Order sorting method and apparatus

Abstract

This invention provides an order sorting method and apparatus. The order sorting method, applied to a sorting system, includes acquiring multiple target orders, destination information for each target order, and the weight of each sorting slot within a sorting area. The weight of each slot is inversely proportional to a reference distance, which is the distance between the slot and the sorting station. Based on the destination information of each target order, the number of orders at each destination is counted to obtain the destination weight of each destination, which is directly proportional to the number of orders. The correspondence between each slot and each destination is determined according to the slot weight and destination weight. Based on the correspondence, a sorting instruction is sent to a sorting robot to drive the robot to sort each target order to its corresponding slot based on the destination information. By establishing the correspondence between slots and destinations, the travel distance for order sorting based on the correspondence is reduced, thus reducing path congestion and conflicts during travel.

Description

Technical Field

[0001] This invention relates to the field of intelligent logistics technology, and in particular to an order sorting method. The invention also relates to an order sorting device, a computing device, and a computer-readable storage medium. Background Technology

[0002] With the development of technology in the logistics industry, the use of robots is becoming more and more widespread. The scheduling and management of multiple robots and task allocation are unavoidable problems in robot sorting systems.

[0003] In the logistics industry, sorting robots are widely used. In practical applications, after a sorting robot is assigned an order, the sorting system can randomly select one of multiple slots as the destination slot for the order. The same approach is taken for other orders. This random selection of the destination slot may increase the travel distance of the robot when performing its task.

[0004] For example, if a destination with a large proportion of orders is assigned a larger distance between its sorting slots, it will increase the distance the robot has to travel when sorting orders. This increased distance will also lead to path congestion and conflicts for the robot. Therefore, there is an urgent need for a method to reasonably allocate sorting slots in order to avoid path conflicts and congestion when the robot is sorting orders. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide an order sorting method applied to a sorting system to address the technical deficiencies existing in the prior art. Embodiments of the present invention also provide an order sorting device applied to a sorting system, a computing device, and a computer-readable storage medium.

[0006] According to a first aspect of the present invention, an order sorting method is provided, applied to a sorting system, comprising:

[0007] Obtain multiple target orders, destination information for each target order, and grid weights for each grid within the sorting area. The grid weights are inversely proportional to the reference distance, which is the distance between the grid and the sorting station.

[0008] Based on the destination information of each target order, the number of orders for each destination is counted to obtain the destination weight of each destination, where the destination weight is directly proportional to the number of orders;

[0009] The correspondence between each grid and each destination is determined according to the weight of each grid and the weight of each destination;

[0010] Based on the correspondence, sorting instructions are sent to the sorting robot to drive it to sort each target order to its corresponding compartment based on the destination information of each target order.

[0011] According to a second aspect of the present invention, an order sorting apparatus is provided, applied to a sorting system, comprising:

[0012] The acquisition module is configured to acquire multiple target orders, destination information of each target order, and grid weight of each grid in the sorting area. The grid weight is inversely proportional to the reference distance, which is the distance between the grid and the sorting station.

[0013] The statistics module is configured to count the number of orders for each destination based on the destination information of each target order, and obtain the destination weight of each destination, wherein the destination weight is directly proportional to the number of orders;

[0014] The relationship determination module is configured to determine the correspondence between each grid and each destination based on the weight of each grid and the weight of each destination.

[0015] The sending module is configured to send sorting instructions to the sorting robot according to the correspondence, so as to drive the sorting robot to sort each target order to the corresponding grid based on the destination information of each target order.

[0016] According to a third aspect of the present invention, a computing device is provided, comprising:

[0017] Memory and processor;

[0018] The memory is used to store computer-executable instructions, and the processor executes the computer-executable instructions to implement the steps of the order sorting method.

[0019] According to a fourth aspect of the present invention, a computer-readable storage medium is provided that stores computer-executable instructions which, when executed by a processor, implement the steps of the order sorting method.

[0020] The order sorting method provided by this invention is applied to a sorting system and includes: acquiring multiple target orders, destination information of each target order, and the weight of each grid within the sorting area, wherein the grid weight is inversely proportional to a reference distance, and the reference distance is the distance between the grid and the sorting station; based on the destination information of each target order, counting the number of orders at each destination to obtain the destination weight of each destination, wherein the destination weight is directly proportional to the number of orders; determining the correspondence between each grid and each destination according to the grid weight and the destination weight; and sending sorting instructions to the sorting robot according to the correspondence to drive the sorting robot to sort each target order to the corresponding grid based on the destination information of each target order. By acquiring multiple target orders and their destination information, the destination weight of each destination is determined. Based on the destination weights and their magnitudes, the correspondence between each sorting grid and its destination is obtained, ensuring that grids with high weights correspond to destinations with high destination weights. The grid weight is inversely proportional to the reference distance, meaning that grids that are closer correspond to a larger number of destinations. This reduces the distance the robot travels during order sorting and further reduces path congestion and conflicts during robot movement. Attached Figure Description

[0021] Figure 1A This is a schematic diagram of a centralized layout in a robot sorting scenario;

[0022] Figure 1B This is a schematic diagram of a platform layout for a robot sorting scenario;

[0023] Figure 2 This is a flowchart of an order sorting method provided in an embodiment of the present invention;

[0024] Figure 3A This is a flowchart of an order sorting method provided in an embodiment of the present invention;

[0025] Figure 3B This is a schematic diagram of a logistics sorting area provided in an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of the structure of an order sorting device according to an embodiment of the present invention;

[0027] Figure 5 This is a structural block diagram of a computing device provided in an embodiment of the present invention. Detailed Implementation

[0028] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0029] The terminology used in one or more embodiments of the present invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of the invention. The singular forms “a,” “the,” and “the” used in one or more embodiments of the invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” used in one or more embodiments of the invention refers to and includes any or all possible combinations of one or more associated listed items.

[0030] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of the present invention, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of the present invention, and similarly, second may also be referred to as first.

[0031] First, the terminology used in one or more embodiments of the present invention will be explained.

[0032] Grid: In logistics order sorting scenarios, a grid is used to sort and store corresponding orders.

[0033] With the development of technology in the logistics industry, the use of robots is becoming more and more widespread. The scheduling and management of robots and the allocation of tasks are unavoidable problems in robot sorting systems.

[0034] In the logistics industry, sorting robots are widely used in various logistics scenarios, for example, see Figure 1A This diagram illustrates a centralized layout for a robot sorting scenario; see also... Figure 1B The diagram illustrates a platform-style layout for a robot sorting scenario. In the two examples of logistics robot sorting scenarios mentioned above, sorting slots are scattered throughout the planned area. How to rationally allocate robot task slots and reduce congestion is one of the main factors in ensuring and improving robot sorting efficiency.

[0035] In practical applications, after a logistics sorting robot is assigned an order, the sorting system can randomly select one of multiple slots as the destination slot for the order. The same approach is taken for other orders. This method of randomly selecting the destination slot may increase the travel distance of the robot when performing the task.

[0036] For example, if a destination with a large proportion of orders is assigned a larger distance between its sorting slots, it will increase the distance the robot has to travel when sorting orders. This increased distance will also lead to path congestion and conflicts for the robot. Therefore, there is an urgent need for a method to reasonably allocate sorting slots in order to avoid path conflicts and congestion when the robot is sorting orders.

[0037] This invention provides an order sorting method applied to a sorting system. The invention also relates to an order sorting device applied to a sorting system, a computing device, and a computer-readable storage medium, which are described in detail in the following embodiments.

[0038] Figure 2 A flowchart of an order sorting method according to an embodiment of the present invention is shown, which is applied to a sorting system and specifically includes the following steps:

[0039] Step 202: Obtain multiple target orders, destination information for each target order, and grid weights for each grid within the sorting area. The grid weights are inversely proportional to the reference distance, which is the distance between the grid and the sorting station.

[0040] When there is a need to sort orders and reduce the distance traveled during sorting, multiple target orders, their destination information, and the weights of each sorting compartment within the sorting area are obtained. This information can be obtained either through user clicks to trigger the sorting system, or according to pre-defined methods, such as pre-setting to retrieve multiple orders in batches or at time intervals. Each time multiple orders are retrieved, the destination information and the weights of each sorting compartment within the sorting area are obtained.

[0041] Specifically, a target order refers to an order awaiting sorting by the robot. A target order can be any order to be sorted and includes its corresponding destination information. Destination information refers to the destination to which the target order is delivered. This destination information can include the address of the destination. For example, if target order 1 is shipped from city A to city B, then when sorting in city C, the destination information for target order 1 will be identified as city B. The sorting area refers to the area where orders are sorted. The sorting area includes at least sorting stations and multiple slots. Slot weight refers to the popularity of a slot within the sorting area. Popularity is inversely proportional to the reference distance; that is, the greater the reference distance, the smaller the slot weight. The reference distance is the distance between the slot and the sorting station. When there is only one sorting station, the reference distance is the distance between the slot and the sorting station; when there are multiple sorting stations, the reference distance is the average distance between the slot and all sorting stations. A sorting station is a station where target orders are sorted. After establishing the correspondence between the sorting station and the target orders, each target order is sorted from the sorting station to the corresponding sorting slot according to the correspondence.

[0042] One way to obtain multiple target orders is to retrieve the orders to be sorted from the order record system and use the retrieved orders as target orders; another way is for the manual entry of the orders to be sorted into the sorting system, and the sorting system determines the entered orders as target orders, i.e., orders to be sorted.

[0043] The way to obtain the destination information of each target order is to identify the physical object corresponding to each target order, read the information recorded on the surface of the physical object, and determine the destination information of the target order based on the recorded information; or the sorting system can obtain the destination information of each target order from the order record system when it obtains multiple target orders from the order record system.

[0044] The method for obtaining the grid weight of each grid in each sorting area can be either from a weight repository that stores grid weights, or it can be calculated based on the location information of each grid relative to the sorting station.

[0045] The method for calculating the grid weight of each grid based on the location information of each grid and the sorting station can be as follows: obtain the reference distance between each grid and the sorting station based on the location information of each grid and the sorting station, and determine the grid weight of each grid based on the reference distance. The grid weight is inversely proportional to the reference distance.

[0046] By acquiring multiple target orders, their destination information, and the weight of each compartment within the sorting area, the system can establish a correspondence between each compartment and each target order based on this information, and then sort the target orders according to this correspondence.

[0047] Optionally, the above steps for obtaining the grid weights of each grid within the sorting area include the following steps:

[0048] Obtain the location information of each compartment and multiple sorting stations within the sorting area;

[0049] For any given grid, based on the location information of the grid and multiple sorting stations, determine the distance between the grid and each sorting station, and based on each distance, determine the reference distance of the grid.

[0050] Based on the reference distance of each grid cell, the grid cell weight is determined, wherein the grid cell weight of each grid cell is inversely proportional to the reference distance of each grid cell.

[0051] Specifically, location information refers to the position within the sorting area. The location information can be represented by distance, such as sorting slot 1 being 3 meters away from the sorting station on the left and 5 meters away from the sorting station on the top; or it can be represented by coordinates, such as establishing the X-axis and Y-axis with the lower left corner of the sorting area as the origin, and determining the coordinates of each sorting slot and the document station.

[0052] The location information of each compartment and multiple sorting stations within the sorting area can be obtained by retrieving it from a pre-stored location information repository; or by measuring the location based on the current sorting area and determining the measurement result as location information.

[0053] Based on the location information of any sorting grid and multiple sorting stations, the method to determine the distance between any sorting grid and each sorting station can be either to use Manhattan distance to calculate the distance between any sorting grid and each sorting station, or to use A* distance to calculate the distance between any sorting grid and each sorting station.

[0054] The implementation of determining the reference distance of any grid point based on distance can be achieved by summing all distances and using the summed distance as the reference distance of any grid point; it can also be achieved by summing all distances and averaging them to obtain the reference distance of any grid point; or it can be achieved by obtaining the weights corresponding to each distance, weighting the distances based on the weights, and averaging them to obtain the reference distance of any grid point.

[0055] The method to determine the grid weight of each grid based on the reference distance of each grid can be to take the reciprocal of the reference distance and use the reciprocal of the reference distance as the grid weight.

[0056] The solution of this invention obtains the location information of each grid and multiple sorting stations within the sorting area; for any grid, the distance between the grid and the sorting station is determined, and a reference distance corresponding to the grid is determined based on the distance. A grid weight that is inversely proportional to the reference distance is determined. The distance is calculated through the location information, and the weight is determined based on the distance. This enables the subsequent establishment of the correspondence between the grid and the destination based on the grid weight. Specifically, the correspondence between the grid and the destination is established based on the distance between the grids. That is, when establishing the relationship, it is based on the distance between the grids, which reduces the distance for order sorting.

[0057] Step 204: Based on the destination information of each target order, count the number of orders for each destination and obtain the destination weight of each destination. The destination weight is directly proportional to the number of orders.

[0058] Specifically, the order quantity refers to the number of target orders for the same destination. For example, if there are 10 target orders, with 3 destinations in location A, 5 in location B, and 2 in location C, then the number of orders for destination A is determined to be 3, the number of orders for destination B is 5, and the number of orders for destination C is 2. Destination weight refers to the popularity of a destination among multiple target orders. Popularity is directly proportional to the number of orders for that destination; that is, the more orders there are, the greater the destination weight.

[0059] The method of calculating the number of orders for each destination based on the destination information of each target order and obtaining the destination weight of each destination can be implemented in two ways: one is to calculate the number of orders for each destination based on the destination information of each target order and obtain the order percentage of each destination in the multiple target orders, and then determine the destination weight of each destination based on the order percentage; the other is to calculate the number of orders for each destination based on the destination information of each target order and then determine the destination weight of each destination based on the order number.

[0060] One way to determine the destination weight of each destination based on the number of orders is to use the number of orders as the destination weight for each destination.

[0061] Optionally, the above steps, based on the destination information of each target order, count the number of orders for each destination and obtain the destination weight for each destination, including the following steps:

[0062] Based on the destination information of each target order, the number of orders for each destination is counted;

[0063] For any given destination, determine the percentage of orders for that destination among multiple target orders based on the number of orders for that destination.

[0064] Based on the order proportion of each destination, the destination weight of each destination is determined, and the destination weight of each destination is directly proportional to the order proportion of each destination.

[0065] Specifically, the order percentage (p_i) refers to the proportion of the target orders corresponding to a destination among multiple target orders. For example, if the total number of target orders is 10 and the target orders for destination A are 3, then the order percentage for destination A is determined to be 3 / 10.

[0066] The method to count the number of orders for each destination based on the destination information of each target order can be to classify the orders according to different destinations, count the number of orders in each category, and obtain the number of orders for each destination.

[0067] The method to determine the order percentage of any destination in multiple target orders based on the order quantity of any destination can be to divide the order quantity of any destination by the total number of target orders to obtain the order percentage of any destination in multiple target orders.

[0068] The method for determining the destination weight based on the order percentage of each destination can be either to determine the destination weight of each destination based on the order percentage of each destination, or to obtain a baseline value, multiply the order percentage of each destination by the baseline value, and determine the destination weight of each destination based on the result of the multiplication. The baseline value can be a randomly selected value greater than 0.

[0069] By applying the solution of this invention, based on the destination information of each target order, the number of orders for each destination is statistically obtained, and the order proportion of each destination in multiple target orders is obtained, so that the destination weight of each destination can be determined based on the order proportion. The destination weight is determined based on the number of orders corresponding to each destination, so that the subsequent establishment of the correspondence between the destination and the sorting grid based on the weight is also determined based on the number of orders corresponding to the destination. This fully considers the number of orders corresponding to the destination and improves the efficiency of subsequent order sorting based on the correspondence.

[0070] Step 206: Determine the correspondence between each grid and each destination according to the weight of each grid and the weight of each destination.

[0071] Specifically, the correspondence relationship refers to the correspondence between the grid and the destination. The correspondence relationship is used to sort the target order to the corresponding grid.

[0072] The method for determining the correspondence between each grid and each destination based on the grid weight and destination weight can be as follows: First, based on the grid weight and location information of each grid, divide each grid into hot grids and non-hot grids. Second, based on the destination weight and a preset threshold, divide each destination into hot destinations and non-hot destinations, thus determining the correspondence between hot grids and hot destinations, and the correspondence between non-hot grids and non-hot destinations. Alternatively, the correspondence can be established by ranking the grid weight and destination weight from largest to smallest, thereby establishing a one-to-one relationship between each grid and each destination.

[0073] Optionally, the correspondence between each grid and each destination can be determined according to the weight of each grid and the weight of each destination. It can be a one-to-one correspondence, or a many-to-one or one-to-many correspondence. The specific correspondence is determined according to the actual situation, and this invention does not limit it.

[0074] Optionally, the above steps determine the correspondence between each grid and each destination according to the weight of each grid and the weight of each destination, including the following steps:

[0075] Based on the destination weight of each destination, at least one hot destination is identified, and destinations other than hot destinations are identified as non-hot destinations, wherein the destination weight of the hot destination is greater than a first threshold.

[0076] Based on the grid weight of each grid, at least one hot grid is identified, and based on the location information of each hot grid in the sorting area, non-hot grids are identified, wherein the grid weight of the hot grid is greater than a second threshold.

[0077] Based on the grid weight of each hot spot grid and the destination weight of each hot spot destination, establish the correspondence between hot spot grids and hot spot destinations;

[0078] Based on the destination weight of each non-hotspot destination and the location information of each hotspot and non-hotspot grid in the sorting area, a correspondence between non-hotspot grids and non-hotspot destinations is established.

[0079] Specifically, "hotspot destinations" refer to destinations with a weight greater than a first threshold, where any hotspot destination has more orders than any non-hotspot destination. "Non-hotspot destinations" refer to destinations with a weight less than or equal to the first threshold, where the number of orders is less than that of hotspot destinations. The first threshold is a pre-set threshold for distinguishing between hotspot and non-hotspot destinations. This threshold can be set based on multiple target orders currently awaiting sorting, pre-set based on the sorting area's range, or a combination of factors including the number of target orders, the sorting area's range, and the number of compartments within the sorting area.

[0080] Hotspot grids refer to grids within the sorting area whose threshold is greater than a second threshold. Hotspot grids have a shorter reference distance than non-hotspot grids. Non-hotspot grids refer to all grids within the sorting area except for hotspot grids. Non-hotspot grids have a longer reference distance than hotspot grids. The second threshold is the threshold that a hotspot grid's weight must exceed. This second threshold can be set based on the range of the sorting area, the number of grids, or a combination of factors including the grid's location, number, and the sorting area's range.

[0081] The method of identifying at least one hot destination based on the destination weight of each destination and identifying destinations other than hot destinations as non-hot destinations can be as follows: compare the destination weight of each destination with a first threshold, identify the destination with a weight greater than the first threshold as a hot destination, and identify the destinations other than hot destinations as non-hot destinations.

[0082] Optionally, before determining the destinations with destination weights greater than the first threshold as hotspot destinations, the method further includes determining whether the distance between destinations with destination weights greater than the first threshold is greater than the adjacent range. If it is not greater, one of the hotspot grids is determined as a pending hotspot grid, and the distance between other hotspot grids is determined until the hotspot grids with grid weights greater than the second threshold within the sorting area are determined. If the number of hotspot grids is insufficient, a hotspot grid is selected from the pending hotspot grids.

[0083] Based on the grid weights of each grid, at least one hot grid is identified. Based on the location information of each hot grid in the sorting area, the implementation method for determining non-hot grids is determined. This can be achieved by comparing the grid weights of each grid with a second threshold, identifying grids with weights greater than the second threshold as hot grids, and identifying grids other than hot grids as non-hot grids. Based on the location information of hot and non-hot grids, the correspondence between hot and non-hot grids is determined.

[0084] The method for establishing the correspondence between hotspot grids and hotspot destinations based on the grid weight of each hotspot grid and the destination weight of each hotspot destination can be either to establish a one-to-one correspondence between each hotspot grid and each hotspot destination sequentially based on the size of the grid weight of each hotspot grid and the destination weight of each hotspot destination, or to establish a one-to-one correspondence between each hotspot grid and each hotspot destination sequentially based on the size of the grid weight of each hotspot grid and the destination weight of each hotspot destination.

[0085] The method for establishing the correspondence between non-hotspot grids and non-hotspot destinations based on the destination weight of each non-hotspot destination and the location information of each hotspot grid and each non-hotspot grid in the sorting area can be as follows: determine the first reference hotspot grid corresponding to each non-hotspot destination in ascending order of destination weight and each hotspot grid in descending order of hotspot grid weight; and, based on the location information of the first reference hotspot grid and each non-hotspot grid in the sorting area, determine the target non-hotspot grid corresponding to the first reference hotspot grid from the neighborhood of the first reference hotspot grid, thus establishing a one-to-one correspondence between each non-hotspot destination and each target non-hotspot grid.

[0086] The solution of this invention divides the grid into hot grids and non-hot grids, and the destination into hot destinations and non-hot destinations. A correspondence is established between hot grids and hot destinations, and a correspondence is established between non-hot grids and non-hot destinations. This means that grids with relatively close reference distances are associated with destinations with a relatively large number of orders, and grids with relatively far reference distances are associated with destinations with a relatively small number of orders. This avoids destinations with a large number of orders being associated with grids with a far reference distance, and reduces the travel path of the sorting robot when sorting target orders.

[0087] Optionally, the above steps establish a correspondence between hotspot grids and hotspot destinations based on the grid weight of each hotspot grid and the destination weight of each hotspot destination, including the following steps:

[0088] Based on the grid weight of each hotspot grid and the destination weight of each hotspot destination in descending order, a one-to-one correspondence between each hotspot grid and each hotspot destination is established sequentially.

[0089] There are many ways to establish a one-to-one correspondence between each hotspot grid and each hotspot destination, based on the grid weight of each hotspot grid and the destination weight of each hotspot destination in descending order. The specific method depends on the actual situation and is not limited in this invention.

[0090] In one possible implementation of the present invention, each grid is sorted in descending order according to its grid weight to obtain a first ascending order sorting result. Each destination is sorted in descending order according to its destination weight to obtain a second ascending order sorting result. The first ascending order sorting result and the second ascending order sorting result are matched one-to-one to obtain a one-to-one correspondence between each grid and each destination.

[0091] In another possible implementation of the present invention, the hotspot grid with the largest grid weight is selected as the first hotspot grid based on the grid weight of each hotspot grid. The hotspot destination with the largest destination weight is selected as the first hotspot destination based on the destination weight of each hotspot destination. A correspondence between the first hotspot grid and the first hotspot destination is established. The hotspot grid with the second largest grid weight is selected as the second hotspot grid based on the grid weight of each hotspot grid. The hotspot destination with the second largest destination weight is selected as the second hotspot destination based on the destination weight of each hotspot destination. A correspondence between the second hotspot grid and the second hotspot destination is established. This process is repeated to establish a correspondence between each hotspot grid and each hotspot destination.

[0092] The solution of this invention establishes a one-to-one correspondence between each hotspot grid and each hotspot destination in descending order of grid weight and destination weight. This ensures that the correspondence between hotspot grids and hotspot destinations is established in descending order of popularity, thereby reducing the travel distance of the sorting robot when sorting orders according to this correspondence.

[0093] Optionally, before establishing the correspondence between hotspot grids and hotspot destinations based on the grid weights of each hotspot grid and the destination weights of each hotspot destination as described above, the following steps are also included:

[0094] Obtain the number of hotspot grids and the number of hotspot destinations;

[0095] If the number of grids is less than the number of destinations, calculate the difference between the number of grids and the number of destinations;

[0096] Select multiple target non-hotspot cells that meet the difference from the non-hotspot cells, and then identify these multiple target non-hotspot cells as hotspot cells.

[0097] The number of hotspot grids and hotspot destinations is obtained. If the number of hotspot destinations is greater than the number of hotspot grids, grids are selected from non-hotspot grids as hotspot grids to make up the difference between the number of hotspot grids and the number of hotspot destinations. The embodiments of this invention are used to sort target orders. In order to ensure the efficiency of target order sorting and reduce path conflicts when sorting robots sort orders, it is necessary to ensure that at least one hotspot destination corresponds to one grid. Therefore, when the number of hotspot destinations is greater than the number of hotspot grids, it is necessary to make up the difference in the number of hotspot grids.

[0098] If the number of grids is less than the number of destinations, before calculating the difference between the number of grids and the number of destinations, it also includes determining the relative sizes of the number of grids and the number of destinations.

[0099] When the number of grids is less than the number of destinations, the difference between the number of grids and the number of destinations can be calculated by subtracting the number of grids from the number of destinations.

[0100] The method of selecting multiple target non-hot grids that meet the difference from non-hot grids and determining multiple target non-hot grids as hot grids can be based on the grid weight of non-hot grids, selecting multiple target non-hot grids that meet the difference from non-hot grids, and determining multiple target non-hot grids as hot grids.

[0101] The solution of this invention obtains the number of hotspot grids and the number of hotspot destinations. When the number of grids is less than the number of hotspot destinations, the difference is calculated, and a target non-hotspot grid that meets the difference is selected from the non-hotspot grids as a hotspot grid. This ensures that when establishing a correspondence between hotspot grids and hotspot destinations in the future, the correspondence is established between hotspot grids and hotspot destinations. As a result, when sorting orders based on the correspondence, the travel distance of the sorting robot is reduced.

[0102] Optionally, the above steps involve selecting multiple target non-hotspot cells that match the difference from the non-hotspot cells, including the following steps:

[0103] According to the grid weight of each hot spot grid in ascending order, select multiple target hot spot grids that meet the difference value from each hot spot grid;

[0104] From the neighborhood of each target hotspot grid, select non-hotspot grids whose grid weight reaches the third threshold;

[0105] Update the selected non-hotspot grids to hotspot grids.

[0106] Specifically, the domain range refers to the pre-defined range that limits the non-hotspot grid corresponding to the hotspot grid. For example, the domain range can be 1 or 2. The size of the specific range is determined according to the actual size of the sorting area, which is not limited in this invention.

[0107] The implementation method of selecting multiple target hotspot grids that meet the difference value from each hotspot grid in ascending order of grid weight can be to sort the grid weights of each hotspot grid in ascending order and select the hotspot grids that meet the difference value as target hotspot grids.

[0108] The method to select non-hotspot grids whose grid weight reaches the third threshold from the neighborhood of each target hotspot grid can be to sort the target hotspot grids according to their weights from smallest to largest, and then select a non-hotspot grid whose weight reaches the third threshold from the neighborhood of each sorted target hotspot grid.

[0109] The method to update the selected non-hot grids to hot grids can be to update the selected non-hot grids from non-hot grids to hot grids.

[0110] For example, when the difference is 2, the 5 hot grids are sorted in ascending order of grid weight as follows: A, B, C, D, E. Hot grid A and hot grid B are selected as target hot grids. From the adjacent range of hot grid A and hot grid B, a non-hot grid with a grid weight reaching the third threshold is selected respectively. The selected non-hot grid is then updated as a hot grid.

[0111] The solution of this invention involves selecting multiple target hotspot grids that meet the difference value from each hotspot grid in ascending order of grid weight. Then, grids with grid weights greater than a threshold are selected from the neighborhood of the target hotspot grids to update them as hotspot grids. By completing the steps of completing the hotspot grids, at least one hotspot grid corresponds to the hotspot destination, which reduces the travel distance of the sorting robot when sorting orders based on the correspondence.

[0112] Optionally, the above steps establish a correspondence between non-hotspot slots and non-hotspot destinations based on the destination weight of each non-hotspot destination and the location information of each hotspot slot and each non-hotspot slot in the sorting area, including the following steps:

[0113] Based on the destination weights of each non-hotspot destination from smallest to largest and the hotspot grids from largest to smallest, the first reference hotspot grid corresponding to each non-hotspot destination is determined.

[0114] Based on the location information of the first reference hot spot in the sorting area and the location information of each non-hot spot in the sorting area, the target non-hot spot corresponding to the first reference hot spot is determined from the neighborhood of the first reference hot spot.

[0115] Establish a one-to-one correspondence between each non-hotspot destination and each target non-hotspot grid.

[0116] Specifically, the first reference hotspot grid refers to the hotspot grid that corresponds to the non-hotspot destination and allows for selection of non-hotspot grids within the adjacent range.

[0117] There are many ways to determine the first reference hotspot grid corresponding to each non-hotspot destination, based on the order of destination weight from smallest to largest and hotspot grid from largest to smallest. The specific method depends on the actual situation and is not limited in this invention.

[0118] In one possible implementation of the present invention, non-hotspot destinations are sorted in ascending order based on their destination weights to obtain a first reverse sorting result; hotspot grids are sorted in descending order based on their grid weights to obtain a third forward sorting result; and the first reference hotspot grid corresponding to each non-hotspot destination is determined based on the first reverse sorting result and the third forward sorting result.

[0119] In another possible implementation of the present invention, the method may be as follows: based on the destination weights of each non-hotspot destination, the non-hotspot destination with the smallest destination weight is selected as the first non-hotspot destination; based on the grid weights of each hotspot grid, the hotspot grid with the largest grid weight is selected as the first hotspot grid, and the first hotspot grid is determined as the first reference hotspot grid for the first non-hotspot destination; based on the destination weights of each non-hotspot destination, the non-hotspot destination with the second smallest destination weight is selected as the second non-hotspot destination; based on the grid weights of each hotspot grid, the hotspot grid with the second largest grid weight is selected as the second hotspot grid, and the second hotspot grid is determined as the first reference hotspot grid for the second non-hotspot destination, and so on, to determine the first reference hotspot grid corresponding to each non-hotspot destination.

[0120] In another possible implementation of the present invention, the grid with the largest grid weight is selected as the first hot grid based on the grid weight of each hot grid, and the first number of non-hot grids in the adjacent range of the first hot grid is obtained; based on the destination weight of each non-hot destination, the non-hot destinations that meet the first number are selected in ascending order of destination weight as the first non-hot destinations; and the first hot grids are used as the first reference hot grids corresponding to the first non-hot destinations.

[0121] Based on the location information of the first reference hot spot grid in the sorting area and the location information of each non-hot spot grid in the sorting area, the implementation method of the target non-hot spot grid corresponding to the first reference hot spot grid is determined from the neighborhood of the first reference hot spot grid. Based on the location information of the first reference hot spot grid in the sorting area and the location information of each non-hot spot grid in the sorting area, the non-hot spot grids in the adjacent range of the first reference hot spot grid are determined, and the target non-hot spot grid corresponding to the first reference hot spot grid is selected from each non-hot spot grid.

[0122] By applying the scheme of this invention, the first reference hot spot grid corresponding to each non-hot spot destination is determined according to the order of weight of each non-hot spot destination from small to large and the order of hot spot grid from large to small. Based on the location information, the target non-hot spot grid corresponding to the first reference hot spot grid is determined, and a one-to-one correspondence between the target non-hot spot grid and the target non-hot spot destination is established. This ensures that the destination with the lower destination weight is associated with the grid with the higher grid weight, thus separating the grid corresponding to the hot spot destination from the grid corresponding to the hot spot destination. This ensures the path balance of the sorting robot during subsequent sorting, reduces path conflicts for the sorting robot, and improves the efficiency of order sorting.

[0123] Optionally, after establishing the correspondence between non-hotspot grids and non-hotspot destinations in the above steps, the following steps are also included:

[0124] In the case of remaining cells without established relationships, select reference remaining cells whose cell weight is greater than the fourth threshold.

[0125] Establish a one-to-one correspondence between each reference remaining grid and each destination, based on the grid weights of each reference remaining grid from smallest to largest and the destination weights of each destination from largest to smallest.

[0126] Specifically, "remaining grid cells" refers to grid cells for which no corresponding relationship has been established after the establishment of the corresponding relationships in the above embodiments. The fourth threshold is a pre-set threshold for filtering grid cell weights; it is determined by the number of hotspot destinations and grid cells. "Reference remaining grid cells" refers to remaining grid cells whose weights are greater than the fourth threshold.

[0127] One way to select reference remaining cells from the remaining cells whose cell weights are greater than the fourth threshold is to compare the cell weights of the remaining cells with the fourth threshold and determine the cells with cell weights greater than the fourth threshold as reference remaining cells.

[0128] Optionally, the implementation of setting the fourth threshold can be as follows: obtain the target number of hotspot destinations and the target difference between the number of grids and the number of hotspot destinations, select the smaller one from the target number and the target difference as the selection number, sort the remaining grids in descending order according to their grid weights, determine the target grid weight of the selected number of remaining grids from the sorting results, and use the determined target grid weight as the fourth threshold.

[0129] There are many ways to establish a one-to-one correspondence between each reference remaining grid and each destination, based on the grid weights of each reference remaining grid from smallest to largest and the destination weights of each destination from largest to smallest. The specific method depends on the actual situation and is not limited in this invention.

[0130] In one possible implementation of the present invention, the reference remaining cell with the smallest cell weight is selected as the first reference remaining cell based on the cell weight of each reference remaining cell, and the destination with the largest destination weight is selected as the first destination based on the destination weight of each destination, thus establishing a correspondence between the first reference remaining cell and the first destination; the reference remaining cell with the second smallest cell weight is selected as the second reference remaining cell based on the cell weight of each reference remaining cell, and the destination with the second largest destination weight is selected as the second destination based on the destination weight of each destination, thus establishing a correspondence between the second reference remaining cell and the second destination, and so on, to establish a one-to-one correspondence between each reference remaining cell and each destination.

[0131] In another possible implementation of the present invention, the reference remaining grids are sorted in reverse order according to their grid weights to obtain a second reverse sorting result; the destinations are sorted in ascending order according to their destination weights to obtain a fourth ascending sorting result; and a one-to-one correspondence between each reference remaining grid and each destination is established sequentially based on the second reverse sorting result and the fourth ascending sorting result.

[0132] By applying the solution of this invention, when there are remaining grids without established correspondence, reference remaining grids with grid weights greater than a fourth threshold are selected from the remaining grids. Based on the grid weights of the reference remaining grids from small to large and the destination weights from large to small, a one-to-one correspondence between the reference remaining grids and the destinations is established, so that all reference remaining grids selected from the remaining grids have established correspondence with the destinations respectively, thereby improving the efficiency of subsequent order sorting through the correspondence.

[0133] Optionally, after establishing a one-to-one correspondence between each reference remaining grid and each destination in the above steps according to the grid weights of each reference remaining grid from smallest to largest and the destination weights of each destination from largest to smallest, the following steps are also included:

[0134] In the case of unconnected surplus grids and surplus destinations, count the first number of surplus grids and the second number of surplus destinations.

[0135] When the difference between the first quantity and the second quantity reaches the fifth threshold, the second reference hotspot grid corresponding to each remaining destination is determined according to the destination weight of each remaining destination from small to large and the hotspot grid from large to small.

[0136] Based on the location information of the second reference hot spot grid in the sorting area and the location information of each remaining grid in the sorting area, the target remaining grid corresponding to the second reference hot spot grid is determined from the neighborhood of the second reference hot spot grid.

[0137] Establish a one-to-one correspondence between each surplus destination and each target surplus grid.

[0138] Specifically, "remaining grid cells" refers to grid cells other than the reference remaining grid cells, and grid cells without established correspondence. "Remaining destinations" refers to destinations other than those with established correspondences with the remaining reference grid cells, and can include both hotspot and non-hotspot destinations. The "fifth threshold" is a pre-set threshold that limits the relationship between the number of remaining grid cells and the number of remaining destinations; for example, the fifth threshold could be 1.5, and it can be set through system parameters. The "second reference hotspot grid cell" refers to a hotspot grid cell within its adjacent range that contains remaining grid cells.

[0139] The method to calculate the first quantity of remaining grid slots and the second quantity of remaining destinations can be to list the remaining grid slots to obtain the first quantity of remaining grid slots, and list the remaining destinations to obtain the second quantity of remaining destinations.

[0140] If the difference between the first quantity and the second quantity reaches the fifth threshold, before determining the second reference hotspot grid corresponding to each remaining destination according to the destination weight of each remaining destination from small to large and the hotspot grid from large to small, it also includes judging whether the difference between the first quantity and the second quantity reaches the fifth threshold.

[0141] If the difference between the first and second quantities does not reach the fifth threshold, the correspondence between the grid and the destination is established.

[0142] There are many ways to determine the second reference hotspot grid corresponding to each surplus destination, based on the order of destination weight from smallest to largest and hotspot grid from largest to smallest. The specific method depends on the actual situation and is not limited in this invention.

[0143] In one possible implementation of the present invention, the remaining destinations are sorted in ascending order based on their destination weights to obtain a third reverse sorting result; the hotspot grids are sorted in descending order based on their grid weights to obtain a third forward sorting result; and the second reference hotspot grids corresponding to each remaining destination are determined based on the third reverse sorting result and the third forward sorting result.

[0144] In another possible implementation of the present invention, the following steps can be taken: Based on the destination weights of each remaining destination, the destination with the smallest destination weight can be selected as the first remaining destination; based on the grid weights of each hotspot grid, the hotspot grid with the largest grid weight can be selected as the first hotspot grid, and the first hotspot grid can be determined as the second reference hotspot grid of the first remaining destination; based on the destination weights of each remaining destination, the remaining destination with the second smallest destination weight can be selected as the second remaining destination; based on the grid weights of each hotspot grid, the hotspot grid with the second largest grid weight can be selected as the second hotspot grid, and the second hotspot grid can be determined as the second reference hotspot grid of the second remaining destination, and so on, to determine the second reference hotspot grid corresponding to each remaining destination.

[0145] Based on the location information of the second reference hot spot grid in the sorting area and the location information of each remaining grid in the sorting area, the method of determining the target remaining grid corresponding to the second reference hot spot grid from the neighborhood of the second reference hot spot grid can be as follows: Based on the location information of the second reference hot spot grid in the sorting area and the location information of each remaining grid in the sorting area, determine the remaining grids in the adjacent range of the second reference hot spot grid, and select the target remaining grid corresponding to the second reference hot spot grid from each non-hot spot grid.

[0146] Applying the solution of this invention, when there are uncorrelated surplus slots and surplus destinations, the first number of surplus slots and the second number of surplus destinations are counted. When the difference between the first number and the second number reaches a fifth threshold, the second reference hotspot slots corresponding to each surplus destination are determined according to the destination weight of each surplus destination from smallest to largest and the hotspot slots from largest to smallest. Based on the second reference hotspot slots, the target surplus slots corresponding to the second reference hotspot slots are determined. A one-to-one correspondence is established between each surplus destination and each target surplus slot, so that the surplus destinations establish a correspondence with the target surplus slots, thereby improving the efficiency of subsequent order sorting based on the correspondence.

[0147] Optionally, after establishing a one-to-one correspondence between each surplus destination and each target surplus grid in the above steps, the following steps are also included:

[0148] In the case of specific grids where no corresponding relationship exists, the degree of difference between each hot destination is determined based on the order volume of each hot destination;

[0149] If the difference is less than the sixth threshold, select the target hot destination from each hot destination in descending order of destination weight, and select the target specific cell from each specific cell in descending order of cell weight.

[0150] Establish a correspondence between target hot destinations and target specific grids, and add a seventh threshold based on the target range, where the target range represents the average proportion of orders from hot destinations;

[0151] Return to the execution process and select the target hot spot destination from each hot spot destination in descending order of destination weight, and select the target specific grid from each specific grid in descending order of grid weight, until the number of remaining specific grids is greater than the eighth threshold or the seventh threshold is reached to achieve the maximum order proportion of hot spot destinations. The eighth threshold is determined based on the total number of hot spot destinations.

[0152] Specifically, the difference refers to the difference between the number of orders for popular destinations and non-popular destinations. For example, the difference could be that the number of orders for one popular destination exceeds 40% of the total number of orders, and / or, the number of orders for two popular destinations exceeds 50% of the total number of orders, and / or, the number of orders for three popular destinations exceeds 55% of the total number of orders, etc. The sixth threshold is a threshold that limits the difference of popular destinations. For example, if the difference of a popular destination is the proportion of its orders in the total number of orders, and the sixth threshold is 40%, then the difference of that popular destination is determined to be greater than the sixth threshold. Specific cells refer to the remaining cells that have not yet established a corresponding relationship, specifically the remaining cells excluding the reference remaining cells and the surplus cells. The seventh threshold is a pre-set threshold used to limit the number of times a corresponding relationship is established. The initial value of the seventh threshold is 0, and it increases according to a preset range. The target range is determined based on the number of popular destinations and the proportion of each popular destination in the total number of orders. For example, the target range is equal to [max(p_i)-min(p_i)] / number of popular destinations. The eighth threshold is determined based on the number of hotspot destinations, for example, it could be half the number of hotspot destinations.

[0153] The method to determine the degree of difference between popular destinations based on the number of orders for each popular destination can be to determine the proportion of the number of orders for each popular destination in the total number of orders, and then determine the degree of difference between popular destinations based on the proportion.

[0154] The implementation method is to select the target hotspot destination from each hotspot destination in descending order of destination weight, and select the target specific cell from each specific cell in descending order of cell weight. This can be achieved by selecting the top-ranked hotspot destination from each hotspot destination in descending order of destination weight, and selecting the top-ranked specific cell from each specific cell in descending order of cell weight.

[0155] The method to establish the correspondence between target hotspot destinations and target specific grids, and to increase the seventh threshold based on the target magnitude, can be to establish the correspondence between target hotspot destinations and target specific grids, and increase the initial value of the seventh threshold by the target magnitude to obtain an updated seventh threshold.

[0156] After obtaining the updated seventh threshold, return to the execution steps of selecting the target hotspot destination from each hotspot destination in descending order of destination weight, and selecting the target specific cell from each specific cell in descending order of cell weight.

[0157] The remaining number of specific slots is greater than the eighth threshold or the seventh threshold, reaching the maximum order proportion of hotspot destinations. This can be either the number of specific slots other than the target specific slot in the specific slots reaching the eighth threshold, or the seventh threshold being greater than or equal to the maximum proportion of hotspot destinations in the total orders.

[0158] By applying the solution of this invention, when there are specific grids that have not yet established a correspondence, the difference between each hot spot destination is determined. When the difference is less than a sixth threshold, a target specific grid and a target hot spot destination are selected, and a correspondence between the target specific grid and the target hot spot destination is established. A seventh threshold is then added based on the target magnitude, and the above steps of selecting the target specific grid and the target hot spot destination are repeated until the stopping condition is met. By selecting the target specific grid and the target hot spot destination from the specific grids that have not yet established a correspondence and establishing a correspondence, the correspondence can be used for order sorting in the future, thereby improving the efficiency of order sorting.

[0159] Optionally, after determining the degree of difference between popular destinations based on the order volume of each popular destination in the above steps, the following steps are also included:

[0160] If the difference is greater than or equal to the sixth threshold, identify multiple reserved grids that meet the eighth threshold;

[0161] Calculate the remaining number of specific compartments based on the total number of compartments in the sorting area, the number of compartments with established relationships, and the number of multiple reserved compartments;

[0162] The number of pre-allocated slots for each popular destination is determined based on the order percentage of each popular destination and the number of remaining specific slots.

[0163] Select the target hot destination from all hot destinations according to the destination weight in descending order, and select the target specific cell from all specific cells according to the cell weight in descending order.

[0164] Establish a correspondence between target hotspot destinations and specific target grids;

[0165] If the number of pre-allocated grid cells is not reached for each hotspot destination, return to the previous step of selecting the target hotspot destination from each hotspot destination in descending order of destination weight, and selecting the target specific grid cell from each specific grid cell in descending order of grid cell weight.

[0166] The implementation method for determining multiple reserved grids that meet the eighth threshold can be to select multiple specific grids that meet the eighth threshold from specific grids as reserved grids.

[0167] The method to calculate the remaining specific number of compartments based on the total number of compartments in the sorting area, the number of compartments with established relationships, and the number of multiple reserved compartments can be to subtract the number of compartments with established relationships from the total number of compartments in the sorting area, and then subtract the number of multiple reserved compartments to obtain the remaining specific number of compartments.

[0168] The method for determining the number of pre-allocated slots for each hot destination based on the order percentage of each hot destination and the remaining number of specific slots can be as follows: for any hot destination, the number of pre-allocated slots can be determined based on the order percentage of that hot destination and the remaining number of specific slots.

[0169] The method for determining the number of pre-allocated slots for any hot destination based on the order percentage of any hot destination and the remaining number of specific slots can be to multiply the order percentage of any hot destination by the remaining number of specific slots and round down to obtain the number of pre-allocated slots for any hot destination.

[0170] The process involves selecting target hotspot destinations from each hotspot destination in descending order of destination weight, and then selecting target specific grids from each specific grid in descending order of grid weight. The correspondence between target hotspot destinations and target specific grids can be established by pairing the target destination with the highest destination weight with the target specific grid with the lowest grid weight, the target destination with the second highest destination weight with the target specific grid with the second lowest grid weight, and so on, iterating through each hotspot destination. After the iteration is complete, the iteration restarts until the number of target specific grids corresponding to each hotspot destination reaches the pre-allocated number of grids.

[0171] By applying the solution of this invention, when the difference is greater than or equal to the sixth threshold, multiple reserved slots that meet the eighth threshold are determined so that the number of specific slots that establish a correspondence with each hot destination reaches the number of reserved slots, thereby maximizing the establishment of a correspondence between destinations and slots. In the subsequent order sorting, sorting can be performed directly based on the correspondence, thus improving the efficiency of subsequent order sorting.

[0172] Step 208: Based on the correspondence, send sorting instructions to the sorting robot to drive the sorting robot to sort each target order to the corresponding slot based on the destination information of each target order.

[0173] Specifically, sorting instructions refer to the instructions that drive the sorting robot to sort orders. Sorting instructions can usually be in the form of natural language or in the form of code.

[0174] The implementation method of sending sorting instructions to the sorting robot based on the correspondence to drive the sorting robot to sort each target order to the corresponding slot based on the destination information of each target order can be as follows: One method is to generate sorting instructions containing the correspondence based on the correspondence, send the sorting instructions to the sorting robot, and the sorting robot sorts each target order to the corresponding slot based on the destination information of each target order and the correspondence in the sorting instructions; another method is to identify the slot corresponding to any target order, send sorting instructions to the sorting robot, and drive the sorting robot to sort the target order to the corresponding slot.

[0175] The present invention provides a solution for obtaining multiple target orders, destination information for each target order, and the weight of each grid within the sorting area. The grid weight is inversely proportional to the reference distance, which is the distance between the grid and the sorting station. Based on the destination information of each target order, the number of orders for each destination is counted to obtain the destination weight of each destination, which is directly proportional to the number of orders. According to the grid weight and the destination weight, the correspondence between each grid and each destination is determined. Based on the correspondence, a sorting instruction is sent to the sorting robot to drive the sorting robot to sort each target order to the corresponding grid based on the destination information of each target order. By acquiring multiple target orders and their destination information, the destination weight of each destination is determined. Based on the destination weights and their magnitudes, the correspondence between each sorting grid and its destination is obtained, ensuring that grids with high weights correspond to destinations with high destination weights. The grid weight is inversely proportional to the reference distance, meaning that grids that are closer correspond to a larger number of destinations. This reduces the distance the robot travels during order sorting and further reduces path congestion and conflicts during robot movement.

[0176] The following is in conjunction with the appendix Figure 3A Taking the application of the order sorting method provided by this invention to sort logistics parcels as an example, the order sorting method will be further explained. Among other things, Figure 3A This diagram illustrates a processing flowchart of an order sorting method according to an embodiment of the present invention, which specifically includes the following steps:

[0177] Step 302: Obtain multiple target orders and the destination information for each target order.

[0178] Get 200 logistics packages and their destination information.

[0179] Step 304: Obtain the location information of each compartment and multiple sorting stations within the sorting area.

[0180] Obtain the location coordinates of 194 sorting grids and 20 sorting stations within the logistics sorting area.

[0181] See details Figure 3B , Figure 3B A schematic diagram of a logistics sorting area provided by an embodiment of the present invention is shown:

[0182] The diagram includes sorting station areas on the left and right sides, as well as a sorting grid area in the middle. Each of the sorting station areas on the left and right sides includes 10 sorting stations, while the sorting grid area in the middle includes 194 sorting grids.

[0183] Step 306: For any given grid, based on the location information of the grid and multiple sorting stations, determine the distance between the grid and each sorting station, and based on each distance, determine the reference distance of the grid.

[0184] For sorting grid 1, calculate the distances between sorting grid 1 and the 20 sorting stations, sum them up, and then average them to obtain the reference distance for sorting grid 1.

[0185] Using a similar calculation method as described above, the reference distance for each sorting compartment is obtained.

[0186] Step 308: Determine the grid weight of each grid based on the reference distance of each grid, wherein the grid weight of each grid is inversely proportional to the reference distance of each grid.

[0187] The reciprocal of the reference distance for each sorting grid is used to obtain the grid weight of each sorting grid.

[0188] Step 310: Based on the destination information of each target order, count the number of orders for each destination.

[0189] Identify the destination information of each logistics package, summarize the destination information of each logistics package according to the destination information, and obtain the number of orders for each destination. For example, there are 200 logistics packages with a total of 50 different destinations. The number of orders corresponding to destination 1 is 30, the number of orders corresponding to destination 2 is 5, and so on. The number of orders corresponding to destination 50 is 15.

[0190] Step 312: For any destination, determine the order percentage of any destination among multiple target orders based on the order quantity for that destination.

[0191] For destination 1, divide the number of orders for destination 1 (30) by the total number of orders (200) to get the percentage of orders for destination 1 in the multiple logistics packages as 30 / 200.

[0192] Step 314: Determine the destination weight of each destination based on the order proportion of each destination. The destination weight of each destination is directly proportional to the order proportion of each destination.

[0193] The order percentage of each destination in multiple logistics packages is used as the destination weight for each destination.

[0194] Step 316: Based on the destination weight of each destination, determine at least one hot destination and determine the destinations other than the hot destinations as non-hot destinations, wherein the destination weight of the hot destination is greater than the first threshold.

[0195] The destination weight of each destination is compared with a first threshold. Destinations with a destination weight greater than the first threshold are identified as hot destinations, and destinations other than hot destinations are identified as non-hot destinations.

[0196] Step 318: Based on the grid weight of each grid, determine at least one hot grid, and based on the location information of each hot grid in the sorting area, determine non-hot grids, wherein the grid weight of the hot grid is greater than the second threshold.

[0197] The sorting grid weights are compared with a second threshold. Sorting grids with weights greater than the second threshold are selected as hotspot grid 1. Based on hotspot grid 1 and its location information, the weights of sorting grids outside the adjacent range of hotspot grid 1 are compared with the second threshold to confirm whether they are greater than the second threshold. If they are, they are selected as hotspot grid 2. This process is repeated for multiple sorting grids within the sorting area. Sorting grids other than hotspot grids are selected as non-hotspot grids.

[0198] Step 320: Establish the correspondence between hotspot grids and hotspot destinations based on the grid weight of each hotspot grid and the destination weight of each hotspot destination.

[0199] Based on the grid weight of each hotspot grid and the destination weight of each hotspot destination in descending order, a one-to-one correspondence between each hotspot grid and each hotspot destination is established sequentially.

[0200] Step 322: Based on the destination weight of each non-hotspot destination and the location information of each hotspot grid and each non-hotspot grid in the sorting area, establish the correspondence between non-hotspot grids and non-hotspot destinations.

[0201] Step 324: Based on the correspondence, send sorting instructions to the sorting robot to drive the sorting robot to sort each target order to the corresponding slot based on the destination information of each target order.

[0202] This invention, applied to a sorting system, includes: acquiring multiple target orders, destination information for each target order, and the weight of each grid within the sorting area, wherein the grid weight is inversely proportional to a reference distance, the reference distance being the distance between the grid and the sorting station; based on the destination information of each target order, counting the number of orders for each destination to obtain the destination weight of each destination, wherein the destination weight is directly proportional to the number of orders; determining the correspondence between each grid and each destination according to the grid weight and the destination weight; and sending sorting instructions to a sorting robot according to the correspondence to drive the sorting robot to sort each target order to its corresponding grid based on the destination information of each target order. By acquiring multiple target orders and their destination information, the destination weight of each destination is determined. Based on the destination weights and their magnitudes, the correspondence between each sorting grid and its destination is obtained, ensuring that grids with high weights correspond to destinations with high destination weights. The grid weight is inversely proportional to the reference distance, meaning that grids that are closer correspond to a larger number of destinations. This reduces the distance the robot travels during order sorting and further reduces path congestion and conflicts during robot movement.

[0203] Corresponding to the above method embodiments, the present invention also provides an embodiment of an order sorting device. Figure 4 A schematic diagram of an order sorting device according to an embodiment of the present invention is shown. Figure 4 As shown, the device includes:

[0204] The acquisition module 402 is configured to acquire multiple target orders, destination information of each target order, and grid weight of each grid in the sorting area. The grid weight is inversely proportional to the reference distance, which is the distance between the grid and the sorting station.

[0205] The statistics module 404 is configured to count the number of orders for each destination based on the destination information of each target order, and obtain the destination weight of each destination, wherein the destination weight is directly proportional to the number of orders;

[0206] The relationship determination module 406 is configured to determine the correspondence between each grid and each destination according to the weight of each grid and the weight of each destination.

[0207] The sending module 408 is configured to send sorting instructions to the sorting robot according to the correspondence, so as to drive the sorting robot to sort each target order to the corresponding grid based on the destination information of each target order.

[0208] Optionally, the acquisition module 402 is further configured to acquire the location information of each grid and multiple sorting stations within the sorting area; for any grid, based on the location information of any grid and multiple sorting stations, determine the distance between any grid and each sorting station, and based on each distance, determine the reference distance of any grid; based on the reference distance of each grid, determine the grid weight of each grid, wherein the grid weight of each grid is inversely proportional to the reference distance of each grid.

[0209] Optionally, the statistics module 404 is further configured to: count the number of orders for each destination based on the destination information of each target order; determine the order percentage of any destination among multiple target orders based on the order percentage of any destination; and determine the destination weight of each destination based on the order percentage of each destination, wherein the destination weight of each destination is proportional to the order percentage of each destination.

[0210] Optionally, the relationship determination module 406 is further configured to: determine at least one hot destination based on the destination weight of each destination, and determine destinations other than hot destinations as non-hot destinations, wherein the destination weight of the hot destination is greater than a first threshold; determine at least one hot grid based on the grid weight of each grid, and determine non-hot grids based on the location information of each hot grid in the sorting area, wherein the grid weight of the hot grid is greater than a second threshold; establish a correspondence between hot grids and hot destinations based on the grid weight of each hot grid and the destination weight of each hot destination; and establish a correspondence between non-hot grids and non-hot destinations based on the destination weight of each non-hot destination, the location information of each hot grid and each non-hot grid in the sorting area.

[0211] Optionally, the relationship determination module 406 is further configured to establish a one-to-one correspondence between each hot spot grid and each hot spot destination in descending order of grid weight and destination weight.

[0212] Optionally, the order sorting device also includes a grid determination module, configured to obtain the number of hot grids and the number of hot destinations; if the number of grids is less than the number of destinations, calculate the difference between the number of grids and the number of destinations; select multiple target non-hot grids that meet the difference from the non-hot grids, and determine the multiple target non-hot grids as hot grids.

[0213] Optionally, the grid determination module is further configured to select multiple target hotspot grids that meet the difference value from each hotspot grid in ascending order of grid weight; select non-hotspot grids whose grid weight reaches the third threshold from the neighborhood of each target hotspot grid; and update each selected non-hotspot grid as a hotspot grid.

[0214] Optionally, the relationship determination module 406 is further configured to determine the first reference hot spot cell corresponding to each non-hot spot destination according to the destination weight of each non-hot spot destination in ascending order and the hot spot cells in descending order; determine the target non-hot spot cell corresponding to the first reference hot spot cell from the neighborhood of the first reference hot spot cell based on the location information of the first reference hot spot cell in the sorting area and the location information of each non-hot spot cell in the sorting area; and establish a one-to-one correspondence between each non-hot spot destination and each target non-hot spot cell.

[0215] Optionally, the order sorting device also includes a first relationship establishment module, which is configured to select reference remaining grids with grid weights greater than a fourth threshold from the remaining grids when there are remaining grids without established corresponding relationships; and establish a one-to-one correspondence between each reference remaining grid and each destination in order of grid weights from small to large and destination weights from large to small.

[0216] Optionally, the order sorting device further includes a second relationship establishment module, configured to: when there are unestablished corresponding surplus slots and surplus destinations, count the first number of surplus slots and the second number of surplus destinations; when the difference between the first number and the second number reaches a fifth threshold, determine the second reference hot spot slots corresponding to each surplus destination in ascending order of destination weight and descending order of hot spot slots; based on the location information of the second reference hot spot slots in the sorting area and the location information of each surplus slot in the sorting area, determine the target surplus slots corresponding to the second reference hot spot slots from the neighborhood of the second reference hot spot slots; and establish a one-to-one correspondence between each surplus destination and each target surplus slot.

[0217] Optionally, the order sorting device further includes a third relationship establishment module, configured to, in the case of specific slots where no corresponding relationship has been established, determine the degree of difference between each hot spot destination based on the number of orders for each hot spot destination; if the degree of difference is less than a sixth threshold, select a target hot spot destination from each hot spot destination in descending order of destination weight, and select a target specific slot from each specific slot in descending order of slot weight; establish a correspondence between the target hot spot destination and the target specific slot, and increase a seventh threshold based on a target magnitude, where the target magnitude represents the average order proportion of hot spot destinations; return to execute the steps of selecting a target hot spot destination from each hot spot destination in descending order of destination weight, and selecting a target specific slot from each specific slot in descending order of slot weight, until the number of remaining specific slots is greater than an eighth threshold or the seventh threshold reaches the maximum order proportion of hot spot destinations, where the eighth threshold is determined based on the total number of hot spot destinations.

[0218] Optionally, the order sorting device also includes a fourth relationship establishment module, configured to: determine multiple reserved slots that meet an eighth threshold when the difference is greater than or equal to a sixth threshold; calculate the remaining number of specific slots based on the total number of slots in the sorting area, the number of slots with established correspondences, and the number of multiple reserved slots; determine the pre-allocated number of slots for each hotspot destination based on the order proportion of each hotspot destination and the remaining number of specific slots; select target hotspot destinations from each hotspot destination in descending order of destination weight, and select target specific slots from each specific slot in descending order of slot weight; establish a correspondence between target hotspot destinations and target specific slots; if each hotspot destination has not reached the corresponding pre-allocated number of slots, return to the steps of selecting target hotspot destinations from each hotspot destination in descending order of destination weight, and selecting target specific slots from each specific slot in descending order of slot weight.

[0219] This invention, applied to a sorting system, includes: acquiring multiple target orders, destination information for each target order, and the weight of each grid within the sorting area, wherein the grid weight is inversely proportional to a reference distance, the reference distance being the distance between the grid and the sorting station; based on the destination information of each target order, counting the number of orders for each destination to obtain the destination weight of each destination, wherein the destination weight is directly proportional to the number of orders; determining the correspondence between each grid and each destination according to the grid weight and the destination weight; and sending sorting instructions to a sorting robot according to the correspondence to drive the sorting robot to sort each target order to its corresponding grid based on the destination information of each target order. By acquiring multiple target orders and their destination information, the destination weight of each destination is determined. Based on the destination weights and their magnitudes, the correspondence between each sorting grid and its destination is obtained, ensuring that grids with high weights correspond to destinations with high destination weights. The grid weight is inversely proportional to the reference distance, meaning that grids that are closer correspond to a larger number of destinations. This reduces the distance the robot travels during order sorting and further reduces path congestion and conflicts during robot movement.

[0220] The above is a schematic scheme of an order sorting device according to this embodiment. It should be noted that the technical solution of this order sorting device and the technical solution of the order sorting method described above belong to the same concept. Details not described in detail in the technical solution of the order sorting device can be found in the description of the technical solution of the order sorting method described above. Furthermore, the components in the device embodiment should be understood as functional modules necessary to implement each step of the program flow or each step of the method; these functional modules are not actual functional divisions or separations. The device claims defined by such a set of functional modules should be understood as a functional module architecture that primarily implements the solution through the computer program described in the specification, and not as a physical device that primarily implements the solution through hardware.

[0221] Figure 5 A structural block diagram of a computing device 500 according to an embodiment of the present invention is shown. The components of the computing device 500 include, but are not limited to, a memory 510 and a processor 520. The processor 520 is connected to the memory 510 via a bus 530, and a database 550 is used to store data.

[0222] The computing device 500 also includes an access device 540, which enables the computing device 500 to communicate via one or more networks 560. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 540 may include any type of wired or wireless network interface, such as one or more Network Interface Controllers (NICs), such as an IEEE 802.11 Wireless Local Area Networks (WLAN) wireless interface, a Wi-MAX (World Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, a Near Field Communication (NFC) interface, and so on.

[0223] In one embodiment of the present invention, the above-mentioned components of the computing device 500 and Figure 5 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 5 The illustrated block diagram of the computing device is for illustrative purposes only and is not intended to limit the scope of the invention. Those skilled in the art can add or replace other components as needed.

[0224] Computing device 500 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). Computing device 500 can also be a mobile or stationary server.

[0225] The processor 520 is used to execute computer-executable instructions for the order sorting method.

[0226] The above is a schematic diagram of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the order sorting method described above belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the order sorting method described above.

[0227] An embodiment of the present invention also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, are used for an order sorting method.

[0228] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the order sorting method described above belong to the same concept. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the order sorting method described above.

[0229] The foregoing has described specific embodiments of the invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0230] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0231] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0232] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0233] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of the present invention. These embodiments have been selected and specifically described to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An order picking method characterized by, Applications in sorting systems include: The system obtains multiple target orders, destination information for each target order, and grid weights for each grid within the sorting area. The grid weights are inversely proportional to a reference distance, which is the distance between the grid and the sorting station. The grid weights are used to reflect the popularity of the grid within the sorting area. Based on the destination information of each target order, the number of orders for each destination is counted to obtain the destination weight of each destination. The destination weight is directly proportional to the number of orders and is used to reflect the popularity of the destination among the multiple target orders. The correspondence between each sorting grid and each destination is determined according to the weight of each grid and the weight of each destination. The grids in the sorting area are divided into hot grids and non-hot grids based on their respective weights, and the destinations are divided into hot destinations and non-hot destinations based on their respective weights. The determination of the correspondence between each grid and each destination according to their respective weights includes: determining the target non-hot grids corresponding to each non-hot destination from the neighborhood of the first reference hot grid corresponding to each non-hot destination, and establishing a one-to-one correspondence between each non-hot destination and each target non-hot grid. The first reference hot grid corresponding to each non-hot destination refers to a hot grid allocated to each non-hot destination for selecting the corresponding non-hot grid in its neighborhood. Based on the correspondence, a sorting instruction is sent to the sorting robot to drive the sorting robot to sort each target order into the corresponding compartment based on the destination information of each target order.

2. The method according to claim 1, characterized in that, The process of obtaining the grid weights of each grid within the sorting area includes: Obtain the location information of each compartment and multiple sorting stations within the sorting area; For any given grid, based on the location information of the given grid and the plurality of sorting stations, the distance between the given grid and each sorting station is determined, and based on each distance, a reference distance for the given grid is determined. Based on the reference distance of each grid cell, the grid cell weight of each grid cell is determined, wherein the grid cell weight of each grid cell is inversely proportional to the reference distance of each grid cell.

3. The method according to claim 1, characterized in that, The step of calculating the number of orders for each destination based on the destination information of each target order, and obtaining the destination weight of each destination, includes: Based on the destination information of each target order, the number of orders for each destination is counted; For any given destination, determine the percentage of orders for that destination among multiple target orders based on the number of orders for that destination. Based on the order proportion of each destination, the destination weight of each destination is determined, wherein the destination weight of each destination is directly proportional to the order proportion of each destination.

4. The method according to any one of claims 1-3, characterized in that, The step of determining the correspondence between each grid point and each destination according to the weight of each grid point and the weight of each destination includes: Based on the destination weight of each destination, at least one hot destination is identified, and destinations other than the hot destination are identified as non-hot destinations, wherein the destination weight of the hot destination is greater than a first threshold. Based on the grid weight of each grid, at least one hot grid is identified, and based on the location information of each hot grid in the sorting area, non-hot grids are identified, wherein the grid weight of the hot grid is greater than a second threshold. Based on the grid weight of each hot spot grid and the destination weight of each hot spot destination, establish the correspondence between hot spot grids and hot spot destinations; Based on the destination weight of each non-hotspot destination and the location information of each hotspot and non-hotspot grid in the sorting area, a correspondence between non-hotspot grids and non-hotspot destinations is established.

5. The method according to claim 4, characterized in that, The process of establishing a correspondence between hotspot grids and hotspot destinations based on the grid weight of each hotspot grid and the destination weight of each hotspot destination includes: Based on the grid weight of each hotspot grid and the destination weight of each hotspot destination in descending order, a one-to-one correspondence between each hotspot grid and each hotspot destination is established sequentially.

6. The method according to any one of claims 4-5, characterized in that, Before establishing the correspondence between hotspot grids and hotspot destinations based on the grid weights of each hotspot grid and the destination weights of each hotspot destination, the following steps are also included: Obtain the number of hotspot grids and the number of hotspot destinations; If the number of grids is less than the number of destinations, calculate the difference between the number of grids and the number of destinations; Select multiple target non-hotspot grids that meet the difference from the non-hotspot grids, and determine the multiple target non-hotspot grids as hotspot grids.

7. The method according to claim 6, characterized in that, The step of selecting multiple target non-hotspot grids that meet the difference from the non-hotspot grids includes: According to the grid weight of each hot spot grid in ascending order, select multiple target hot spot grids that meet the difference value from each hot spot grid; From the neighborhood of each target hotspot grid, select non-hotspot grids whose grid weight reaches the third threshold; Update the selected non-hotspot grids to hotspot grids.

8. The method according to claim 4, characterized in that, The step of establishing a correspondence between non-hotspot slots and non-hotspot destinations based on the destination weights of each non-hotspot destination and the location information of each hotspot slot and each non-hotspot slot in the sorting area includes: The first reference hotspot grid corresponding to each non-hotspot destination is determined according to the destination weight of each non-hotspot destination from smallest to largest and the hotspot grid from largest to smallest. Based on the location information of the first reference hot spot in the sorting area and the location information of each non-hot spot in the sorting area, the target non-hot spot corresponding to the first reference hot spot is determined from the neighborhood of the first reference hot spot. Establish a one-to-one correspondence between each non-hotspot destination and each target non-hotspot grid.

9. The method according to claim 4, characterized in that, After establishing the correspondence between non-hotspot grids and non-hotspot destinations, the following is also included: In the case of remaining cells without established correspondence, select reference remaining cells whose cell weight is greater than the fourth threshold from the remaining cells; A one-to-one correspondence is established between each reference remaining grid and each destination, based on the grid weights of each reference remaining grid from smallest to largest and the destination weights of each destination from largest to smallest.

10. The method according to claim 9, characterized in that, After establishing a one-to-one correspondence between each reference remaining grid and each destination according to the grid weights of each reference remaining grid in ascending order and the destination weights of each destination in descending order, the method further includes: In the case of unconnected spare grids and spare destinations, count the first number of spare grids and the second number of spare destinations. When the difference between the first quantity and the second quantity reaches the fifth threshold, the second reference hotspot grid corresponding to each remaining destination is determined in order of destination weight from small to large and hotspot grid from large to small. Based on the location information of the second reference hot spot grid in the sorting area and the location information of each remaining grid in the sorting area, the target remaining grid corresponding to the second reference hot spot grid is determined from the neighborhood of the second reference hot spot grid. Establish a one-to-one correspondence between each remaining quantity destination and each target remaining quantity grid.

11. The method according to claim 10, characterized in that, After establishing the one-to-one correspondence between each surplus destination and each target surplus grid, the method further includes: In the case of specific grids where no corresponding relationship exists, the degree of difference between the various hot destinations is determined based on the number of orders for each hot destination; If the difference is less than the sixth threshold, select the target hotspot destination from each hotspot destination in descending order of destination weight, and select the target specific cell from each specific cell in descending order of cell weight. Establish the correspondence between the target hot destinations and the target specific grids, and add a seventh threshold based on the target amplitude, wherein the target amplitude represents the average order proportion of hot destinations; Return to the steps of selecting target hotspot destinations from each hotspot destination in descending order of destination weight, and selecting target specific grids from each specific grid in descending order of grid weight, until the number of remaining specific grids is greater than the eighth threshold or the seventh threshold reaches the maximum order proportion of hotspot destinations, wherein the eighth threshold is determined based on the total number of hotspot destinations.

12. The method according to claim 11, characterized in that, After determining the degree of difference between the various popular destinations based on the order volume of each popular destination, the method further includes: If the difference is greater than or equal to the sixth threshold, a number of reserved grids that meet the eighth threshold are determined; The remaining number of specific compartments is calculated based on the total number of compartments in the sorting area, the number of compartments with established correspondences, and the number of the multiple reserved compartments. The number of pre-allocated slots for each hot destination is determined based on the order percentage of each hot destination and the remaining number of specific slots. Select the target hot destination from all hot destinations according to the destination weight in descending order, and select the target specific cell from all specific cells according to the cell weight in descending order. Establish the correspondence between the target hotspot destinations and the target specific grids; If the number of pre-allocated grid slots for each hotspot destination has not been reached, return to the steps of selecting the target hotspot destination from each hotspot destination in descending order of destination weight, and selecting the target specific grid slot from each specific grid slot in descending order of grid slot weight.

13. An order sorting device, characterized in that, Applications in sorting systems include: The acquisition module is configured to acquire multiple target orders, destination information of each target order, and grid weight of each grid in the sorting area. The grid weight is inversely proportional to the reference distance, which is the distance between the grid and the sorting station. The grid weight is used to reflect the popularity of the grid in the sorting area. The statistics module is configured to count the number of orders for each destination based on the destination information of each target order, and obtain the destination weight of each destination, wherein the destination weight is directly proportional to the number of orders, and the destination weight is used to reflect the popularity of the destination among the multiple target orders; The relationship determination module is configured to determine the correspondence between each grid and each destination according to the weight of each grid and the weight of each destination. The grids within the sorting area are divided into hotspot grids and non-hotspot grids based on their respective weights, and the destinations are divided into hotspot destinations and non-hotspot destinations based on their respective weights. Determining the correspondence between each grid and each destination according to their respective weights includes: determining the target non-hotspot grid corresponding to each non-hotspot destination from the neighborhood of the first reference hotspot grid corresponding to each non-hotspot destination; and establishing a one-to-one correspondence between each non-hotspot destination and each target non-hotspot grid. The first reference hotspot grid corresponding to each non-hotspot destination refers to a hotspot grid allocated to each non-hotspot destination for selecting the corresponding non-hotspot grid within its neighborhood. The sending module is configured to send sorting instructions to the sorting robot according to the correspondence, so as to drive the sorting robot to sort each target order to the corresponding grid based on the destination information of each target order.

14. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the steps of the order sorting method according to any one of claims 1 to 12.

15. A computer-readable storage medium storing computer instructions, characterized in that, When executed by the processor, this instruction implements the steps of the order sorting method according to any one of claims 1 to 12.

16. A computer program product comprising computer instructions, characterized in that, When executed by a processor, the computer instructions implement the steps of the order sorting method according to any one of claims 1 to 12.

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