Method and system for synchronously assisting in picking fresh goods by manpower and robot

Abstract

The invention discloses a method and system for synchronously assisting in sorting fresh goods through manpower and a robot, and relates to the field of logistics distribution. The method is applied to an intelligent sorting system and comprises the steps that management information of target storage is obtained, and the management information comprises the daily required warehouse-in amount, the storage amount, the daily required warehouse-out amount and the shelf life of various fresh goods; according to the management information, calculating a distribution index of the target warehouse; generating a resource allocation planning table of the target storage based on the distribution index; and the resource allocation planning table is sent to the warehouse management personnel, so that the warehouse management personnel can deploy resources required to be sorted of the target warehouse, and the resources required to be sorted comprise human resources and intelligent equipment resources. By implementing the technical scheme provided by the invention, the problems of low picking efficiency and high loss rate of the fresh goods at present are solved.

Description

Technical Field

[0001] The present application relates to the technical field of logistics distribution, and particularly relates to a method and system for synchronous auxiliary picking of fresh goods by humans and robots. Background Art

[0002] In recent years, with the significant improvement of people's living standards, the demand for the quality and variety of fresh food has become increasingly diversified, thus accelerating the continuous expansion of the scale of the fresh food distribution market. This has led to an increasingly urgent demand for immediate fresh food delivery from consumers. In this context, in order to improve the distribution efficiency, intelligent picking robots have been introduced in fresh food warehousing to assist manual sorting of goods.

[0003] However, due to the significant characteristics of fresh goods such as perishability, vulnerability, and short shelf life, higher requirements are imposed on the distribution efficiency. In the traditional manual operation mode, the distribution of goods in and out of the warehouse lacks scientificity, and the operation routes of goods transported to storage shelves lack scientific planning, resulting in low utilization efficiency of intelligent picking robots and unreasonable work distribution of picking personnel, thus reducing the picking efficiency of fresh goods and increasing the loss rate of fresh goods. Summary of the Invention

[0004] Aiming at the problems of low picking efficiency and high loss rate of current fresh goods, the present application provides a method and system for synchronous auxiliary picking of fresh goods by humans and robots.

[0005] In a first aspect, the present application provides a method for synchronous auxiliary picking of fresh goods by humans and robots, which is applied to an intelligent sorting system. The method includes: Obtaining management information of a target warehouse, where the management information includes the daily incoming quantity, storage quantity, daily outgoing quantity, and shelf life of various fresh goods; Calculating a distribution index of the target warehouse according to the management information; Generating a resource allocation planning table of the target warehouse based on the distribution index; Sending the resource allocation planning table to warehouse management personnel so that the warehouse management personnel can allocate the required picking resources of the target warehouse, where the required picking resources include human resources and intelligent device resources.

[0006] Optionally, the calculating a distribution index of the target warehouse according to the management information specifically includes: Calculating the remaining shelf life of various fresh goods in the target warehouse according to the management information; Calculating the urgency coefficients of various fresh goods according to the remaining shelf life; The delivery index of the target warehouse is calculated by using the delivery index calculation formula and the urgency coefficients of various fresh goods.

[0007] Optionally, the delivery index calculation formula is specifically: where P is the delivery index of the target warehouse, is the urgency coefficient of the i-th fresh good, is the daily outbound quantity of the i-th fresh good, is the current storage quantity of the i-th fresh good, is the daily inbound quantity of the i-th fresh good, and i is the type number of the fresh goods, with a total of n types, is the adjustment coefficient.

[0008] Optionally, generating the resource allocation planning table for the target warehouse based on the delivery index specifically includes: Calculating the delivery indices of various fresh goods; Calculating the ratio of the delivery indices of various fresh goods to the delivery index of the target warehouse; Determining the resource allocation priorities of various fresh goods according to the ratio results; Based on the resource allocation priorities, gradually allocating the required picking resources for the target warehouse to obtain the resource allocation planning table.

[0009] Optionally, the resource allocation planning table includes the inbound resource planning. Based on the resource allocation priorities, gradually allocating the required picking resources for the target warehouse to obtain the resource allocation planning table specifically further includes: According to the delivery index of the first fresh good, configuring the storage area of the first fresh good in the target warehouse, where the storage area includes the core area, the buffer area, and the edge area, and the first fresh good is any one of various fresh goods; Obtaining the remaining stock and the future expected inbound quantity of the first fresh good after storage; Calculating the pre-allocated capacity of the first fresh good according to the remaining stock and the future expected inbound quantity; Based on the storage area and the pre-allocated capacity of the first fresh good, conducting inbound resource planning for the first fresh good and storing it in the resource allocation planning table.

[0010] Optionally, the resource allocation planning table includes the outbound resource planning. Based on the resource allocation priorities, gradually allocating the required picking resources for the target warehouse to obtain the resource allocation planning table specifically further includes: Obtain multiple outbound nodes of the second fresh product, where the second fresh product is any one of multiple fresh products; Calculate the contribution of multiple outbound nodes to the outbound distribution of the second fresh product; Based on the contribution of multiple outbound nodes, perform inbound resource planning for multiple outbound nodes of the second fresh product and store it in the resource configuration planning table.

[0011] Optionally, the resource configuration planning table includes commodity storage and transportation resource planning. Based on the resource configuration priority, perform hierarchical allocation of the required picking resources for the target warehouse to obtain the resource configuration planning table, which specifically further includes: Obtain multiple storage and transportation targets of the third fresh product, where multiple storage and transportation targets include available resources, storage and transportation time, storage and transportation loss, and available storage and transportation paths, and the third fresh product is any one of multiple fresh products; Based on multiple storage and transportation targets, use the greedy strategy to generate an initial storage and transportation population; Use the NSGA-II algorithm to calculate the optimal storage and transportation path of the initial storage and transportation population; Based on the optimal storage and transportation path, perform commodity storage and transportation resource planning for the third fresh product and store it in the resource configuration planning table.

[0012] In a second aspect, the present application provides a system for manually and robotically synchronously assisting in picking fresh products. The system is an intelligent sorting system, and the intelligent sorting system includes an acquisition module, a processing module, and a sending module, where: The acquisition module is used to obtain the management information of the target warehouse, and the management information includes the daily required inbound quantity, storage quantity, daily required outbound quantity, and shelf life of multiple fresh products; The processing module is used to calculate the distribution index of the target warehouse based on the management information; based on the distribution index, generate a resource configuration planning table for the target warehouse, and the resource configuration planning table includes inbound resource planning, outbound resource planning, and commodity storage and transportation resource planning; The sending module is used to send the resource configuration planning table to the warehouse management personnel, so that the warehouse management personnel can allocate the required picking resources for the target warehouse, and the required picking resources include human resources and intelligent device resources.

[0013] In a third aspect, the present application provides an electronic device, including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method described in any item of the first aspect.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium storing instructions that, when executed, perform the method according to any one of the first aspect.

[0015] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By obtaining the management information of the target warehouse (the daily inbound volume, storage volume, daily outbound volume, and shelf life of various fresh products), and calculating the distribution index based on this information, the present application generates a resource allocation planning table covering inbound resource planning, outbound resource planning, and commodity operation resource planning, and finally sends the planning table to the warehouse management personnel to guide the allocation of human resources and intelligent device resources. In this process, through intelligent distribution index calculation and resource allocation planning, the efficient dynamic allocation of warehouse picking resources is achieved, significantly improving the picking efficiency of fresh products, reducing losses caused by manual operation errors and improper resource allocation, optimizing the warehouse management process, reducing labor costs and time costs, and providing reliable technical support for the rapid circulation and shelf life management of fresh products.

[0016] 2. When generating the resource allocation planning table, the present application further refines the resource planning methods of the three aspects according to the respective operation modes of inbound, outbound, and operation of fresh products, making the dynamic allocation of warehouse picking resources more reasonable. Among them, for the inbound of fresh products, according to the distribution index of fresh products, the corresponding storage area is configured, and then according to its remaining stock and future expected inbound volume, its pre-allocated capacity is determined. Finally, in combination with the storage area, the resource allocation during the inbound process of fresh products is further refined, reducing the loss during the inbound process of fresh products while improving the inbound efficiency. For the outbound of fresh products, since there are many uncertain factors in the outbound of fresh products, the present application plans the resource allocation of each outbound node according to the influence (contribution degree) of each outbound node of fresh products on the distribution index of fresh products, thus improving the response speed to emergencies during the outbound process. For the operation of fresh products, in order to ensure the highest operation efficiency, multiple operation targets are set. The operation targets can be understood as the feasible solutions of various indicators during the operation process. Then, the greedy strategy is used to generate an initial operation population from multiple operation targets, and finally, the optimal operation path is calculated by combining the NSGA-II algorithm. At this time, the resource allocation for the operation is carried out according to the optimal operation path, which can maximize the balance between efficiency and warehouse picking resources. Generally speaking, by refining the resource planning methods of inbound, outbound, and operation, while greatly improving the risk resistance ability of fresh warehouses, it can also ensure that the distribution efficiency meets market demands. Description of the Drawings

[0017] Figure 1 It is a schematic flow chart of a method for manual and robot synchronous assisted picking of fresh food products provided by an embodiment of the present application.

[0018] Figure 2 It is a schematic structural diagram of a system for manual and robot synchronous assisted picking of fresh food products provided by an embodiment of the present application.

[0019] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0020] Explanation of reference numerals: 1, acquisition module; 2, processing module; 3, sending module; 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed implementation manners

[0021] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0022] In the description of the embodiments of the present application, words such as "for example" or "for illustration" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "for example" or "for illustration" in the embodiments of the present application should not be construed as being more preferred or more advantageous than other embodiments or design solutions. Exactly speaking, the use of words such as "for example" or "for illustration" is intended to present relevant concepts in a specific manner.

[0023] In the description of the embodiments of the present application, the meaning of the term "plurality" refers to two or more. For example, a plurality of systems refers to two or more systems, and a plurality of screen terminals refers to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the technical features indicated. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "include", "comprise", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0024] In the current context of rapid economic development, people's living standards have been significantly improved, which has also greatly promoted the booming development of the fresh food distribution market. In recent years, as the scale of the fresh food distribution market continues to expand, consumers' demand for instant fresh food delivery has become increasingly urgent. Everyone hopes to receive fresh and intact fresh food products within a short time after placing an order. To meet this demand, intelligent picking robots have emerged. By introducing intelligent picking robots to assist manual sorting of goods, the sorting efficiency can be improved, and thus the speed of the entire fresh food distribution can be enhanced.

[0025] However, fresh food products themselves have the characteristics of perishability, vulnerability, and a short shelf life, which pose extremely high requirements for distribution efficiency. This has led to a lack of scientific and reasonable planning for the warehousing and outbound distribution of goods in the traditional manual operation mode in the past. It was often arranged based on experience, without fully considering factors such as the characteristics of the goods, storage conditions, and order requirements. Secondly, the transportation routes of goods to the storage shelves also lack scientific planning, resulting in a waste of a large amount of time and manpower during transportation, and even possible damage to goods due to unreasonable routes.

[0026] These problems have directly led to the low utilization efficiency of intelligent picking robots, with most of the time being idle or in a low-efficiency working state. At the same time, the work distribution of picking personnel is also unreasonable, with some people having too heavy tasks and some being relatively relaxed, thus affecting work efficiency and further reducing the picking efficiency of fresh food products.

[0027] To solve the above problems, this application provides a method for synchronous manual and robotic assisted picking of fresh food products. This method is applied to an intelligent sorting system, as Figure 1 shown. This method includes steps S101 to S104, and the above steps are as follows: S101. Obtain the management information of the target warehouse. The management information includes the daily inbound volume, storage volume, daily outbound volume, and shelf life of various fresh food products.

[0028] In the above step, the intelligent sorting system generates daily inbound tasks and outbound tasks based on the purchase orders and sales orders of the target warehouse, then stores the inbound tasks and outbound tasks in the management log, and real-time updates the inventory and storage time of the goods in the target warehouse. Before the daily operation of the warehouse starts, according to the inbound tasks and outbound tasks of the day, it retrieves the daily inbound volume, storage volume, daily outbound volume, and shelf life of various fresh food products of the day.

[0029] S102. Calculate the distribution index of the target warehouse based on the management information.

[0030] In the above steps, the delivery index can be understood as a quantitative indicator of the overall situation and complexity of the target warehouse in the distribution of fresh food products. It comprehensively considers various factors such as the daily inbound volume, storage volume, daily outbound volume, and shelf life. When the delivery index is relatively high, it indicates that the distribution task of the warehouse is heavy, and it is necessary to increase the number of pickers, dispatch more intelligent robots and other equipment to improve the distribution efficiency. When calculating the delivery index, first calculate the remaining shelf life of the fresh food products according to the shelf life and storage time of various fresh food products stored in the target warehouse, and then calculate the urgency coefficient corresponding to each of the various fresh food products according to the remaining shelf life of the various fresh food products. The specific calculation can be carried out using the following formula: Where t is the remaining shelf life and T is the urgency coefficient. It can be understood that the shorter the remaining shelf life, the greater the urgency coefficient.

[0031] Finally, use the delivery index calculation formula and the urgency coefficients of various fresh food products to calculate the overall delivery index of the target warehouse. Among them, the delivery index calculation formula is specifically as follows: Where P is the delivery index of the target warehouse, is the urgency coefficient of the i-th fresh food product, is the daily outbound volume of the i-th fresh food product, is the current storage volume of the i-th fresh food product, is the daily inbound volume of the i-th fresh food product, i is the type number of the fresh food product, and there are a total of n types, is the adjustment coefficient.

[0032] In the above formula, can be understood as the inventory turnover pressure. The less the current storage volume of the fresh food product, the greater the turnover pressure. Among them, is the adjustment coefficient when the fresh food product has zero inventory. It is a very small value used to represent the extreme shortage of the fresh food product; can be the supply-demand imbalance degree between the inbound and outbound of the fresh food product. The greater the difference between the daily inbound volume and the daily outbound volume, the more tense the supply and demand of the fresh food product; then, multiply the sum of the turnover pressure and the supply-demand imbalance degree of the fresh food product by the urgency coefficient to dynamically adjust the overall distribution pressure of the fresh food product. Finally, determine the overall delivery index of the target warehouse by counting the delivery indices of all types of fresh food products that need to be turned over on the same day.

[0033] S103. Generate a resource allocation plan table for the target warehouse based on the delivery index.

[0034] In the above steps, for the target warehouse, its configurable resources include human resources and intelligent device resources. The intelligent device resources cover AGV intelligent handling robots, intelligent loading devices, intelligent unloading devices, and intelligent picking devices, etc. To improve the effective utilization rate of the configurable resources, this application first calculates the distribution indices corresponding to various fresh food products, and its calculation formula is: Wherein, is the distribution index of the i-th fresh food product, is the urgency coefficient of the i-th fresh food product, is the daily outbound quantity of the i-th fresh food product, is the current storage quantity of the i-th fresh food product, is the daily inbound quantity of the i-th fresh food product, and i is the type number of the fresh food product, with a total of n types, is the adjustment coefficient Then, calculate the ratio of the distribution indices corresponding to various fresh food products to the overall distribution index of the target warehouse, so as to determine the resource allocation priorities corresponding to various fresh food products. It can be understood that if the ratio result of a certain fresh food product to the distribution index of the target warehouse is larger, it means that the pressure of this fresh food product is greater, and its resource allocation priority is higher. At this time, according to the resource allocation priorities corresponding to various fresh food products, preferentially allocate resources to the fresh food products with high priorities, so as to achieve the efficient dynamic allocation of warehouse picking resources, improve the effective utilization rate of resources, and reduce the losses caused by manual operation errors and improper resource allocation.

[0035] When allocating resources for fresh food products, it includes inbound resource planning, commodity operation and storage resource planning, and outbound resource planning; among them: Regarding the inbound resource planning, to ensure that fresh food products have sufficient storage space and suitable storage conditions, this application configures their storage areas in the target warehouse according to the distribution indices of fresh food products. Among them, the storage areas include the core area, the buffer area, and the edge area. The core area is the emergency shipping area for fresh food products, the buffer area is the short-term storage area for fresh food products, and the edge area is the long-term storage area for fresh food products. At this time, when the distribution index of a fresh food product is relatively high, it is configured in the core area; when the distribution index of a fresh food product is relatively low, it is configured in the buffer area or the edge area. Then, by obtaining the current remaining stock quantity of the fresh food product in the target warehouse and the future expected inbound quantity, the future pre-allocation capacity of the fresh food product is predicted, so as to reduce the possible distribution pressure of the fresh food product. Specifically, the following formula can be used: Pre-allocation capacity = remaining stock quantity - future expected inbound quantity × safety factor Among them, the safety factor can be understood as the loss ratio of fresh goods during the warehousing process, and 0.9 can be taken in actual situations.

[0036] Finally, according to the storage area and pre-allocated capacity of fresh goods, the warehousing resource planning for fresh goods is carried out, and the planning results are stored in the resource allocation planning table. The resources configured therein include the available intelligent devices corresponding to the storage area and the corresponding proportion of human resources.

[0037] Regarding the outbound resource planning, since there are many uncertain factors in the outbound of fresh goods, for example, a sudden increase in sales orders will disrupt the original outbound plan, thus reducing the distribution efficiency of fresh goods; based on this, in this application, the outbound of fresh goods is split into multiple outbound nodes, which specifically include steps such as picking, handling, and loading, and then the contribution degrees of the multiple outbound nodes to the outbound distribution of fresh goods are calculated to clarify the impact of each outbound node on the overall outbound distribution efficiency; specifically: the contribution of the outbound node to the commodity distribution is split into efficiency contribution, priority contribution, and capacity contribution, and then the contribution values of the three are calculated respectively, where: Among them, the efficiency contribution value characterizes the coping ability of the current outbound node relative to the outbound node with the highest efficiency. It characterizes the processing ability of the current outbound node for the outbound of high-priority fresh goods, and the capacity contribution value characterizes whether the remaining processing ability of the current outbound node can meet the outbound node with the highest remaining processing ability among other outbound nodes; then, the efficiency contribution value, priority contribution value, and capacity contribution value of each outbound node are multiplied by their respective weights and then added together to obtain the contribution degree of the outbound node to the outbound distribution of fresh goods.

[0038] Finally, according to the contribution degrees of the multiple outbound nodes, the inbound resource planning for the multiple outbound nodes of fresh goods is carried out and stored in the resource allocation planning table. For example, for the outbound node with a lower contribution degree, more resources are allocated to improve its outbound processing efficiency for fresh goods.

[0039] Regarding the planning of commodity operation storage resources, it should be noted that the operation storage of fresh goods is generally automatically completed by AGV handling robots. At this time, multiple operation storage goals need to be considered, namely, the highest effective utilization rate of available resources, the shortest operation storage time, the lowest operation storage loss, and the shortest operation storage path. Under multiple operation storage goals, the commonly used algorithm is the NSGA-II algorithm. However, this algorithm has some defects, such as: the solution quality highly depends on the initial population level and may fall into local optimum and converge prematurely. Therefore, to solve this problem, this application improves the quality of the initial population by adopting a greedy strategy to accelerate the population convergence speed, that is, based on multiple operation storage goals, a greedy strategy is used to generate an initial operation storage population, and then the NSGA-II algorithm is used to calculate the optimal operation storage path of the initial operation storage population. Finally, according to the optimal operation storage path, the commodity operation storage resources of the third fresh goods are planned and stored in the resource configuration planning table, so as to clarify the required allocated warehousing picking resources while satisfying the optimal solution of multiple operation storage goals, thereby improving the operation storage efficiency of fresh goods.

[0040] S104. Send the resource configuration planning table to the warehousing management personnel so that the warehousing management personnel can allocate the required picking resources for the target warehouse. The required picking resources include human resources and intelligent device resources.

[0041] In the above steps, the resource configuration planning table contains the resource configuration situations of various fresh goods on the same day in three aspects: warehousing, operation storage, and outbound, providing reference opinions for the warehousing management personnel to plan the warehousing picking resources, thereby optimizing the warehousing management process, reducing labor costs and time costs, and providing reliable technical support for the rapid circulation and shelf-life management of fresh goods.

[0042] Refer to Figure 2 This application also provides a system for manually and robotically synchronously assisting in picking fresh goods. The system is an intelligent sorting system, which includes an acquisition module 1, a processing module 2, and a sending module 3, where: The acquisition module 1 is used to acquire the management information of the target warehouse. The management information includes the daily inbound volume, storage volume, daily outbound volume, and shelf life of various fresh goods. The processing module 2 is used to calculate the distribution index of the target warehouse based on the management information; based on the distribution index, generate a resource configuration planning table for the target warehouse. The resource configuration planning table includes inbound resource planning, outbound resource planning, and commodity operation storage resource planning. The sending module 3 is used to send the resource configuration planning table to the warehousing management personnel so that the warehousing management personnel can allocate the required picking resources for the target warehouse. The required picking resources include human resources and intelligent device resources.

[0043] In a possible implementation, according to the management information, the distribution index of the target warehouse is calculated, specifically including: According to the management information, calculate the remaining shelf life of various fresh goods in the target warehouse; According to the remaining shelf life, calculate the urgency coefficients of various fresh goods; Using the distribution index calculation formula and the urgency coefficients of various fresh goods, calculate the distribution index of the target warehouse.

[0044] In a possible implementation, the distribution index calculation formula is specifically: where P is the distribution index of the target warehouse, is the urgency coefficient of the i-th fresh good, is the daily outbound quantity of the i-th fresh good, is the current storage quantity of the i-th fresh good, is the daily inbound quantity of the i-th fresh good, i is the type number of the fresh good, and there are a total of n types, is the adjustment coefficient.

[0045] In a possible implementation, generating the resource allocation plan table for the target warehouse based on the distribution index specifically includes: Calculate the distribution indices of various fresh goods; Calculate the ratio of the distribution indices of various fresh goods to the distribution index of the target warehouse; According to the ratio result, determine the resource allocation priorities of various fresh goods; Based on the resource allocation priorities, perform step-by-step allocation of the required picking resources for the target warehouse to obtain the resource allocation plan table.

[0046] In a possible implementation, the resource allocation plan table includes the inbound resource plan. Based on the resource allocation priorities, performing step-by-step allocation of the required picking resources for the target warehouse to obtain the resource allocation plan table specifically further includes: According to the distribution index of the first fresh good, configure the storage area of the first fresh good in the target warehouse, and the storage area includes the core area, the buffer area, and the edge area, where the first fresh good is any one of various fresh goods; Obtain the remaining stock and the future expected inbound quantity of the first fresh good after storage; According to the remaining stock and the future expected inbound quantity, calculate the pre-allocated capacity of the first fresh good; Based on the storage area and the pre-allocated capacity of the first fresh goods, plan the warehousing resources for the first fresh goods and store them in the resource allocation plan table.

[0047] In a possible implementation manner, the resource allocation plan table includes the outbound resource plan. Based on the resource allocation priority, gradually allocate the required picking resources for the target warehouse to obtain the resource allocation plan table. Specifically, it further includes: Obtain multiple outbound nodes of the second fresh goods, where the second fresh goods is any one of the multiple fresh goods; Calculate the contribution degrees of the multiple outbound nodes to the outbound distribution of the second fresh goods; Based on the contribution degrees of the multiple outbound nodes, plan the warehousing resources for the multiple outbound nodes of the second fresh goods and store them in the resource allocation plan table.

[0048] In a possible implementation manner, the resource allocation plan table includes the commodity operation resource plan. Based on the resource allocation priority, gradually allocate the required picking resources for the target warehouse to obtain the resource allocation plan table. Specifically, it further includes: Obtain multiple operation targets of the third fresh goods, where the multiple operation targets include available resources, operation time, operation loss, and available operation paths, and the third fresh goods is any one of the multiple fresh goods; Based on the multiple operation targets, generate an initial operation population using the greedy strategy; Use the NSGA-II algorithm to calculate the optimal operation path of the initial operation population; Based on the optimal operation path, plan the commodity operation resources for the third fresh goods and store them in the resource allocation plan table.

[0049] It should be noted that when the device provided in the above embodiment realizes its functions, only the above-mentioned division of each functional module is used for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0050] This application also discloses an electronic device. Refer to Figure 3 , Figure 3It is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0051] Among them, the communication bus 302 is used to realize the connection and communication between these components.

[0052] Among them, the user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0053] Among them, the network interface 304 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0054] Among them, the processor 301 may include one or more processing cores. The processor 301 connects various parts within the entire server through various interfaces and lines, and by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling data stored in the memory 305, it executes various functions of the server and processes data. Optionally, the processor 301 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 301 may integrate one or several combinations of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, and application programs, etc.; the GPU is responsible for the rendering and drawing of the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately by a single chip.

[0055] Among them, the memory 305 may include a Random Access Memory (RAM), or may also include a Read-Only Memory. Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above method embodiments, etc.; the data storage area may store the data involved in the above method embodiments. Optionally, the memory 305 may also be at least one storage device located far from the aforementioned processor 301. Refer to Figure 3 , in the memory 305 as a computer storage medium, it may include an operating system, a network communication module, a user interface module, and an application program for a method of manually and robotically synchronously assisting in picking fresh produce.

[0056] In Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user to obtain the data input by the user; while the processor 301 can be used to call the application program stored in the memory 305 for a method of manually and robotically synchronously assisting in picking fresh produce. When executed by one or more processors 301, the electronic device 300 is caused to execute one or more of the methods as described in the above embodiments. It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0057] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0058] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection between each other can be through some service interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0059] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0060] In addition, each functional unit in various embodiments of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0061] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of the present application. And the aforementioned memory includes: various media such as USB flash drives, mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0062] The above are only exemplary embodiments of the present disclosure and should not be used to limit the scope of the present disclosure. That is, all equivalent changes and modifications made according to the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will easily think of other implementation schemes of the present disclosure after considering the specification and the disclosure of the practical truth.

[0063] The present application aims to cover any variations, uses, or adaptive changes of the present disclosure. These variations, uses, or adaptive changes follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for picking fresh products by manual and robot assisted synchronously, characterized in that: Applied to an intelligent sorting system, the method comprises: Obtaining management information of the target warehouse, the management information including daily incoming quantity, storage quantity, daily outgoing quantity and shelf life of various fresh goods; Calculate the distribution index of the target warehouse according to the management information; Based on the distribution index, generating a resource allocation planning table for the target warehouse; The resource allocation planning table is sent to the warehouse management personnel so that the warehouse management personnel can allocate the required picking resources of the target warehouse, and the required picking resources include human resources and intelligent equipment resources.

2. The method according to claim 1, characterized in that The calculating, based on the management information, the distribution index of the target warehouse specifically includes: Calculating the remaining shelf life of the plurality of fresh products in the target warehouse according to the management information; Calculating the urgency coefficients of the plurality of fresh products according to the remaining shelf life; The distribution index of the target warehouse is calculated by using the distribution index calculation formula and the urgency coefficients of the various fresh products.

3. The method according to claim 2, characterized in that The distribution index calculation formula is specifically: Among them, P is the distribution index of the target warehouse, is the urgency coefficient of the i-th fresh product, is the daily outbound demand of the i-th fresh product, is the current storage volume of the i-th fresh product, is the daily inventory requirement of the i-th fresh product, i is the type number of the fresh product, and there are n types in total. is the adjustment coefficient.

4. The method according to claim 1, characterized in that: The generating of the resource allocation planning table of the target warehouse based on the distribution index specifically includes: Calculating the delivery index of the plurality of fresh products; Calculating the ratio of the delivery index of the plurality of fresh commodities to the delivery index of the target warehouse; Determining resource allocation priorities of the plurality of fresh products according to the ratio results; Based on the resource allocation priority, the required picking resources are allocated to the target warehouse step by step to obtain the resource allocation planning table.

5. The method according to claim 4, characterized in that The resource allocation planning table includes a warehousing resource planning, and based on the resource allocation priority, the required picking resources are allocated to the target warehouse step by step to obtain the resource allocation planning table, which specifically includes: According to the distribution index of the first fresh product, a storage area of ​​the first fresh product in the target warehouse is configured, the storage area includes a core area, a buffer area and a marginal area, and the first fresh product is any one of the multiple fresh products; Obtaining the remaining stock of the first fresh product after storage and the expected future storage volume; Calculate the pre-allocated capacity of the first fresh product according to the remaining inventory and the future expected inventory volume; Based on the storage area and pre-allocated capacity of the first fresh product, storage resources are planned for the first fresh product and stored in the resource allocation planning table.

6. The method according to claim 4, characterized in that The resource allocation planning table includes outbound resource planning, and based on the resource allocation priority, the required picking resources are allocated to the target warehouse step by step to obtain the resource allocation planning table, which specifically includes: Acquire multiple outbound nodes of a second fresh product, where the second fresh product is any one of the multiple fresh products; Calculating the contribution of the plurality of the outbound nodes to the outbound delivery of the second fresh product; According to the contribution of the plurality of outbound nodes, inbound resources are planned for the plurality of outbound nodes of the second fresh product and stored in the resource allocation planning table.

7. The method according to claim 4, characterized in that The resource allocation planning table includes commodity storage resource planning, and the resource allocation planning table is obtained by allocating the required picking resources to the target warehouse based on the resource allocation priority, and specifically includes: Acquire multiple storage targets of a third fresh product, wherein the multiple storage targets include available resources, storage time, storage loss, and available storage paths, and the third fresh product is any one of the multiple fresh products; Based on the multiple operation and storage targets, an initial operation and storage population is generated using a greedy strategy; Using the NSGA-II algorithm, the optimal operation and storage path of the initial operation and storage population is calculated; According to the optimal storage path, commodity storage resources are planned for the third fresh product and stored in the resource allocation planning table.

8. A system for picking fresh produce with manual and robot assistance, characterized in that: The system is an intelligent sorting system, comprising an acquisition module (1), a processing module (2) and a sending module (3), wherein: The acquisition module (1) is used to acquire management information of the target warehouse, wherein the management information includes daily required inbound quantity, storage quantity, daily required outbound quantity and shelf life of various fresh goods; The processing module (2) is used to calculate the distribution index of the target warehouse according to the management information; based on the distribution index, generate a resource allocation planning table for the target warehouse, the resource allocation planning table including inbound resource planning, outbound resource planning and commodity storage resource planning; The sending module (3) is used to send the resource allocation planning table to the warehouse management personnel, so that the warehouse management personnel can allocate the required picking resources of the target warehouse, and the required picking resources include human resources and intelligent equipment resources.

9. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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