimization goal to minimize the total distance of delivery. Assume that there is Express delivery, of which the quantity of S, M, L, and XL goods are , , , , the total number of goods , and sort the goods by size from small to large .

[0064] Based on the total number of robots delivering goods and the total number of goods, the objective function is:

[0065] ;

[0066] Where N is the total number of goods, K is the total number of robots delivering goods, is the cost between the distribution point of cargo i and the distribution point of cargo j, Indicates whether robot k is arranged to take the route from the delivery point of cargo i to the delivery point of cargo j, ;

[0067] At the same time, according to the requirements definition, the following constraints should be met:

[0068] (a) The total number of vehicles departing from the post should not exceed the number of robots , ;

[0069] (b) The delivered goods do not exceed the maximum capacity of the vehicle. In this example, XL goods can only be delivered in XL compartments. , and the total number of goods on each robot cannot exceed the total number of L and XL compartments ;

[0070] (c) For each robot, before arriving at the delivery point of item j, it can only start from one of the delivery points of item i, not multiple. ;

[0071] (d) For each robot, starting from the delivery point of cargo i, it can only reach one delivery point of cargo j. ;

[0072] (e) each item is delivered only once, ;

[0073] (f) each Goods can be delivered, .

[0074] In the above constraints, for:

[0075] , where Indicates whether the item i is delivered by robot k;

[0076] and for:

[0077] , where Indicates whether the item j is delivered by robot k.

[0078] S4: Solve the numerical optimization problem, taking the constraints into account when solving it, and obtain the cargo distribution plan.

[0079] In this example, Google's OR-TOOLS is used for solving. OR-TOOLS is an open source software for combinatorial optimization, which strives to find the best solution to a problem from a large set of possible solutions. The optimization problem proposed in S3 can actually be considered a variant of the CVRP problem. The CVRP problem is specifically designed to solve the problem of how to allocate robots with limited capacity to pick up and put goods at different locations. In CVRP, each robot has a maximum capacity, and each cargo will occupy a different capacity. At each moment, the total capacity of the cargo carried by each robot cannot exceed the maximum capacity.

[0080] The biggest difference between the optimization problem of the present invention and the CVRP problem is that the present invention allows small goods to be placed in large compartments, while the CVRP problem only considers the size of the goods, and does not consider the problem of robots having compartments of various sizes, nor does it consider the mixed use. In order to use OR-TOOLS for solving, the definition of the robot load and the goods is modified in this example.

[0081] In this example, assume that there is There are goods that need to be delivered, and there are goods that can only be loaded into XL compartments but not L compartments (defined as XL goods). Then the remaining goods are those that can be loaded into both XL and L compartments. indivual.

[0082] Set the number of robots used in the solver to the maximum number of robots that need to be used. Each robot has two capacities, one is L capacity and the other is XL capacity. For the robots in this example, S31 is defined , However, in order to use OR-TOOLS to solve the problem, and to be able to put small goods into the XL compartment, , .

[0083] Next, define the capacity occupied by each specification of goods. An L-sized item occupies one L-slot capacity of the robot, and an XL-sized item occupies one XL-slot capacity and one additional L-slot capacity. For example, if the robot originally did not deliver any goods, its available capacity should be 3 L-slots + 1 XL-slot. If an L-sized item is assigned to the robot, the available capacity will be 2 L-slots and 1 XL-slot. If an XL-sized item is assigned to the robot, the available capacity will be 2 L-slots and 0 XL-slots, and only 2 L-sized items can be assigned.

[0084] Based on the above design, if a machine has been assigned 3 L-sized items, the remaining L-sized items will be 0, and XL-sized items will not be assigned to the robot, because one XL-sized item needs to occupy one L-sized bin and one XL-sized bin. This satisfies the requirement that the robot can hold up to 3 L-sized items.

[0085] After the problem is defined, the result of cargo distribution can be obtained by calling the OR-TOOLS solver.

[0086] The solution obtained by OR-TOOLS is not necessarily the best. The CVRP problem itself is an NP-hard problem. When the number of couriers is large (generally there are hundreds of couriers arriving at the courier station in one wave), the solution space is very large. Due to the limitation of server computing resources, it often takes a lot of time to get the best result.

[0087] OR-TOOLS can set the solver effect by configuring 3 parameters: initial value method, local search option and solution time limit.

[0088] Therefore, in the example of the present invention, the method for obtaining the initial value is set to PATH_CHEAPEST_ARC, the local search option is set to GUIDED_LOCAL_SEARCH, and the solution time limit is 5s. If it exceeds 5s, the program will return a suboptimal result.

[0089] S5: Based on the cargo delivery plan, the delivery tasks are assigned to each robot for sequential execution. Figure 4 As shown, specifically:

[0090] S5.1. Get the order splitting result;

[0091] S5.2, determine whether there is an idle robot, if so, proceed to step S5.3, otherwise, wait for an idle robot;

[0092] S5.3. Allocate the goods to the robot based on the order splitting result, and the robot delivers the goods;

[0093] S5.4, determine whether the robot has been to the last cargo delivery point; if so, return to the post station, otherwise continue delivery;

[0094] S5.5. Determine whether there are any goods in the robot compartment. If so, take out the goods as stranded goods and wait for the next delivery. Otherwise, determine whether the results of this order splitting have been processed. If so, proceed to step S5.6. Otherwise, return to step S5.3.

[0095] S5.6. Re-sort the stranded goods and return to step S5.1.

[0096] For example, the post station has 3 robots, but when optimizing the order splitting, the number of robots used is entered as , in the result, only the first 8 robots distribute goods. Then first assign the first 3 tasks in the result to the 3 currently idle robots. When the express of the first task is loaded into the robot's compartment, the robot can start the delivery without waiting for all 3 tasks to be loaded before starting. After the robot starts, the second task is loaded to the second robot, and so on.

[0097] After the robot has delivered the assembled goods, it needs to return to the post station to accept the next task. If there are parcels in the robot that have not been taken out by the user, the staff of the post station will take the parcels out of the robot and put them in the queue to wait for re-assignment. If all the parcels have been taken out of the robot, the system will assign the first task that has not been executed in the optimization result to the robot that has returned to the post station.

[0098] After all tasks in the last optimization result are completed, the system will re-sort the stranded express and then deliver it. If the express has been stranded twice, it will be classified as abnormal express and wait for manual processing, and robot delivery will no longer be used.

[0099] Embodiment 2

[0100] The present invention proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the order splitting method applicable to delivery robots with compartments of different sizes as described in Example 1.

[0101] Embodiment 3

[0102] The present invention proposes a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the order splitting method applicable to a delivery robot with compartments of different sizes as described in Example 1.

[0103] In the embodiments disclosed in the present application, the computer storage medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or apparatus. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. More specific examples of computer storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CDROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0104] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0105] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A method for splitting orders for delivery robots with compartments of different sizes, characterized in that: The following steps are involved: S1: Classify the goods according to the size that the cell can accommodate, obtain the quantity of goods of each size, and set the rules for placing the goods in the cell of the delivery robot; S2. Obtain the total number of robots delivering goods based on the number of goods of each size and the rules for placing goods in the delivery robot compartments; S3: Convert the order splitting problem into a numerical optimization problem, and construct the objective function and constraints of the numerical optimization problem based on the total number of robots delivering goods and the total number of goods; S3 is specifically: Find the distance between two cargo delivery points, taking the distance as the cost, The optimization goal is set to minimize the total distance of distribution, and the objective function is: ； Where N is the total number of goods, K is the total number of robots delivering goods, is the cost between the distribution point of cargo i and the distribution point of cargo j, Indicates whether robot k is assigned to take the route from the delivery point of cargo i to the delivery point of cargo j. ; The constraints include: The number of robots that depart from the post station shall not exceed the number of robots that can deliver all the goods; the goods delivered shall not exceed the maximum capacity of the robots; Each robot can only start from one of all the delivery points before reaching the delivery point, and cannot have multiple delivery points. Each robot can only reach one delivery point after starting from the delivery point. Each item is delivered only once. Each item can be delivered. S4: Solve the numerical optimization problem, taking the constraints into consideration, and obtain the cargo distribution plan; S5: Based on the cargo delivery plan, the delivery tasks are assigned to each robot for sequential execution.

2. The order splitting method applicable to a delivery robot with bins of different sizes as claimed in claim 1, characterized in that: In S1, the rules for placing goods into the delivery robot compartment are specifically: Each compartment of the robot can only hold one item. The specifications of the robots in the same scenario must be consistent. The size of the items must not exceed the robot's maximum compartment. As long as the size of the compartment is not exceeded, the items are allowed to be placed in the compartment.

3. The order splitting method applicable to a delivery robot with bins of different sizes as claimed in claim 1, characterized in that: In S4, the numerical solver used to solve the numerical optimization problem is OR-TOOLS; the parameters of the numerical solver are configured under limited computing resources, and the parameters include the method of obtaining initial values, local search options and solution time limit.

4. The order splitting method applicable to a delivery robot with bins of different sizes as claimed in claim 1, characterized in that: S5 is as follows: S5.

1. Get the order splitting result; S5.2, determine whether there is an idle robot, if so, proceed to step S5.3, otherwise, wait for an idle robot; S5.

3. Allocate the goods to the robot based on the order splitting result, and the robot delivers the goods; S5.4, determine whether the robot has been to the last cargo delivery point; if so, return to the post station, otherwise continue delivery; S5.

5. Determine whether there are any goods in the robot compartment. If so, take out the goods as stranded goods and wait for the next delivery. Otherwise, determine whether the results of this order splitting have been processed. If so, proceed to step S5.

6. Otherwise, return to step S5.

3. S5.

6. Re-sort the stranded goods and return to step S5.

1.

5. The order splitting method applicable to a delivery robot with bins of different sizes as claimed in claim 1, characterized in that: The method of obtaining the distance between two cargo delivery points specifically includes: First determine whether the two cargo delivery points are on the same floor. If they are on the same floor, use the Euclidean distance as the cost. If the two points are not on the same floor, first calculate the Euclidean distance from the starting point to the elevator point on the starting floor , the Euclidean distance from the elevator point on the final floor to the final destination , and the cost of taking the elevator ; The cost between two points across floors .

6. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the order splitting method applicable to a delivery robot with compartments of different sizes as described in any one of claims 1 to 5 is implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the order splitting method applicable to a delivery robot with compartments of different sizes as described in any one of claims 1 to 5.

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