Intelligent picking method and system

Abstract

The application discloses an intelligent picking method and belongs to the field of warehouse logistics. The method is based on an electric flat car carrying multiple batches of picking boxes, and establishes the association between the shelf identification and the double-sided storage location. The task is mounted according to the double-sided pre-classification, the all picking tasks are called by scanning the shelf identification, and the display order is adaptively adjusted according to the vehicle travel direction, so that the picking storage locations are sorted from near to far and highlighted preferentially, and the picking along the way is realized without turning back. After scanning the product identification, the corresponding batch picking box is put in according to the prompt, and finally the picking box is directly sent to the automatic seeding wall for distribution. Through the one-key loading of the double-sided task, the adaptive sorting of the travel direction and the integrated cooperation of the picking and distribution, the invalid walking and the operation frequency are greatly reduced, and the picking efficiency and the overall throughput of the system are significantly improved.

Description

Technical Field

[0001] This invention relates to the field of logistics and warehousing technology, and in particular to an intelligent picking method and system. Background Technology

[0002] With the rapid development of e-commerce and logistics warehousing, the efficiency of order fulfillment center picking operations has become a key bottleneck restricting the overall supply chain timeliness. Traditional picking methods mainly rely on manual picking using paper lists or mobile terminals, walking between shelves to pick items.

[0003] In one existing technical solution, as disclosed in patent document CN116050687B, task allocation and path planning are optimized by considering the walking time of goods in the warehouse and the efficiency of workers searching. However, this solution still relies on pickers walking between shelves, and the number of order batches and goods that can be carried in a single picking session is extremely limited. Furthermore, this solution manages the picking tasks of a set of shelves separately by left and right sides, requiring workers to scan and load them separately. It cannot achieve synchronous retrieval and integration of tasks on both sides, leading to frequent switching between interfaces and increasing additional operation time. More importantly, the task display order is static and cannot be adaptively adjusted according to the actual direction of worker movement, causing workers to frequently have to backtrack within the aisles, and the walking path is not truly minimized.

[0004] Another existing technical solution, as disclosed in patent document CN116651760B, focuses on optimizing vehicle scheduling in the seeding process, providing a method for scheduling intelligent seeding wall circulating railcars. However, this solution only addresses the efficiency issue of back-end seeding and is completely disconnected from the front-end picking process. In actual operation, picking and seeding are two sequential and independent processes. After picking, the goods need to be centrally transferred to the seeding area, during which there is a significant intermediate waiting time. The difference in single-batch processing capacity also leads to a mismatch between the front-end and back-end cycles, preventing the front-end picking capacity from being fully utilized and thus limiting the overall system throughput.

[0005] In addition, the existing hardware carriers for picking operations are mostly hand-pushed or simple electric flatbed carts. Their design lacks consideration for multiple batches of parallel operations and generally suffers from problems such as small load capacity, unstable center of gravity, and poor safety. It is difficult to meet the dual requirements of high load capacity and flexible passage in the narrow aisles of the warehouse.

[0006] As the above analysis shows, existing technologies mainly suffer from drawbacks such as the separation of picking and sorting processes, unintelligent task loading and interface display, and poor hardware compatibility. Therefore, how to provide a picking solution that can achieve integrated picking and sorting, intelligently sense the direction of movement and adaptively adjust the task interaction interface, and has high load capacity and high security has become a pressing technical problem to be solved in this field. Summary of the Invention

[0007] The purpose of this invention is to provide an intelligent picking method and system, which aims to solve the problem of easy wear and tear in intelligent picking methods, improve the service life of intelligent picking methods, and ensure that the intelligent picking method does not damage the window structure during use, is easy to install, and improves performance.

[0008] To achieve the above objectives, the present invention provides an intelligent picking method based on an electric flatbed cart and a wearable barcode scanning device worn by the operator. The electric flatbed cart has a cargo platform on which multiple picking boxes can be detachably placed, each picking box corresponding to a picking batch. The intelligent picking method includes the following steps: Establish the association between shelf identification and storage location information on both sides of the shelf in the shelf area; wherein, the storage location information on both sides of the shelf includes storage location code and its corresponding product; Based on the orders to be picked, picking tasks involving the same shelf are categorized according to the storage locations on both sides of the shelf and attached to the corresponding shelf labels; In response to the wearable scanning device scanning the shelf identifier, all picking tasks on both sides of the shelf are retrieved, and the display order of picking tasks is adaptively adjusted according to the preset shelf position and the traveling direction information of the electric flatbed vehicle, so that the picking storage locations in the current traveling direction are sorted from near to far and highlighted first. Receives scans of product tags and prompts users to place the required quantity of products into the corresponding picking bin; Once all picking tasks for all batches are completed, the picking bins are instructed to be transported to the automated seeding wall for sorting.

[0009] In a preferred embodiment, the method further includes the step of: if it is determined that the wearable barcode scanner directly scans the product label instead of the shelf label, then the preset channel route is automatically matched according to the location information of the storage location to which the product belongs, the current travel direction of the electric flatbed cart is intelligently corrected, and the display order of the picking tasks is rearranged according to the corrected travel direction.

[0010] In a preferred embodiment, the step of adaptively adjusting the display order of tasks to be picked, so that the storage locations to be picked in the current direction of travel are sorted from near to far and highlighted preferentially, specifically includes: Based on the identified direction of travel, the display logic of the storage locations on the left and right sides of the shelf is changed on the display interface, so that the storage locations closer to the electric flatbed truck are displayed first. Reorder all items to be picked on both sides of the shelf according to their physical location on the current travel route, from near to far. Prioritize highlighting the product information corresponding to the first pending storage location in the current direction of travel.

[0011] In a preferred embodiment, the method further includes the step of: Obtain historical search efficiency data of the workers who drive the electric flatbed truck; For non-new employees, the arithmetic mean of their previous search efficiencies is used as the current efficiency parameter; for new employees, the arithmetic mean of the initial search efficiencies of all non-new employees is used as the baseline efficiency parameter. Based on the current or baseline efficiency parameters of each operator, the workload allocated to the batches they handle is dynamically adjusted to ensure that the workload of operators with different skill levels tends to be balanced within the same working time.

[0012] In a preferred embodiment, the wearable barcode scanner is a Bluetooth ring reader and includes a mobile terminal that can be fixed to the operator's arm and run a picking system application. The mobile terminal is used to display the picking task interface in real time.

[0013] In a preferred embodiment, after scanning the product label with the wearable scanning device, a high-resolution photo of the product is displayed on the mobile terminal.

[0014] In a preferred embodiment, when any of the picking boxes is full, an empty picking box can be added and the corresponding batch barcode can be attached. The barcode of the new box is scanned to complete the replacement binding, and the picking operation is not interrupted.

[0015] In a preferred embodiment, the automated sorting wall has multiple sorting slots arranged in rows and columns, and its single-batch sorting capacity matches the number of picking boxes that the electric flatbed truck can carry in a single transport and the average order capacity corresponding to each picking box.

[0016] In a preferred embodiment, the electric flatbed vehicle is a stand-on electric flatbed vehicle with a rearward-moving axle structure and enclosed guardrails.

[0017] The present invention also provides an intelligent picking system, comprising: An electric flatbed truck has a cargo platform on which multiple picking boxes can be detachably placed, each picking box corresponding to a picking batch; A wearable barcode scanner, worn by the operator, is used to scan shelf labels and product labels; An automatic sorting wall is used to automatically sort the goods in the picking box in batches; and at least one computing device configured to: Establish and store the association between shelf identification and storage location information on both sides of the shelf; Based on the orders to be picked, picking tasks involving the same shelf are categorized according to the storage locations on both sides of the shelf and attached to the corresponding shelf labels. In response to the wearable scanning device scanning the shelf identifier, all picking tasks on both sides of the shelf are retrieved, and the display order of picking tasks is adaptively adjusted according to the preset shelf position and the traveling direction information of the electric flatbed vehicle, so that the picking storage locations in the current traveling direction are sorted from near to far and highlighted first. Receives scans of product tags and prompts users to place the required quantity of products into the corresponding picking bin; And after all batch picking tasks are completed, instruct the picking box to be transported to the automated seeding wall for seeding.

[0018] The intelligent picking method and system provided by this invention establishes a unique association between shelf identifiers and all storage locations on both sides of the shelf in a pre-established backend system, and pre-categorizes and loads orders to be picked according to this association. When an operator drives a vehicle close to the shelf and scans the shelf identifier, the system can retrieve all picking tasks on both sides of the shelf with one click, completely eliminating the tedious process of scanning each side individually. Furthermore, this invention can also obtain preset shelf location information and the current travel direction information of the electric flatbed cart, and adaptively adjust the display order of the retrieved picking tasks accordingly. The adjustment logic is to ensure that the order of goods on the display interface is completely consistent with the physical order of the storage locations traversed by the vehicle along the aisle, arranged from near to far, and prioritizing the highlighting of the first item to be picked on the path. This mechanism ensures that operators only need to proceed straight along the path to complete the picking sequentially according to the interface guidance, without needing to judge the location or turn back midway. Once all batches of tasks carried by the vehicle are completed, the picking boxes are directly transported to the automated sorting wall for continuous sorting, realizing the "one-round, picking and sorting in one" operation mode. This allows the operator's behavior to naturally match the optimal path, thereby greatly shortening the effective picking path and overcoming the problems of blind operation and backtracking caused by static task lists. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A 3D schematic diagram of an electric flatbed truck; Figure 2 A schematic diagram of a barcode scanning device or mobile terminal that is fixed on the operator; Figure 3 A framework diagram of the intelligent picking system provided by the present invention; Figure 4This is a schematic diagram illustrating the status changes of the mobile terminal's display interface during the picking process.

[0021] The diagram is labeled as follows: 10. Electric flatbed cart; 20. Wearable barcode scanner; 30. Picking box; 40. Automatic sorting wall; 50. Mobile terminal; 60. Computing device; 61. Shelf storage location association module; 62. Task classification and mounting module; 63. Task display and adjustment module; 64. Task workload dynamic balancing module. Detailed Implementation

[0022] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described in this specification are merely for explaining the invention and are not intended to limit the invention.

[0023] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0024] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] In an embodiment of the present invention, an intelligent picking method is provided. This method can be implemented based on an S3D (Smart, Speedy, and Safe) intelligent picking system, which organically integrates the carrying capacity of multiple batches of parallel picking, one-click loading of tasks on both sides of the shelf, adaptive interface sorting based on the direction of travel, and automatic back-end seeding to build a seamless and efficient closed loop from "picking" to "sorting".

[0026] It should be noted that the hardware of the S3D intelligent picking system mainly includes a stand-on electric flatbed cart 10, a wearable barcode scanner 20, multiple large picking boxes 30, and an automatic sorting wall 40.

[0027] Specifically, the stand-on electric flatbed truck 10 serves as the core mobile carrier, and its structure can be referenced in the appendix. Figure 1In a preferred embodiment, the flatbed truck's loading platform is approximately 75 cm wide and 120 cm long, capable of stably holding four standard-sized large picking boxes 30 simultaneously. The vehicle's overall length with the running boards retracted is approximately 143 cm, with the rear protruding only about 20 cm; its compact design allows it to maneuver flexibly through narrow warehouse aisles. For safety, the vehicle can be equipped with enclosed guardrails to prevent goods from falling during transport, enclosed running boards to ensure the safety of the operator's feet when standing, and a foot brake for parking. The design also addresses the potential for drive wheel slippage under heavy loads.

[0028] Furthermore, the electric flatbed truck 10 adopts a rearward axle design. This design moves the drive axle further back, so that after loading goods, the center of gravity of the load is closer to the drive wheels, thereby increasing the normal force on the drive wheels and effectively improving ground adhesion and driving stability under heavy load conditions. Even further, the electric flatbed truck 10 uses a foldable, angled handle as the control component. When not in use, the handle can be folded away, further saving storage space in the warehouse.

[0029] In this embodiment, combined with Figure 2 As shown, the wearable barcode scanning device 20 specifically includes a Bluetooth ring barcode reader and a breathable arm sleeve that can be fixed to the operator's arm. The Bluetooth ring barcode reader is worn on the wrist, freeing the operator's hands. The operator can perform scanning operations without repeatedly grabbing and putting down the barcode scanner, allowing for seamless picking and scanning. The breathable arm sleeve contains a mobile terminal 50 running the intelligent picking system application. The screen of this mobile terminal 50 serves as a visual interactive interface, displaying task information and issuing prompts to the operator in real time. The operator only needs to naturally raise their arm to view these prompts, avoiding the inconvenience of holding the device.

[0030] The automatic sorting wall 40 can adopt a three-dimensional grid layout, for example, it can be designed as a layout of 6 rows by 4 columns and then by 8 layers, for a total of 192 physical sorting grids. Each sorting grid corresponds to a single customer order, which makes the single batch processing capacity of one sorting wall reach 192 orders. This is precisely matched with the capacity of the electric flatbed cart 10 to carry 4 picking boxes 30 at a time, with each box corresponding to one batch. That is, all 4 batches completed in one picking cycle can be directly sent to the automatic sorting wall 40 for continuous sorting, achieving seamless connection in the process.

[0031] Combining the aforementioned hardware devices, the implementation steps of this system are collaboratively achieved by a computing device 60 running on a backend server and an application (APP) on a mobile terminal 50. The computing device 60 can be deployed on a local server, in the cloud, or using a hybrid deployment model combining edge computing nodes and the cloud. Figure 3 and Figure 4As shown, the specific implementation steps of the computing device 60 are described below.

[0032] First, the computing device 60 has a built-in shelf location association module 61. During system initialization or warehouse layout adjustments, this module 61 is responsible for creating a file for each set of double-sided shelves, generating a unique shelf identifier, such as a unique QR code or barcode. This identifier is firmly bound in the database to all storage location codes on the left and right sides of its corresponding shelf. Each storage location code is also associated with its stored SKU (Stock Keeping Unit) information, its corresponding storage area, and other files. This establishes a fixed association relationship of "shelf identifier - left-side storage location set - right-side storage location set," laying the data foundation for subsequent one-click loading.

[0033] Secondly, a task classification and assignment module 62 runs within the computing device 60. When a new picking wave is generated, the task classification and assignment module 62 queries the storage locations in the warehouse based on the SKUs of the goods in the order to be picked, and automatically assigns all picking tasks to their corresponding shelf labels according to the aforementioned relationships. For example, if an order requires goods in storage location 3 on the left side of shelf A and goods in storage location 5 on the right side of shelf A, both tasks will be pre-assigned to the label of shelf A. This process is completed before the workers begin moving, achieving silent preprocessing of tasks in the background.

[0034] Before the operation begins, the operator drives an electric flatbed cart 10 and places four empty large picking boxes 30, each with a batch barcode already attached, onto the loading platform. Using a Bluetooth ring reader, the operator scans the barcodes on each of the four picking boxes 30 in sequence, and the app on the mobile terminal 50 binds these four physical boxes to the four picking batches for this operation.

[0035] The operator drives the electric flatbed cart 10 to the target shelf aisle. When approaching a set of shelves, the operator uses a Bluetooth ring reader to scan the shelf identification on the shelf. At this time, the APP sends the identification to the computing device 60. In response to this scanning operation, the computing device 60 calls up the data of its internal shelf storage location association module 61 and task classification mounting module 62, retrieves all the pending picking tasks in all storage locations on both sides of the shelf, including the goods to be picked, the corresponding required quantity, and the order information, and returns this data to the APP.

[0036] Next, a task display adjustment module 63 built into the computing device 60 begins execution. This is the core step in solving the path reversal problem in this embodiment, as detailed below: First, orientation rules need to be preset. In the backend management system, the warehouse manager will preset a forward / reverse travel attribute for each shelf barcode based on the warehouse's standard picking flow. For example, it is stipulated that traveling from south to north in the aisle is forward, in which case one physical side of the shelf is defined as the front and the other side as the back. This rule is stored as a basic parameter.

[0037] Next, direction recognition is performed. Once the app receives a set of tasks from both sides of a shelf, it determines the operator's direction of travel based on the currently provided information. This determination logic can be implemented in two ways, either individually or in combination: First, utilizing the built-in directional identifiers of the shelf barcode itself. For example, the shelf barcode can be designed as a directional QR code containing directional information. When the app scans the barcode using a camera, it can simultaneously analyze the relative angle from which the scanner approached the barcode, thus inferring whether they were approaching the shelf forward or backward. Second, relying on the inertial measurement unit (IMU) built into the vehicle or mobile terminal 50, or through Bluetooth AOA (Angle of Arrival) positioning technology, to obtain the vehicle's real-time heading angle, comparing it with the preset aisle path to determine the vehicle's current direction of travel. This constitutes a sensor fusion positioning module that receives raw orientation data from the scanning device and positioning system, and outputs a clear direction determination result.

[0038] Finally, the display order is adjusted. The task display adjustment module 63 performs three core operations on the task list based on the determined direction of travel: First, the logic was rearranged. Specifically, the visual logic of the display areas representing "left-side storage" and "right-side storage" on the APP interface was changed. The principle is to make the storage tasks on the side closer to the vehicle's driving lane appear more prominently and easily accessible on the interface. For example, if the vehicle is traveling in the forward direction and the lane is close to the physical left side of the shelf, then the "left-side storage" area on the interface will be placed at the top or highlighted, and vice versa.

[0039] Second, there's the location sorting. Specifically, based on the physical arrangement of the storage locations within the aisle, all items to be picked are reordered from nearest to farthest along the current travel route. This way, the order of the items on the interface perfectly maps to the order of the storage locations the vehicle is about to pass.

[0040] Third, the first item is highlighted. Specifically, the first item in the sorted list is highlighted first, that is, the item in the nearest pick location in the current direction of travel. The photo of the item and the required quantity are highlighted, providing unambiguous starting instructions for operators.

[0041] Therefore, through these three adjustments, when the operator enters the passage, the mobile terminal screen in front of him displays a "route list". The operator does not need to think at all, but only needs to walk straight along the passage and process the highlighted items one by one, completely eliminating the need for ineffective backtracking in the passage.

[0042] It should be noted that there is a special but common situation in the specific operating procedures. If the operator forgets to scan the shelf label first and instead uses a Bluetooth ring reader to scan a product label based on experience, then correction is required to prevent errors.

[0043] At this point, the APP uploads the scanned product identifier to the computing device 60. The task display adjustment module 63 in the computing device 60 initiates an auxiliary correction program. This program first queries the storage location file in the database to find the storage location code and its specific spatial coordinates of the product. Then, it matches the storage location coordinates with the electronic map of the warehouse aisle, thereby intelligently reversing and correcting the most likely direction of travel and the aisle where the operator is located. Once the direction and aisle are corrected and determined, based on this corrected information, the same logical swapping, position sorting, and first item highlighting operations as described above are performed to regenerate a correct route list and push it to the APP. This fault-tolerant design ensures that regardless of the operator's operation sequence, the system can ensure optimal path and user-friendly interface.

[0044] In this embodiment, when an operator removes a product from the shelf and scans its label according to the highlighted guidance, the APP interface undergoes a series of intuitive changes to assist the operation. In a preferred embodiment, the APP's product display area immediately shows a high-resolution photo of the product. This function constitutes a visual comparison step, allowing operators to quickly compare the actual product with the photo before placing it in the picking bin 30, effectively preventing mispicking due to similar packaging, unclear barcode printing, or other reasons. This is especially valuable for newly hired employees, significantly reducing their cognitive load and error rate, and greatly shortening the training cycle.

[0045] Meanwhile, the picking bin status area on the interface clearly displays the required quantity of the product in each of the four bound picking bins 30. Based on this, operators place the corresponding quantity of products into the four picking bins 30 and use a Bluetooth ring reader to scan the barcode of the completed picking bin for confirmation. Once the demand for a product in all four batches has been met, the product's photo and entry will automatically disappear from the task list, and the app will automatically jump to and highlight the next product to be picked. The entire interaction process is seamless and smooth, requiring no manual page turning or confirmation.

[0046] To further improve the overall efficiency of the system in multi-worker collaborative operation scenarios, this embodiment also integrates a worker searching efficiency optimization function. This function is implemented by a task dynamic balancing module 64 built into the computing device 60. The task dynamic balancing module 64 continuously collects and records the historical operation data of each worker, especially the time spent completing a single picking action, i.e., searching efficiency. Its working logic is as follows: For a non-new worker with historical data, the module obtains the searching efficiency values ​​of the first few statistically significant tasks completed recently (e.g., the first 5 times) and calculates their arithmetic mean, which is used as the worker's current efficiency parameter. For a new worker without historical data, to avoid deviations caused by initial value settings, the module pulls the searching efficiency of all non-new workers during their first operation and calculates the arithmetic mean of these initial efficiencies, which is used as the new worker's baseline efficiency parameter. After obtaining the efficiency parameters of each worker, the task dynamic balancing module 64 can dynamically adjust the task volume allocated to each person when generating picking waves or assigning tasks. The adjustment principle is "those with high efficiency should take on more tasks, and those with low efficiency should take on less tasks," so that workers with different skill levels can complete a workload that matches their abilities within the same standard working time. This avoids new employees being overwhelmed with pressure, which could lead to errors or further reduction in efficiency, and also avoids experienced employees being idle and waiting, thus achieving a balanced utilization of human resources in the entire picking team.

[0047] Understandably, if a particular batch of goods is particularly large during the picking process, causing a picking box 30 to be full, the operator can take out a spare empty picking box 30 from the vehicle at any time, attach the batch barcode of the unfinished batch to the new box, and scan the barcode of the new box with a Bluetooth ring barcode reader. The system then completes the replacement and binding of the old and new boxes, and the entire picking operation is not interrupted, continuing to instruct subsequent goods to be put into the new box.

[0048] Once the four picking batches carried by the electric flatbed cart 10 have been confirmed by the computing device 60, the APP on the mobile terminal 50 will issue a notification. The operator can then drive the electric flatbed cart 10 to transport the four full picking boxes 30 directly to the automatic sorting wall 40. These four boxes are connected to the entrance of the automatic sorting wall 40 sequentially or in parallel. Since the automatic sorting wall 40's processing capacity of 192 orders per batch perfectly matches the total capacity of 768 orders for the four picking boxes, the automatic sorting wall 40 can continuously and automatically sort the four batches without interruption. The sorting process is controlled by the automatic sorting wall 40's built-in scheduling engine. This engine receives order information corresponding to each slot from the computing device 60 and controls the goods to accurately fall into one of the 192 slots, thus realizing the integrated process from shelf picking to order sorting, eliminating the bottlenecks of transfer, handover, and waiting that inevitably exist between the picking area and the sorting area in traditional operation modes.

[0049] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For example, the size and carrying capacity of the electric flatbed cart 10 can be adjusted according to the actual warehouse conditions; the grid layout of the automatic seeding wall 40 can also be customized according to the order structure; in addition to barcodes and IMUs, orientation recognition technology can also adopt any technical solution with indoor positioning and orientation capabilities, such as ultra-wideband (UWB) positioning and visual simultaneous localization and mapping (V-SLAM). Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0050] In summary, the intelligent picking method and system provided by this invention systematically integrates the multi-batch carrying and movement capabilities of the stand-on electric flatbed cart 10, the one-click task loading mechanism based on "shelf identification - double-sided storage location", the direction recognition and interface adaptive sorting strategy that integrates multi-source information, and the automatic seeding wall 40 with precise matching backend processing capabilities. This constructs a highly coordinated S3D intelligent picking solution that integrates physical flow and information flow, solving the core problems of process disconnect, static path, and cumbersome human-machine interaction in the prior art. It achieves a leapfrog improvement in efficiency, accuracy, safety, and ease of operation.

[0051] Specifically, independent claim 1 of this invention protects an intelligent picking method. This method first provides an electric flatbed cart 10 equipped with a loading platform, which can simultaneously carry multiple picking boxes 30 corresponding to multiple picking batches, physically overcoming the limitation of single-cycle picking capacity. Based on this, a unique association is pre-established between shelf identifiers (such as electronic or physical barcodes) and all storage location information on both sides of the shelf through a backend system, and orders to be picked are pre-classified and loaded according to this association. When an operator drives the vehicle close to the shelf and scans the shelf identifier, the system can retrieve all picking tasks on both sides of the shelf with one click, completely eliminating the tedious process of scanning barcodes side by side.

[0052] More importantly, this method can obtain preset shelf location information and the current travel direction information of the electric flatbed cart 10, and adaptively adjust the display order of the retrieved picking tasks accordingly. The adjustment logic is to make the order of goods on the display interface completely consistent with the physical order of the storage locations traversed by the vehicle along the aisle, arranged from near to far, and prioritizing the highlighting of the first item to be picked on the path. This ensures that operators only need to walk straight along the path to complete the picking in sequence according to the interface guidance, without having to judge the location or turn back midway.

[0053] Finally, once all batches of tasks carried by the vehicle are completed, the batch of picking boxes is directly transported to the automatic seeding wall 40 for continuous seeding, realizing the "one-time patrol, picking and seeding in one" operation mode.

[0054] Therefore, the implementation principle and beneficial effects of the present invention are as follows: (1) Multiple batches in parallel and electric transport: Electric flatbed truck 10 is used as a mobile carrier to replace human walking and its cargo platform is used to carry multiple independent batches of picking boxes 30, maximizing the carrying capacity and mobility efficiency of a single operation, significantly reducing the physical exertion of operators and the ineffective walking time between the picking area and the sowing area, so that a single inspection can handle several times the order volume of the traditional solution, and the picking efficiency is increased exponentially. (2) One-click loading of dual-side tasks: By establishing a pre-binding relationship between "shelf identifier - dual-side storage location" and pre-loading tasks, multiple scanning and interface switching operations are compressed into a single scanning action. Using the physical entity of the shelf as the anchor point, the tasks it carries are spatially aggregated, which fundamentally reduces the number of human-computer interactions, reduces the complexity of operation, and improves the smoothness of task switching. (3) Adaptive interface sorting based on direction of travel: By acquiring and integrating the shelf location and vehicle direction of travel information, a minimum turnaround path is dynamically calculated and mapped to the display order of the task list. Thus, the result of path planning is reflected intuitively and in real time on the user interface. Through the visual guidance of "sorting from near to far" and "highlighting the first target", the behavior of the operators is naturally aligned with the optimal path, thereby greatly shortening the effective picking path and overcoming the blind operation and turnaround problems caused by the static task list. (4) Integrated picking and sorting: The final transportation of the picking process and the direct input of the sorting process are integrated in the physical flow and information flow, eliminating the buffer, waiting and transfer links between the two processes, making the batch processing rhythm accurately matched, thereby breaking through the bottleneck of the entire process from the shelf to the sorting grid, and making the overall throughput of the system achieve a qualitative leap.

[0055] This invention is not limited to what is described in the specification and embodiments. Therefore, other advantages and modifications can be readily realized by those skilled in the art. Thus, without departing from the spirit and scope of the general concept defined by the claims and their equivalents, this invention is not limited to the specific details, representative devices, and illustrative examples shown and described herein. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An intelligent picking method, based on an electric flatbed cart and a wearable barcode scanning device worn by the operator, wherein the electric flatbed cart has a cargo platform on which multiple picking boxes are detachably placed, each picking box corresponding to a picking batch; characterized in that, The intelligent picking method includes the following steps: Establish the association between shelf identification and storage location information on both sides of the shelf in the shelf area; wherein, the storage location information on both sides of the shelf includes storage location code and its corresponding product; Based on the orders to be picked, picking tasks involving the same shelf are categorized according to the storage locations on both sides of the shelf and attached to the corresponding shelf labels; In response to the wearable scanning device scanning the shelf identifier, all picking tasks on both sides of the shelf are retrieved, and the display order of picking tasks is adaptively adjusted according to the preset shelf position and the traveling direction information of the electric flatbed vehicle, so that the picking storage locations in the current traveling direction are sorted from near to far and highlighted first. Receives scans of product tags and prompts users to place the required quantity of products into the corresponding picking bin; Once all picking tasks for all batches are completed, the picking bins are instructed to be transported to the automated seeding wall for sorting.

2. The intelligent picking method as described in claim 1, characterized in that, The method also includes the following steps: if it is determined that the wearable barcode scanner directly scans the product label instead of the shelf label, then the preset channel route is automatically matched according to the location information of the storage location to which the product belongs, the current direction of travel of the electric flatbed cart is intelligently corrected, and the display order of the picking tasks is rearranged according to the corrected direction of travel.

3. The intelligent picking method as described in claim 1, characterized in that, The step of adaptively adjusting the display order of tasks to be picked, so that the storage locations to be picked in the current direction of travel are sorted from near to far and highlighted first, specifically includes: Based on the identified direction of travel, the display logic of the storage locations on the left and right sides of the shelf is changed on the display interface, so that the storage locations closer to the electric flatbed truck are displayed first. Reorder all items to be picked on both sides of the shelf according to their physical location on the current travel route, from near to far. Prioritize highlighting the product information corresponding to the first pending storage location in the current direction of travel.

4. The intelligent picking method as described in claim 1, characterized in that, It also includes the following steps: Obtain historical search efficiency data of the workers who drive the electric flatbed truck; For non-new employees, the arithmetic mean of their previous search efficiencies is used as the current efficiency parameter; for new employees, the arithmetic mean of the initial search efficiencies of all non-new employees is used as the baseline efficiency parameter. Based on the current or baseline efficiency parameters of each operator, the workload allocated to the batches they handle is dynamically adjusted to ensure that the workload of operators with different skill levels tends to be balanced within the same working time.

5. The intelligent picking method as described in claim 1, characterized in that, The wearable barcode scanner is a Bluetooth ring barcode reader and includes a mobile terminal that can be fixed to the operator's arm and run the picking system application. The mobile terminal is used to display the picking task interface in real time.

6. The intelligent picking method as described in claim 5, characterized in that, After scanning the product label with the wearable scanning device, a high-resolution photo of the product is displayed on the mobile terminal.

7. The intelligent picking method as described in claim 1, characterized in that, When any of the picking boxes is full, empty picking boxes can be added and the corresponding batch barcode can be attached. The barcode of the new box is scanned to complete the replacement binding, and the picking operation is not interrupted.

8. The intelligent picking method as described in claim 1, characterized in that, The automated sorting wall has multiple sorting slots arranged in rows and columns, and its single-batch sorting capacity matches the number of picking boxes that the electric flatbed truck can carry in a single transport and the average order capacity corresponding to each picking box.

9. The intelligent picking method as described in claim 1, characterized in that, The electric flatbed truck is a stand-on type electric flatbed truck, and it has a rearward-moving axle structure and an enclosed guardrail.

10. An intelligent picking system, characterized in that, include: An electric flatbed truck has a cargo platform on which multiple picking boxes can be detachably placed, each picking box corresponding to a picking batch; A wearable barcode scanner, worn by the operator, is used to scan shelf labels and product labels; An automatic sorting wall is used to automatically sort the goods in the picking box in batches; and at least one computing device configured to: Establish and store the association between shelf identification and storage location information on both sides of the shelf; Based on the orders to be picked, picking tasks involving the same shelf are categorized according to the storage locations on both sides of the shelf and attached to the corresponding shelf labels. In response to the wearable scanning device scanning the shelf identifier, all picking tasks on both sides of the shelf are retrieved, and the display order of picking tasks is adaptively adjusted according to the preset shelf position and the traveling direction information of the electric flatbed vehicle, so that the picking storage locations in the current traveling direction are sorted from near to far and highlighted first. Receives scans of product tags and prompts users to place the required quantity of products into the corresponding picking bin; And after all batch picking tasks are completed, instruct the picking box to be transported to the automated seeding wall for seeding.

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