Intelligent warehousing system and warehouse guiding control method

Abstract

The invention relates to intelligent warehousing, and provides an intelligent warehousing system and a warehouse guiding control method, and the system comprises a cargo storage unit, a cargo conveying unit, a cargo sensing unit, a light-emitting positioning guiding device group, a positioning terminal, and a warehouse information processing system in communication connection with the cargo storage unit, the cargo conveying unit, the cargo sensing unit, the light-emitting positioning guiding device group and the positioning terminal. The positioning terminal collects signal light for matching the associated information set to determine the position of the terminal; a warehouse information processing system obtains cargo attribute information of cargos, and generates a planned route of warehouse-in / warehouse-out of the cargos based on a destination position corresponding to the cargo attribute information; and determining a group of target light-emitting positioning guiding devices according to the matching relationship between the position information of the light-emitting positioning guiding devices and the planned route, and instructing the target light-emitting positioning guiding devices to execute a light-emitting guiding action.

Description

Technical Field

[0001] The present disclosure relates to the field of smart warehousing technology, and in particular to a smart warehousing system and a warehouse guidance control method. Background Art

[0002] Traditional warehousing management methods can no longer meet the needs of modern logistics for efficiency, accuracy, and intelligence. Especially for ports, where there are many types of materials, frequent warehousing and warehousing, and great management difficulties, it is imperative to build smart warehouses.

[0003] However, in the current intelligent warehouse technology, although the efficiency of goods operation is improved through automated equipment, data collection, and display, some technologies are still missing in actual scene applications. For example, due to traditional problems or cost issues, many intelligent warehouses still use semi-automatic solutions that combine manual and machine operations. This leads to higher requirements for manual work in many scenarios, affecting the efficiency of goods operation. For example, when querying goods, although the target goods and the warehouse location of the goods can be quickly found based on the goods entry records, for the scenario of manual pickup, if the staff has little experience, they may not clearly understand the warehouse goods storage layout information, and cannot quickly find the target location of the goods. They need to refer to the identification and confirm one by one, which is very inconvenient; by the same token, when storing goods, the staff also needs to find and confirm the target location where the goods need to be placed, which is very inconvenient.

[0004] In addition, even if one is willing to accept higher costs and use fully automated equipment, such as automated guided vehicles (AGVs) and smart stackers to perform unmanned work, taking AGVs as an example, by pre-learning the warehouse terrain and routes, etc., it can automatically deliver goods. However, there are still problems such as limited movement speed, less flexibility than manual labor, easy failure and low reliability, which also affect the efficiency of cargo handling. In addition, once a failure occurs, temporary manual replacement may still be required, which also means the above problems exist.

[0005] Therefore, how to design a navigation solution that can conveniently guide workers to reach the target location efficiently and quickly, and even better, be compatible with the guidance of AGVs at a lower cost, has become a technical problem that needs to be urgently solved in the industry. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a smart warehousing system and a warehouse guidance control method to solve the problems in the related technology.

[0007] The first aspect of the present disclosure provides an intelligent warehousing system, which is applied to a warehouse and includes: a goods storage unit, which is arranged in the warehouse and has a goods storage space; a goods conveying unit, which is arranged in the warehouse and includes: a goods transporting sub-unit for transporting goods in the warehouse, and a goods handling sub-unit for disposing goods to the goods storage unit; a goods sensing unit, which is at least arranged at the inbound position, outbound position and goods storage unit, and is used for sensing goods and collecting goods attribute information; a group of light-emitting positioning and guiding devices, which are distributed in the warehouse and are used for emitting at least one type of signal light to indicate the location; wherein each light-emitting positioning and guiding device has an information set generated based on an associated one of the light-emitting device identifier, location information and light-emitting characteristics, for optical communication with the outside to determine the location based on the information set; the signal lights of each of the light-emitting positioning and guiding devices have different light-emitting characteristics; the group of light-emitting positioning and guiding devices is used for providing a group of target light-emitting positioning and guiding devices that perform a light-emitting guiding action corresponding to the current planned route; a positioning terminal, which can be carried and moved by the goods conveying unit or a staff member, and is used for collecting the signal light, for matching the associated information set according to the signal light to determine the location of the terminal; a warehouse information processing system, which is communicatively connected with the goods conveying unit, the goods sensing unit, each of the light-emitting positioning and guiding devices and the positioning terminal, and is used for obtaining the goods attribute information of the goods, and generating the inbound / outbound planned route of the goods based on the destination location corresponding to the goods attribute information; and, determining a group of target light-emitting positioning and guiding devices according to the matching relationship between the location information of a group of the light-emitting positioning and guiding devices and the planned route, and instructing them to perform a light-emitting guiding action.

[0008] In an embodiment of the first aspect, the warehouse information processing system includes a warehousing deployment strategy prediction module for predicting a warehousing deployment strategy according to in / out warehouse goods data; the warehousing deployment strategy prediction module includes: a logistics prediction module for collecting logistics transportation information of each logistics transportation vehicle with in / out warehouse behavior with the warehouse in the future from a transportation logistics database, and predicting first in / out warehouse predicted goods data of the goods delivered by each logistics transportation vehicle arriving at the warehouse at the target time slot based thereon; the target time slots of each logistics transportation vehicle form a target time slot sequence in the order of time slots; an in / out warehouse prediction module for using an in / out warehouse time sequence prediction model to predict second in / out warehouse predicted goods data of each future time slot in a future preset duration and corresponding first warehousing allocation resource prediction information of the next time slot one by one according to the immediately updated historical in / out warehouse actual data of the warehouse; wherein the future preset duration includes one or more of the target time slots; a warehousing scheduling module for traversing in the order of the target time slot sequence, superimposing the first in / out warehouse goods data predicted by the logistics prediction module at the current target time slot to the second in / out warehouse predicted goods data predicted by the in / out warehouse prediction module, so as to obtain updated in / out warehouse goods prediction data of the current target time slot; and matching the first warehousing allocation resource prediction information of the current target time slot with the updated in / out warehouse goods prediction data, and updating the inventory deployment strategy of the time slots before the current target time slot according to the matching result.

[0009] In an embodiment of the first aspect, the warehouse information processing system includes: a replenishment time sequence prediction module for executing an intelligent replenishment prediction process, including: using an inventory time sequence prediction model to predict the predicted inventory quantity of target goods in a future time slot based on historical inventory data, and using a project demand time sequence prediction model to obtain the predicted shipment demand quantity of the target goods in a future time slot based on the prediction of the historical project demand goods data of the target goods or based on the planned project demand shipment goods data; comparing the predicted inventory quantity with the predicted shipment demand quantity of the goods; when there is a first predicted inventory shortage quantity in the comparison, determining to execute a replenishment strategy at the current time slot; wherein the replenishment strategy includes: determining a first replenishment quantity to make up for the first predicted inventory shortage quantity; predicting the predicted replenishment quantity in a future time slot based on the historical replenishment quantity data of one or more suppliers for the target goods; selecting one supplier whose predicted replenishment quantity can meet the first predicted inventory shortage quantity or multiple suppliers whose sum of predicted replenishment quantities can meet the first predicted inventory shortage quantity as target suppliers to execute the replenishment action.

[0010] In an embodiment of the first aspect, the warehouse information processing system includes a recommended storage location module, which is configured to, in response to a goods receipt record being generated for goods, determine a matching recommended goods storage space in a goods storage unit according to the goods attribute information of the goods, and perform a virtual storage action of storing the goods in a virtual recommended space corresponding to the recommended goods storage space to obtain a virtual warehousing record; when the goods are actually stored, determine a corresponding recommended storage space based on the virtual storage space of the virtual warehousing record, and form an actual warehousing record in response to the completion of the actual storage action; wherein, the goods storage unit has storage unit attribute information, and the goods conveying unit has conveying unit attribute information; the determination of the matching recommended goods storage space according to the goods attribute information of the goods includes: based on the establishment of an inbound / outbound matching chain among the goods attribute information, the storage unit attribute information, and the conveying unit attribute information, determining the recommended goods storage space, the allocated goods conveying subunit, and the allocated goods handling subunit in the goods storage unit allocated to the goods, including at least one of the following: 1) determining a goods conveying subunit and a goods handling subunit with matching volume / load-bearing and a recommended goods storage space with matching volume / load-bearing / height according to the volume / weight of the goods; wherein, the volume / load-bearing of the matching goods conveying subunit and the recommended storage space is positively correlated with the volume / weight of the goods, and the height of the recommended goods storage space is negatively correlated with the volume / weight of the goods; 2) determining a goods conveying subunit and a goods handling subunit that meet the category transportation conditions and a recommended goods storage space in a matching category partition according to the category of the goods; the category transportation conditions include a goods conveying subunit and / or a goods handling subunit with the ability to protect against danger / control temperature for goods with danger / temperature requirements; the category partition is used for cross-contamination isolation / temperature isolation / confusion avoidance between goods with pollution / temperature requirements / similarity; 3) selecting and determining a recommended goods storage space in a matching frequency partition according to the outbound frequency / inbound frequency / shelf life of the goods; wherein, the distance between the location of the recommended goods storage space and the inbound location / outbound location is negatively correlated with the outbound frequency / inbound frequency of the goods and positively correlated with the remaining shelf life of the goods; the height of the recommended goods storage space is negatively correlated with the outbound frequency / inbound frequency of the goods and positively correlated with the remaining shelf life, and is determined by combining and superimposing with the volume / weight.

[0011] In an embodiment of the first aspect, when there are multiple alternative goods storage spaces, the warehouse information processing system is configured to select a recommended goods storage space therefrom with the goal of maximizing the space utilization rate of the goods storage space and minimizing the distance between the goods storage spaces where goods with approximate / related goods attribute information are located.

[0012] In an embodiment of the first aspect, the warehouse information processing system includes: a twin warehouse system obtained by virtualizing the intelligent warehousing system, and the operation data of the twin warehouse system is displayed through an intelligent warehousing visualization graphic interface, where the operation data includes the material information of the goods in the warehouse; the operation state of the twin warehouse system is updated consistently according to the data change of the intelligent warehousing system; the twin warehouse system includes: a twin storage unit corresponding to the goods storage unit, which is used to perform virtual storage actions or virtual retrieval actions of goods; a twin conveying unit corresponding to the goods conveying unit, including: a twin transportation sub-unit for transporting twin goods in the twin warehouse, and a twin handling sub-unit for disposing goods to the twin storage unit; and / or, the intelligent warehousing system further includes a variety of monitoring and sensing devices distributed in the warehouse for collecting monitoring data on the warehouse environment, equipment, and / or goods; the warehouse information processing system is communicatively connected to the variety of monitoring and sensing devices, and integrally displays the monitoring data of the variety of monitoring and sensing devices on the intelligent warehousing visualization graphic interface; the warehouse information processing system is further configured to form and output an alarm message in response to determining the occurrence of an alarm event based on the monitoring data.

[0013] In an embodiment of the first aspect, the warehouse information processing system is configured to obtain historical goods attribute information distribution data based on the historical inventory data of goods, and use a layout time series prediction model to predict the predicted distribution of goods attribute information within a preset time period based on the historical goods attribute information distribution data, so as to obtain a layout plan of the goods storage unit adapted to the warehouse based on the predicted distribution of goods attribute information, and obtain a layout adjustment strategy for the goods storage unit accordingly.

[0014] In an embodiment of the first aspect, the intelligent warehousing system further includes: sorting equipment communicatively connected to the warehouse information processing system; the sorting equipment is configured to collect and identify the image feature information of the goods to be sorted, and use a target recognition model to obtain a sorted target area that matches the classification based on the image feature information and perform sorting; and / or, obtain the goods attribute information of a group of goods to be sorted, and match the clustering results of a group of the goods attribute information to the corresponding sorted target areas corresponding to each preset classification and perform sorting.

[0015] In an embodiment of the first aspect, the warehouse information processing system includes a light-emitting guidance control module, configured to sort a determined set of target light-emitting positioning and guiding devices according to a planned route to obtain a target light-emitting sequence; and, based on the target light-emitting sequence, cause a set of the target light-emitting positioning and guiding devices to emit light in sequence, including: in response to a target positioning terminal completing communication confirmation of a corresponding information set by collecting signal light from a currently emitting target light-emitting positioning and guiding device in the planned route of a transportation task, the currently emitting target light-emitting positioning and guiding device is turned off and the next target light-emitting positioning and guiding device emits light.

[0016] In an embodiment of the first aspect, the warehouse information processing system includes a light-emitting guidance control module, configured to sort a determined set of target light-emitting positioning and guiding devices according to a planned route to obtain a target light-emitting sequence; and, based on the target light-emitting sequence, cause a set of the target light-emitting positioning and guiding devices to emit light simultaneously, including: in response to a communication confirmation based on the information set being completed between a target light-emitting positioning and guiding device in the planned route of a transportation task and a target positioning terminal, the target light-emitting positioning and guiding device that has completed the communication confirmation is turned off.

[0017] In an embodiment of the first aspect, each of the light-emitting positioning and guiding devices includes a guiding lamp and a limiting lamp with different light-emitting characteristics; the warehouse information processing system includes a light-emitting guidance control module, configured to cause the guiding lamps of a set of the target light-emitting positioning and guiding devices to emit light simultaneously or in sequence; wherein, in response to a communication confirmation indication of a route traveling error event between a target light-emitting positioning and guiding device and a target positioning terminal based on the information set, the limiting lamp of the target light-emitting positioning and guiding device emits light in the direction of the traveling error while the guiding lamp does not emit light.

[0018] In an embodiment of the first aspect, the warehouse information processing system is configured to provide a material query graphical interface in response to a user operation, the material query graphical interface including a goods query interface for querying materials and a location guiding control corresponding to the queried goods; in response to the location guiding control receiving a user operation, display a warehouse floor plan including a planned route for guiding to the location where the corresponding goods are located, and instruct a corresponding set of target light-emitting positioning and guiding devices to perform a light-emitting guidance action.

[0019] In an embodiment of the first aspect, the warehouse information processing system is further configured to determine the eligibility of the positioning terminal relative to the collected light-emitting positioning and guiding device according to the signal characteristics of the signal light collected by the light-emitting positioning and guiding device; and, when the positioning terminal is ineligible, refuse to perform the light guiding action; and / or, the warehouse information processing system is integrated with a warehouse management system (WMS) and a warehouse control system (WCS) for communicating with and controlling the goods conveying unit; or, in addition to integrating the warehouse management system (WMS) and the warehouse control system (WCS), the warehouse information processing system is further integrated with at least one of the following: an enterprise resource planning system (ERP); a product life cycle management system (PLM); a manufacturing execution system (MES); and / or, the warehouse information processing system includes a goods image matching module, which is configured to respond to a retrieval request for a goods image including the goods to be retrieved, and match the first image features extracted from the goods image with a preset material image feature library to determine the goods attribute information associated with the second image features that match the first image features to reply to the retrieval request; and / or, the light-emitting positioning and guiding device is implemented as a lighting device.

[0020] The second aspect of the present disclosure provides a warehouse guiding control method, which is applied to the control of a group of light-emitting positioning and guiding devices in a warehouse; the light-emitting positioning and guiding device is used to emit at least one type of signal light to indicate the location; each light-emitting positioning and guiding device has an information set generated based on an associated one light-emitting device identifier, location information, and light-emitting characteristics; the method includes: obtaining the goods attribute information of the goods, and generating the inbound / outbound planning route of the goods based on the destination location corresponding to the goods attribute information; determining a group of target light-emitting positioning and guiding devices according to the matching relationship between the location information of a group of the light-emitting positioning and guiding devices and the planning route, and instructing them to perform the light guiding action.

[0021] The third aspect of the present disclosure provides a computer device, including: a processor and a memory; the memory stores a computer program or instruction; the processor is configured to run the computer program or instruction to execute the warehouse guiding control method as described in any item of the second aspect.

[0022] The fourth aspect of the present disclosure provides a computer-readable storage medium, storing a computer program or instruction, and the computer program or instruction is run to execute the warehouse guiding control method as described in any item of the second aspect.

[0023] The fifth aspect of the present disclosure provides a computer program product, including: a computer program or instruction for executing the warehouse guiding control method as described in any item of the second aspect.

[0024] As described above, the present disclosure relates to intelligent warehousing, and provides an intelligent warehousing system and a warehouse guiding and control method. The system includes: a goods storage unit, a goods conveying unit, a goods sensing unit, a group of light-emitting positioning and guiding devices, a positioning terminal, and a warehouse information processing system communicatively connected to them. The positioning terminal collects signal light for matching with an associated information set to determine the position of the terminal. The warehouse information processing system obtains the goods attribute information of the goods, and generates the inbound / outbound planning route of the goods based on the destination position corresponding to the goods attribute information. Moreover, a group of target light-emitting positioning and guiding devices is determined according to the matching relationship between the position information of the light-emitting positioning and guiding devices and the planning route, and they are instructed to perform light guiding actions. Description of the Drawings

[0025] Figure 1 Showing a schematic structural diagram of the intelligent warehousing system in an embodiment of the present disclosure.

[0026] Figure 2 Showing a schematic diagram of a specific application scenario of the intelligent warehousing system in an embodiment of the present disclosure.

[0027] Figure 3 Showing a schematic communication structure diagram between the warehouse information processing system and the goods conveying unit, the goods sensing unit, etc. in an embodiment of the present disclosure.

[0028] Figure 4 Showing a schematic communication structure diagram of the monitoring and sensing device of the intelligent warehousing system in an embodiment of the present disclosure.

[0029] Figure 5 Showing a schematic software architecture diagram of the intelligent warehousing system in an embodiment of the present disclosure.

[0030] Figure 6 Showing a schematic diagram of the process principle of goods being warehoused in the recommended goods storage space in an embodiment of the present disclosure.

[0031] Figure 7 Showing a schematic diagram of the principle of allocating the recommended goods storage space according to the goods attribute information of the goods in an embodiment of the present disclosure

[0032] Figure 8 Showing a schematic diagram of the principle of searching for materials through image in an embodiment of the present disclosure.

[0033] Figure 9 Showing a schematic diagram of the principle of predicting the warehousing deployment strategy in an embodiment of the present disclosure.

[0034] Figure 10 Showing a schematic diagram of the process of predicting the replenishment time sequence in an embodiment of the present disclosure.

[0035] Figure 11 Showing a schematic diagram of the process of the warehouse guiding and control method in an embodiment of the present disclosure.

[0036] Figure 12 Shows a schematic diagram of the modules of the warehouse guidance control device in the embodiments of the present disclosure.

[0037] Figure 13 Shows a schematic diagram of the structure of a computer device in an embodiment of the present disclosure. Detailed implementation manners

[0038] The following uses specific specific examples to illustrate the implementation manners of the present disclosure. Those skilled in the art can easily understand other advantages and effects of the present disclosure from the information disclosed in the present disclosure. The present disclosure can also be implemented or applied through different specific implementation manners. Various details in the present disclosure can also be modified or changed according to different viewpoints and application manners without departing from the spirit of the present disclosure. It should be noted that, without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other.

[0039] The following takes the accompanying drawings as a reference and details the embodiments of the present disclosure so that those skilled in the technical field to which the present disclosure belongs can easily implement it. The present disclosure can be embodied in many different forms and is not limited to the embodiments described herein.

[0040] In the description of the present disclosure, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics represented in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. Moreover, the specific features, structures, materials, or characteristics represented can be combined in a suitable manner in any one or a group of embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples represented in the present disclosure and the features of the different embodiments or examples.

[0041] In addition, the terms "first" and "second" are only used for indicating purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" can explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "a group" is two or more, unless otherwise specifically defined.

[0042] In order to clearly illustrate the present disclosure, devices irrelevant to the description are omitted, and the same or similar components throughout the specification are given the same reference numerals.

[0043] Throughout the specification, when a device is said to be "connected" to another device, this includes not only the case of "direct connection", but also the case of "indirect connection" in which other elements are placed in between. In addition, when a device is said to "include" a certain component, unless there is a particularly contrary record, it does not exclude other components, but means that other components may also be included.

[0044] Although in some examples the terms first, second, etc. are used herein to denote various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first interface and a second interface, etc. are indicated. Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to also include the plural forms unless the context clearly dictates otherwise. It should be further understood that the terms "comprising", "including" indicate the presence of the stated features, steps, operations, elements, modules, items, kinds, and / or groups, but do not preclude the presence, occurrence or addition of one or more other features, steps, operations, elements, modules, items, kinds, and / or groups. The term "or" and "and / or" used herein are interpreted inclusively, or means any one or any combination. Thus, "A, B or C" or "A, B and / or C" means "any one of the following: A; B; C; A and B; A and C; B and C; A, B and C". An exception to this definition only occurs when the combination of elements, functions, steps or operations are mutually exclusive in some way.

[0045] The technical terms used herein are only for referring to specific embodiments and are not intended to limit the present disclosure. The singular forms used herein also include the plural forms as long as the statements do not clearly indicate the contrary meaning. The meaning of "including" used in the specification is to embody specific characteristics, regions, integers, steps, operations, elements and / or components, and does not exclude the existence or addition of other characteristics, regions, integers, steps, operations, elements and / or components.

[0046] Although not differently defined, including the technical terms and scientific terms used herein, all terms have the same meaning as generally understood by those skilled in the technical field to which the present disclosure pertains. Terms defined in commonly used dictionaries are additionally interpreted to have a meaning consistent with the relevant technical literature and the currently presented information, and should not be over-interpreted as ideal or overly formulaic meanings as long as they are not defined.

[0047] In the current intelligent warehouse technology, although the efficiency of goods operation is improved through automated equipment, data collection, and display, some technologies are still missing in actual scene applications. For example, due to traditional problems or cost issues, many intelligent warehouses still use semi-automatic solutions that combine manual and machine operations. This leads to higher requirements for manual work in many scenarios, affecting the efficiency of goods operation. For example, when querying goods, although the target goods and the warehouse location of the goods can be quickly found based on the goods entry records, for the scenario of manual pickup, if the staff has little experience, they may not clearly understand the warehouse goods storage layout information, and cannot quickly find the target location of the goods. They need to refer to the identification and confirm one by one, which is very inconvenient; by the same token, when storing goods, the staff also needs to find and confirm the target location where the goods need to be placed, which is very inconvenient.

[0048] In addition, even if one is willing to accept higher costs and use fully automated equipment, such as automated guided vehicles (AGVs) and smart stackers to perform unmanned work, taking AGVs as an example, by pre-learning the warehouse terrain and routes, etc., it can automatically deliver goods. However, there are still problems such as limited movement speed, less flexibility than manual labor, easy failure and low reliability, which also affect the efficiency of cargo transportation. In addition, once a failure occurs, temporary manual replacement may still be required, which also means the above problems exist.

[0049] Therefore, how to design a navigation solution that can conveniently guide workers to reach the target location efficiently and quickly, and even better, be compatible with the guidance of AGVs at a lower cost, has become a technical problem that needs to be urgently solved in the industry.

[0050] In view of this, a smart warehousing system is provided in the embodiments of the present disclosure, which effectively improves the operational efficiency of storing / picking up goods by guiding people to the target location through luminous instructions along the planned route.

[0051] like Figure 1 As shown, a schematic diagram of the structure of the smart warehousing system in an embodiment of the present disclosure is shown.

[0052] The described intelligent warehousing system 100 is applied to a warehouse. A warehouse is a transfer center for goods and materials and a distribution center for logistics. The warehouse can be of various types. For example, classified by operation form, it can be divided into private warehouses, commercial warehouses, public warehouses, and strategic reserve warehouses; classified by storage conditions, it can be divided into ordinary warehouses, thermal insulation warehouses (refrigerated, constant temperature and humidity warehouses), special warehouses, and water warehouses; classified by function, it can be divided into storage warehouses, distribution warehouses, distribution centers, and bonded warehouses; classified by different building structures, it can be divided into single-story warehouses, multi-story warehouses, high-rise warehouses, and underground warehouses; classified by the degree of construction, it can be divided into indoor warehouses, open storage yards, sheds, and container warehouses; or, if shelves are used, classified by different shelf structures, it can be divided into pallet racks, drive-in / drive-out racks, narrow aisle racks, gravity racks, push-back racks, medium-sized racks, mezzanine racks, cantilever racks, and automated stereoscopic warehouses. Each type of warehouse has its specific functions and applicable scenarios. In some embodiments, the warehouse in the embodiments of the present disclosure can be a port warehouse, which docks the goods transmitted by logistics vessels.

[0053] The described intelligent warehousing system 100 includes: a goods storage unit 101, a goods conveying unit 102, a goods sensing unit 103, a group of light-emitting positioning and guiding devices 104, a positioning terminal 105, and a warehouse information processing system 106.

[0054] In some embodiments, in order to track each piece of goods, an asset tag containing its goods attribute information and capable of being externally read is added to the goods when they are warehoused. For example, information pattern tags such as two-dimensional codes and barcodes, or electronic tags such as RFID, Bluetooth (such as Beacon), and ultra-wideband (UWB). RFID is a relatively commonly used asset tag. RFID tags are generally classified according to the power supply method into: passive RFID and active RFID. In actual applications, passive RFID is divided into low frequency, high frequency, and ultra-high frequency. Combined with the reader, its reading distance ranges from a few centimeters to dozens of meters; while the reading distance of active RFID can reach more than 100 meters. Passive RFID tags are made of flexible printed circuits, and have the characteristics of small size, light weight, and can be embedded in products, etc., and can be perfectly integrated into traditional physical assets. In some alternative embodiments, the asset tag can also be integrated with communication circuits such as WiFi, Bluetooth, or the Internet of Things, and is wirelessly connected to the warehouse information processing system 106 through wireless network communication.

[0055] In some embodiments, the goods attribute information includes, but is not limited to, various combinations of identification numbers (such as ID) assigned when the goods are warehoused, name, specifications, model, material, quantity, weight, volume, use, production date, shelf life, place of origin, manufacturer, etc. It should be noted that when the goods are warehoused and informatized, they are transformed into the role of "materials" or "goods" from the perspective of the warehouse.

[0056] The goods storage unit 101 has a goods storage space. The goods storage unit 101 may include an exposed storage area for placing goods or shelves, etc. Correspondingly, for different implementation forms, the position of the goods storage space also changes accordingly. For example, the space where the open storage area is located is the goods storage space, and each bin in the shelf is the goods storage space. In some embodiments, the goods storage unit 101 includes a shelf. In order to accurately obtain information about each goods storage and retrieval action, the shelf can be configured with the ability to sense goods (including collecting goods attribute information from tags). Therefore, in some embodiments, the shelf can be implemented as an RFID intelligent shelf. The intelligent shelf can be provided with RFID readers on each layer of bins. When goods enter / exit the bin, it can sense the RFID tags on the goods and collect the goods attribute information, so as to determine the identity of the goods and the occurrence of the event of entering or leaving the warehouse. In a further example, sensors for sensing the presence of goods, such as infrared sensors, pressure sensors, etc., can also be provided in the bin. In other embodiments, goods monitoring and information collection can also be completed through vision technology. For example, a goods image can be captured by a vision sensor (which can be an ordinary vision sensor or a depth vision sensor), and the goods attribute information can be obtained according to the pattern tags (such as two-dimensional codes, barcodes) in the image, or the corresponding goods attribute information can be obtained by performing image recognition on the captured goods image to determine the matching materials.

[0057] The goods conveying unit 102 is used for transporting and handling goods in the warehouse. Specifically, the goods conveying unit 102 includes a goods transporting subunit for transporting goods in the warehouse and a goods handling subunit for disposing of goods to the goods storage unit 101. In some embodiments, the goods transporting subunit and the goods handling subunit can be implemented by automated equipment or by manual labor. The automated equipment can include intelligent robots. As an example, the goods transporting subunit can include load-carrying walking conveying equipment such as an automated guided vehicle (AGV), an intelligent forklift, a drone, a chain conveying mechanism, etc. The goods handling subunit can include a warehousing and outwarehousing mechanism (such as a shelf robot, such as a Cartesian coordinate robot, etc.) arranged adjacent to the goods storage unit 101, and intelligent handling equipment (such as a stacker, etc.).

[0058] The goods sensing unit 103 is at least disposed at the inbound position, the outbound position, and the goods storage unit 101, and is used to sense goods and collect goods attribute information. In some embodiments, RFID tags are provided on the corresponding goods, and the goods sensing unit 103 may include RFID readers disposed at the inbound position and the outbound position, and is used to determine the inbound and outbound actions of the goods. And / or, corresponding to the RFID intelligent shelf, the goods sensing unit 103 may include RFID readers disposed on the shelf. Of course, the goods sensing unit 103 may further include sensors such as vision sensors, radars, or other sensors capable of collecting goods attribute information, or may also be other readers for wirelessly sensing and extracting information, such as Bluetooth, UWB, NFC, etc., not limited to RFID.

[0059] In addition, in some embodiments, the goods sensing unit 103 may also be deployed at other sensing positions in the warehouse to sense goods and determine the progress of goods turnover. For example, by being disposed in the inventory area to determine whether the goods inventory is completed, or being disposed in the quality inspection area to determine whether the goods quality inspection is completed, etc.

[0060] The group of light-emitting positioning and guiding devices 104 are distributed in the warehouse and are used to emit at least one type of signal light to indicate the location. Each of the light-emitting positioning and guiding devices 104 has an information set generated based on an associated light-emitting device identifier, location information, and light-emitting characteristics, for performing optical communication with the outside to determine the location based on the information set. The signal lights of the light-emitting positioning and guiding devices 104 have different light-emitting characteristics from each other. The group of light-emitting positioning and guiding devices 104 is used to provide a set of target light-emitting positioning and guiding devices 104 for performing a light-emitting guiding action corresponding to the current planned route.

[0061] In some embodiments, the light-emitting positioning and guiding device 104 may be disposed in the goods storage unit 101. For example, it is disposed corresponding to each shelf, the storage location on the shelf, or the open storage area, and may be specifically implemented as an indicator light, etc., and is used to indicate the shelf, the storage location on the shelf, or the open storage area as the target to be searched when lit. In other embodiments, the light-emitting positioning and guiding device 104 may further include indicator lights arranged along the planned route, or may also be lighting fixtures, and is used to guide users or goods transportation devices with visual recognition capabilities to efficiently find the target shelf, the storage location on the shelf, or the open storage area.

[0062] In some embodiments, the light-emitting features include, but are not limited to, one or more combinations of light-emitting frequency, light-emitting intensity, light-emitting color, or other features. By aggregating the information sets of each light-emitting device identifier, location information, and light-emitting features, the matching based on the information sets can be uniquely associated with the corresponding light-emitting positioning and guiding device 104. In some embodiments, a "fingerprint" uniquely corresponding to each light-emitting positioning and guiding device 104 can be generated according to the information sets for matching use.

[0063] The positioning terminal 105 can be carried and moved by the goods conveying unit 102 or the staff, and is used to collect the signal light for matching the information sets associated according to the signal light to determine the location of the terminal. In some embodiments, the positioning terminal 105 can be configured with a visual sensor or an image collector, and matches with each information set by sensing the light-emitting features of the signal light change to determine the matching light-emitting positioning and guiding device 104, so as to determine the location of the positioning terminal 105. In some examples, the distance can also be determined according to the information related to the distance between the positioning terminal 105 and the matching light-emitting positioning and guiding device 104 (such as light intensity, etc.) to obtain a more accurate positioning result. Since the space of the shelf aisle is limited, rough positioning is performed according to the matching light-emitting positioning and guiding device 104, and combined with the distance, a valuable positioning result can be provided even when the relative orientation is not determined. As an example, the positioning terminal 105 can also be integrated with a GPS module to report the location in real time. And / or, as an example, the goods transportation sub-unit (such as an AGV, etc.) can also be integrated with a GPS module to report the location in real time.

[0064] In some embodiments, there can be multiple positioning terminals 105, and each positioning terminal 105 can have a unique terminal ID. When establishing the task of placing goods in the warehouse or taking out goods from the warehouse, the task ID of each positioning terminal 105 can be associated with the terminal ID to track the task completion progress of the staff or AGV, etc. carrying the positioning terminal 105.

[0065] The warehouse information processing system 106 has the capabilities of data processing and control, and can be used for information processing, control, management, scheduling, etc. of various parts in the warehouse. The warehouse information processing system 106 is communicatively connected to the goods conveying unit 102, the goods sensing unit 103, each of the light-emitting positioning and guiding devices 104, and the positioning terminal 105, and is used to obtain the goods attribute information of the goods, and generate the in / out warehouse planning route of the goods based on the destination location corresponding to the goods attribute information. And, determine a group of target light-emitting positioning and guiding devices 104 according to the matching relationship between the location information of a group of the light-emitting positioning and guiding devices 104 and the planning route, and instruct them to perform the light-emitting guiding action.

[0066] In some embodiments, when goods are stored at the storage location in the warehouse, the corresponding storage space for the goods can be determined according to the goods attribute information, and a planned route is formed with it as the destination. Thus, the goods conveying unit 102 conveys the goods to the goods storage space according to the planned route. When the goods are taken out of the warehouse, the goods storage space where the goods are located is determined, and a route is planned with the warehouse's outbound location as the destination. The goods conveying unit 102 takes out the goods from the goods storage space and transports them to the outbound location according to the planned route. Alternatively, a route is planned according to other tasks. After determining the planned route, a set of target light-emitting positioning devices can be determined to perform the light-emitting guiding action.

[0067] In some embodiments, the matching relationship between the planned route and the light-emitting positioning guiding device 104 may include a position attribution relationship or a spacing relationship. Thus, the target light-emitting positioning guiding device 104 along the route is selected. For example, each section passed by the planned route is determined, and the target light-emitting positioning guiding device 104 is determined according to the pre-determined attribution relationship of the light-emitting positioning guiding device 104 belonging to the section. Another example is that the light-emitting positioning guiding device 104 with a spacing less than a certain preset threshold from each point on the route is determined as the target light-emitting positioning guiding device 104, etc., and this is not limited thereto.

[0068] In some embodiments, when multiple positioning terminals 105 perform tasks simultaneously according to their respective planned routes, the target light-emitting positioning guiding device 104 corresponding to the overlapping sections in the multiple planned routes can be shared.

[0069] In some embodiments, the positioning terminal 105 can send the image of the collected signal light to the warehouse information processing system 106, so that the warehouse information processing system 106 extracts features according to the collected signal light and matches the light-emitting positioning guiding device 104 with the information set library, determines the position of the terminal, and can feedback it to the positioning terminal 105, so that the positioning terminal 105 feeds it back to the user in the form of images or text (a display needs to be configured), voice (a speaker needs to be configured), etc.; preferably, the dynamic virtual planned route is displayed on the electronic map, and the current position on the planned route is mapped to the corresponding point in the virtual planned route to intuitively feedback the traveling situation to the user. Alternatively, in other embodiments, if the positioning terminal 105 is configured with sufficient processing power and storage capacity, the above information processing process of positioning can also be completed by the positioning terminal 105 itself.

[0070] In some embodiments, the warehouse information processing system 106 may be integrated with a Warehouse Management System (WMS) and a Warehouse Control System (WCS) for communicating with and controlling the goods conveying unit 102. Alternatively, in the scenarios of enterprise sales, production, and manufacturing, in addition to being integrated with a Warehouse Management System (WMS) and a Warehouse Control System (WCS), the warehouse information processing system 106 is further integrated with at least one of the following: Enterprise Resource Planning System (ERP); Product Lifecycle Management System (PLM); Manufacturing Execution System (MES). Among them, WMS is a software system dedicated to warehouse operation management. WMS utilizes information technology to precisely control and efficiently manage the storage, inventory count, and inbound and outbound operations (including processes such as receiving, shelving, picking, packaging, and shipping) of goods in the warehouse. At the same time, it can also effectively allocate and schedule resources such as the space, equipment, and manpower of the warehouse to improve the overall operation efficiency of the warehouse, reduce costs, and ensure the accuracy of inventory data. WCS is used to control the real-time activities of the goods conveying unit 102. WCS is responsible for the operation of the goods transportation and handling sub-units, and usually also the activities of the warehouse employees themselves. The Warehouse Control System (WCS) is integrated with WMS to provide an additional control and functional layer. It is specifically designed to control any automation technology or equipment within the facility, such as conveyors, sorters, automated warehouses, etc. PLM is an application solution that creates, manages, distributes, and applies information throughout the product life cycle among enterprises located at a single location, enterprises scattered at multiple locations, and enterprises with a collaborative relationship in the field of product R & D within an enterprise. MES is an integrated operating system that manages and optimizes the entire production and manufacturing process of an enterprise. It optimizes the management of the entire product production process from order release to product completion, promptly reacts and reports real-time events in the factory, and uses current accurate data for guidance and processing. It is an industrial software that can achieve top-down, refined, and collaborative management.

[0071] In some embodiments, the above-mentioned "communication connection" may include a wired connection (such as a network cable, fiber optic connection), or may also include a wireless communication connection (such as WiFi, Bluetooth, NB-IOT, Lora, etc.).

[0072] Reference Figure 2 As shown, it presents a schematic diagram of the specific application scenario of the intelligent warehousing system 100 in the embodiments of the present disclosure.

[0073] Taking an RFID tag as an example, when the goods with the RFID tag arrive at the warehouse inbound location, the RFID reader at the inbound location reads the goods attribute information in the RFID tag on the goods, and immediately sends this information to the warehouse information processing system 106. The WMS in the warehouse information processing system 106 forms an inbound record, and can select the most suitable recommended goods storage space according to the goods attribute information. The WMS sends an instruction to the WCS to indicate the planned path A. The WCS sends an instruction to the goods transportation subunit (such as an AGV), so that the goods transportation subunit transports the goods to the location of the recommended goods storage space in the goods storage unit 101 according to the planned path, and hands it over to the goods handling subunit to store the goods. The WMS updates the goods storage record. When the goods are out of the warehouse, the WMS orders the WCS to control the goods transportation subunit to go to the goods storage space where the goods are located, the goods handling subunit takes out the goods, and orders the goods transportation subunit to carry the goods to the outbound location according to the planned path B for outbound operation. The WMS updates the outbound record. During the movement of the goods transportation subunit along the planned paths A and B, the WMS can select a group of target light-emitting positioning guiding devices 104 that match it to emit light. If the goods transportation subunit is implemented as an unmanned AGV and it carries the positioning terminal 105, it can sense the signal light of the target light-emitting positioning guiding device 104 according to vision, and determine each target light-emitting positioning guiding device 104 along the way according to the light-emitting feature matching information set of the signal light, so as to determine its own location information and can inform the WCS or WMS to obtain real-time updates of the location of the unmanned AGV. Alternatively, when the goods transportation subunit is implemented as a staff member and it carries the positioning terminal 105, it can navigate according to the feature matching of the signal light, or can also travel to the destination by visually observing the lit target light-emitting positioning guiding devices 104.

[0074] Therefore, it can be seen that in the embodiment of the present disclosure, by determining a group of target light-emitting positioning guiding devices with unique light-emitting features respectively according to the planned route for light-emitting guidance, and cooperating with the positioning terminal 105 that can collect signal light for identifying the light-emitting features and is carried by the goods transportation unit 102 or the staff member, the route guidance requirements for manned and unmanned goods transportation in the warehouse can be accurately and well compatible, and the problems existing in the related art can be well solved.

[0075] As Figure 3 shown, it shows a schematic communication structure diagram between the warehouse information processing system 106 and the goods transportation unit 102, the goods sensing unit 103, etc. in an embodiment of the present disclosure.

[0076] In Figure 3In the embodiment, the warehouse information processing system 106 includes a WMS and a WCS, and the WMS is communicatively connected to the WCS. The WMS and the WCS can be integrated. The device (computer device) where the WCS is located is communicatively connected to the wireless routing node 107 through a routing device such as a switch or a router or by direct connection through a line. The goods conveying unit 102 includes an AGV and an intelligent stacker, and is wirelessly communicatively connected to the wireless routing node to form a wireless communication path between the WMS, the WCS and the goods conveying unit 102.

[0077] Optionally, the WMS can also be wirelessly communicatively connected to at least one of the light-emitting positioning and guiding devices 104, asset tags, positioning terminals 105, etc. through the wireless routing node.

[0078] In some embodiments, the intelligent warehousing system 100 further includes a variety of monitoring and sensing devices distributed in the warehouse for collecting monitoring data on the warehouse environment, equipment, and / or goods. As an example, the variety of monitoring and sensing devices may include any combination of temperature / humidity sensors, gas sensors, smoke / fire sensors, water immersion sensors, vibration sensors, air quality sensors, visual sensors (such as cameras, lidar, etc.). Among them, the temperature / humidity sensor is used to monitor the temperature / humidity conditions in the warehouse environment; the gas sensor is used to monitor the concentration of harmful gases in the warehouse; the smoke / fire sensor is used to monitor the smoke and fire signs in the warehouse; the water immersion sensor is used to monitor the water leakage and flooding conditions in the warehouse; the vibration sensor is used to monitor the health conditions of the equipment (such as shelves, AGVs, etc.) and / or building structures in the warehouse; the air quality sensor is used to monitor the air pollution conditions in the warehouse. By collecting the operation data of various objects in the warehouse through a variety of monitoring and sensing devices and displaying them in an integrated and fused manner, it is beneficial for the staff to efficiently and comprehensively monitor the operation of the warehouse and obtain timely feedback and alarm information.

[0079] As Figure 4 shown, a schematic diagram of the communication structure of the monitoring and sensing devices of the intelligent warehousing system in the embodiment of the present disclosure is shown.

[0080] In Figure 4In the embodiments, a schematic diagram of an application scenario of a warehouse including multiple storerooms is shown. As an example, different monitoring and sensing devices may be set in multiple storerooms according to different uses or different security prevention requirements. For example, storeroom 1 is used for storing grains and requires monitoring of environmental temperature and humidity, so multiple temperature and humidity sensors are set. Storeroom 2 and storeroom 3 need to be particularly guarded against water leakage and fire, so smoke / fire sensors and water immersion sensors are set. Optionally, in the case where the sensing signals output by some types of monitoring and sensing devices are analog signals, an analog-to-digital (AD) converter can be connected to convert them into digital signals for transmission. The warehouse information processing system 106 may further include a monitoring terminal 161, and the monitoring terminal 161 is communicatively connected to each of the monitoring and sensing devices to collect monitoring data. The monitoring terminal 161 may include a display screen for displaying the monitoring data through a graphical user interface, and preferably, multiple types of monitoring data can be integrally displayed.

[0081] Thus, in a specific scenario, by connecting sensors, RFID tags, GPS, etc. to the warehouse information processing system 106 through a network, real-time monitoring and management of the warehouse environment, equipment, and goods are realized.

[0082] As Figure 5 shown, a schematic diagram of the software architecture of the intelligent warehousing system in the embodiments of the present disclosure is shown.

[0083] In Figure 5 it, the software architecture is built on the hardware layer. The hardware layer includes various entity objects, such as goods, asset tags, shelves included in the goods storage unit 101, tag readers included in the goods sensing unit 103, light-emitting positioning and guiding devices 104, positioning terminals 105, monitoring and sensing devices (i.e., sensors), etc. The software architecture includes a multi-layer structure, a data interface layer, and an application layer. The data interface layer provides data material interfaces, inbound data interfaces, outbound data interfaces, inventory data interfaces, etc. Among them, the material interface can be used for input / output / editing of goods material data, the inbound interface is used for performing inbound operations to form inbound records and inbound record queries, the outbound interface is used for performing outbound operations to form outbound records and outbound record queries, and the inventory interface is used for querying / editing of inventory records.

[0084] The application layer includes basic data applications (examples include management of basic data related to warehouses, materials, storage locations, label printing, etc.), inbound management (examples include management of purchase orders, inspection sheets, receiving sheets, inbound sheets, etc.), outbound management (examples include management of material requisition sheets, outbound sheets, return material sheets, etc.), storage location management (examples include management of transfers, shelving, inventory counts, adjustments, etc.), equipment management (examples include management of equipment in part or all of the hardware layer)

[0085] Based on the warehouse information processing system 106 in the above embodiments, intelligent functions such as automated storage and retrieval of goods, optimizing the transfer efficiency and reliability of goods in the warehouse using AI, big data analysis and prediction related to goods, visual digital twin warehouse, and comprehensive security monitoring can be realized, effectively improving the intelligence, operation efficiency, and stability of the intelligent warehousing system. The following will be illustrated one by one.

[0086]

Automated Access and Retrieval of Goods

[0087] In some embodiments, goods may be diverse, that is, the types may be different. Among the various information dimensions of the goods attribute information, the goods type is related to the name, specification, model, material, volume, weight, use, etc. Taking a port warehouse as an example, common goods types can include rolling goods such as trucks, buses, trailers, motorcycles, and engineering vehicles; general cargo, including small machinery, construction equipment, furniture, generators, large artworks, etc.; dry bulk cargo, including metal minerals, rapeseed, grains, etc.; liquid bulk cargo, including vegetable oil, essential oil, chemicals, rubber, etc.; containerized goods, etc.

[0088] Different types of goods have different requirements for the goods storage space, such as volume requirements, load-bearing requirements, temperature control requirements for refrigeration / heating, pollution isolation, etc. Therefore, when allocating the goods storage space, the corresponding requirements of the goods need to be met. The traditional allocation method is manual judgment and recommendation. In the case of a warehouse with a large number of goods storage spaces, manual judgment is very inefficient and inaccurate. Therefore, in the embodiments of the present disclosure, the warehouse information processing system 106 may include a recommended storage location module for recommending a suitable storage space for incoming goods.

[0089] In some embodiments, refer to Figure 6As shown in the figure, it is a schematic diagram of the process principle of a goods entering the warehouse in a recommended goods storage space in an embodiment of the present disclosure. The recommended goods location module can be used to respond to the generation of a warehousing record of the goods, determine a matching recommended goods storage space in the goods storage unit 101 according to the goods attribute information of the goods, and perform a virtual storage action of storing the goods in the virtual recommended space corresponding to the recommended goods storage space to obtain a virtual warehousing record. And, when the actual storage action of the goods is performed, the corresponding recommended storage space is determined based on the virtual storage space of the virtual warehousing record, and an actual warehousing record is formed in response to the completion of the actual storage action. For example, when the goods are warehoused, the recommended goods location module can first allocate a virtual recommended space corresponding to an actual recommended goods storage space according to the goods attribute information, and form a virtual warehousing record that locks the recommended goods storage space and prevents other goods from using it by performing a virtual storage action of storing the goods in the virtual recommended space; then, when the goods are actually warehoused, the virtual warehousing record can be called to query the recommended storage space where the goods actually need to be stored, and the actual warehousing action of the goods can be completed accordingly. Thus, by immediately allocating and locking a suitable recommended goods storage space for the goods before actual warehousing, the inefficient consequence that the recommended goods storage spaces of the goods are occupied by each other and need to be repeatedly allocated can be avoided.

[0090] As Figure 7 shown, the principle of allocating the recommended goods storage space according to the goods attribute information of the goods is specifically described. The goods storage unit 101 has storage unit attribute information, and the goods conveying unit 102 has conveying unit attribute information; determining the matching recommended goods storage space according to the goods attribute information of the goods includes: based on the establishment of an inbound / outbound matching chain among the goods attribute information, the storage unit attribute information, and the conveying unit attribute information, determining the recommended goods storage space, the allocated goods transportation sub-unit, and the allocated goods handling sub-unit in the goods storage unit 101 corresponding to the goods. The "inbound / outbound matching chain" refers to "Commodity Category - Assigned Goods Transportation Sub - unit and Goods Handling Sub - unit - Assigned Recommended Goods Storage Space...” the chain matching between the units required to be allocated in each link of the inbound / outbound process and the goods categories among

[0091] 1) Determine the goods transportation sub-unit and the goods handling sub-unit with matching volume / load-bearing and the recommended goods storage space with matching volume / load-bearing / height according to the volume / weight of the goods; among them, the volume / load-bearing of the matching goods transportation sub-unit and the recommended goods storage space is positively correlated with the volume / weight of the goods, and the height of the recommended goods storage space is negatively correlated with the volume / weight of the goods.

[0092] Specifically, the heavier and / or larger the goods are, the higher the load-bearing requirement for the recommended storage space, the larger the volume should be, and the lower the height should be for easy access. Correspondingly, the AGV, intelligent stacker, etc. used to transport the goods also need to have a matching volume / load-bearing capacity.

[0093] 2) Determine the recommended goods storage space for the category partition that matches the goods transportation sub-unit and goods handling sub-unit that meet the category transportation conditions according to the category of the goods; the category transportation conditions include the goods transportation sub-unit and / or goods handling sub-unit with the ability to protect against danger / control temperature for goods with danger / temperature requirements; the category partition is used for cross-contamination isolation / temperature isolation / avoidance of confusion between goods with pollution / temperature requirements / similarity.

[0094] Specifically, the category can be characterized and distinguished by one or more of the specifications, models, and names. For polluting goods, which need to be stored and transported separately, the corresponding recommended goods storage space, goods transportation sub-unit, goods handling sub-unit, etc. also need the ability to protect against danger with safe isolation. Similarly, in the case of goods with temperature control requirements such as refrigeration, the recommended goods storage space, goods transportation sub-unit, and / or goods handling sub-unit also need to have the corresponding refrigeration configuration. In addition, similar goods such as different models of screws also need to be transported and stored separately to avoid confusion.

[0095] 3) Select and determine the recommended goods storage space for the frequency partition that matches according to the outbound frequency / inbound frequency / shelf life of the goods; among them, the distance between the location of the recommended goods storage space and the inbound location / outbound location is negatively correlated with the outbound frequency / inbound frequency of the goods and positively correlated with the remaining shelf life of the goods; the height of the recommended goods storage space is negatively correlated with the outbound frequency / inbound frequency of the goods and positively correlated with the remaining shelf life, and is determined by combining and superimposing the volume / weight.

[0096] Specifically, the outbound frequency / inbound frequency of the goods is related to their category. For example, the inbound and outbound frequency of hot-selling or short-shelf-life goods is high, while the opposite is low. The higher the outbound frequency / inbound frequency, the closer it is to the inbound location / outbound location for convenient and efficient access; conversely, the farther it is from the inbound location / outbound location and deeper in the warehouse. Moreover, the higher the outbound frequency / inbound frequency, the lower the storage height for easy access; conversely, the higher the storage height. Of course, the storage height also needs to consider the volume / weight in 1), so the two need to be considered comprehensively. For example, for hot-selling goods with a small volume, according to the outbound frequency / inbound frequency, they need to be stored lower, but considering the volume, they need to be stored higher, and the two can offset each other to choose a moderate height position.

[0097] Of course, in other embodiments, it is also possible to match the storage unit attribute information and the conveying unit attribute information. For example, the distance between the shelf / floor storage area and the current position of the goods transportation subunit (such as AGV, staff) is too far, then it is not selected, etc.

[0098] In a further alternative embodiment, when selecting a recommended storage space for a piece of goods, there may be multiple alternative goods storage spaces that meet the requirements. In one implementation, multiple alternative goods storage spaces can be recommended to the user for selection. In another implementation, the optimal recommended goods storage space can be automatically determined from multiple alternative spaces. For example, the warehouse information processing system 106 is used to select the recommended goods storage space with the goal of maximizing the space utilization rate of the goods storage space and minimizing the distance between the goods storage spaces where the goods with approximate / related goods attribute information are located. Specifically, we hope that the volume of the recommended goods storage space exactly meets the volume of the goods, without much volume surplus. Otherwise, a recommended goods storage space that could have been used for larger-sized goods is occupied by smaller-sized goods, resulting in space waste. Therefore, the higher the space utilization rate of the recommended goods storage space, the better. On the other hand, goods with approximate / related goods attribute information may be used in similar shipping tasks. For example, different models of screws are approximate, and two goods sold in a bundle are related. A relationship table can be pre-established for various goods between their models, specifications, and their approximate / related degrees (which can be mapped to scoring values, and the level of the values represents the degree). Then, the more concentrated the classification of goods with approximate / related attributes, the easier it is to pick up and place them together on the shelf or the ground, thereby improving the in / out warehouse efficiency, and the goods are arranged more neatly on the shelf or the ground, which is also convenient for searching. Therefore, with the goal of maximizing the space utilization rate and minimizing the distance between similar goods (of course, constraints will also be imposed, and similar goods cannot be in the same goods storage space, such as in the same warehouse location), the final recommended goods storage space is selected from multiple alternative recommended goods storage spaces. In an alternative example, weights can be set for the two considerations of maximizing the space utilization rate and minimizing the distance between similar goods (the sum of the weights is 1), forming an objective function for calculating the weighted sum, and by trying the scores of each alternative goods storage space in the objective function, and then comparing the scores, the one with the highest score is the final recommended goods storage space.

[0099] It can be understood that the above algorithm for selecting the recommended goods storage space is just an example. In the actual scenario, only some of the factors may be considered, such as only using the selection method of "in / out warehouse matching chain" and considering the space utilization rate to determine the recommended goods storage space, or only using the selection method of "in / out warehouse matching chain" and allowing the user to select or randomly select the recommended goods storage space from multiple alternative goods storage spaces.

[0100] In the previous embodiments, the use of the light-emitting positioning guiding device 104 for positioning has been introduced, and the device or user is guided to travel along the planned route by determining a set of target light-emitting positioning guiding devices 104. In some embodiments, the light-emitting mode of a set of target light-emitting positioning guiding devices 104 can be designed to help the user efficiently and correctly complete the travel along the planned route. In some embodiments, the shortest path algorithm can be used to form the planned path to obtain an optimal and efficient planned path to improve the efficiency as much as possible. As an example, the shortest path algorithm may include, for example, Dijkstra algorithm, Floyd-Warshall algorithm, A* search algorithm or Johnson algorithm. The Dijkstra algorithm is an algorithm for finding the shortest path from a single source point to all other points in a weighted graph; it is applicable to the case where the weights of the edges are non-negative; in a specific implementation, a priority queue (such as a min heap) is used to optimize the selection of the next node to be visited, ensuring that the node selected each time is the node with the smallest known distance currently. The Bellman-Ford algorithm can handle graphs containing negative-weight edges and can detect whether there are negative-weight cycles in the graph. It is applicable to all types of edge weights (including negative numbers); in a specific implementation, through multiple iterations, the shortest path estimate values of all vertices to the source point are continuously updated until no change occurs or the maximum number of iterations is reached. The A* search algorithm is a heuristic search algorithm for finding the shortest path from a certain vertex of a graph to another vertex. It combines the ideas of the Dijkstra algorithm and best-first search, and uses a heuristic function to estimate the cost from the current node to the target node. In a specific implementation, it is similar to the Dijkstra algorithm, but uses a heuristic function (such as Euclidean distance) to estimate the cost from the current node to the target node. The Johnson algorithm is a method based on the Bellman-Ford algorithm for calculating the shortest paths between all vertex pairs in a weighted graph. It first uses the Bellman-Ford algorithm to re-weight the graph so that the weights of all edges become non-negative, and then uses the Dijkstra algorithm to calculate the shortest paths in the new graph; in a specific implementation, the original graph is first processed for re-edge weighting, and then the Dijkstra algorithm is applied to each vertex.

[0101] In some embodiments, the warehouse information processing system 106 includes a light-emitting guiding control module, which is configured to sort a determined set of target light-emitting positioning guiding devices 104 according to a planned route to obtain a target light-emitting sequence, and cause a set of the target light-emitting positioning guiding devices 104 to emit light in sequence based on the target light-emitting sequence, including: in response to a target positioning terminal 105 in a planned route of a transportation task completing communication confirmation of a corresponding information set through signal light collected from a currently light-emitting target light-emitting positioning guiding device 104, the currently light-emitting target light-emitting positioning guiding device 104 is turned off and the next target light-emitting positioning guiding device 104 emits light. For example, a set of target light-emitting positioning guiding devices 104 is determined, and their IDs are sorted according to the planned route to obtain a target light-emitting sequence {ID2, ID3, ID1, ID4, ID5}, hereinafter referred to as IDx devices. The corresponding IDx devices are lit in sequence according to this sequence. After ID2 is lit, when the light-emitting characteristics of the signal light collected by the positioning terminal 105 indicate that it is at the ID2 device, the ID2 device is turned off and the ID3 device is lit, and so on, until the ID5 device is lit and then turned off, indicating that the positioning terminal 105 has reached the ID5 device, and thus the planned route is completed.

[0102] Alternatively, in some other embodiments, after sorting a determined set of target light-emitting positioning guiding devices 104 according to a planned route to obtain a target light-emitting sequence, the light-emitting guiding control module may also cause a set of the target light-emitting positioning guiding devices 104 to emit light simultaneously, including: in response to completing communication confirmation based on the information set between a target light-emitting positioning guiding device 104 and a target positioning terminal 105 in a planned route of a transportation task, the target light-emitting positioning guiding device 104 that has completed the communication confirmation is turned off. For example, a set of target light-emitting positioning guiding devices 104 is determined, and their IDs are sorted according to the planned route to obtain a target light-emitting sequence {ID2, ID3, ID1, ID4, ID5}, hereinafter referred to as IDx devices, and ID2, ID3, ID1, ID4, and ID5 are all lit. When the light-emitting characteristics of the signal light collected by the positioning terminal 105 indicate that it is at the ID2 device, the ID2 device is turned off; when it is at the ID3 device, the ID3 device is turned off... and so on, until all the IDx devices are turned off.

[0103] In some embodiments, each of the light-emitting positioning guiding devices 104 may include multiple types of lamps with different light-emitting characteristics, such as guiding lamps and restricting lamps. Different light-emitting characteristics may include different colors or different characteristic frequencies, etc. Based on the above examples, the light-emitting guiding control module can be used to make the guiding lamps of a group of the target light-emitting positioning guiding devices 104 emit light simultaneously or sequentially; and, by configuring guiding lamps and restricting lamps for the light-emitting positioning guiding devices 104, when a communication confirmation indicating a route traveling error event occurs between a target light-emitting positioning guiding device 104 and a target positioning terminal 105 based on the information set, the restricting lamps of the target light-emitting positioning guiding device 104 can form light emission in the wrong traveling direction while the guiding lamps do not emit light. As an example, User 1 travels along the planned route according to the target light-emitting sequence {ID2, ID3, ID1, ID4, ID5}, and User 2 travels along the planned route according to {ID7, ID6, ID1, ID4, ID8}. The guiding lamps and restricting lamps may have different colors, such as green and red. When User 1 goes wrong to the ID7 device, the positioning terminal 105 of User 1 collects the signal light of the ID7 device and feeds it back to the warehouse information processing system 106. The warehouse information processing system 106 determines that User 1 is located at the ID7 device and there is a traveling error, and can control the restricting lamp of the ID7 device to light up to indicate that User 1 is restricted from traveling; if User 2 travels normally, the guiding lamp of the ID7 device can be lit normally. When it is determined that User 1 leaves the ID7 device, the restricting lamp of the ID7 device is extinguished. Thus, when a small number of users travel in parallel, it is possible to prevent the users from deviating too far from the original route.

[0104] In some embodiments, there may be multiple positioning terminals 105. For each task, there should be a predetermined positioning terminal 105, that is, a positioning terminal 105 that is "qualified" relative to this task; if a certain positioning terminal 105 is not assigned a task, that is, there is no qualification relative to the light-emitting positioning guiding device 104, then when it acquires signal light and attempts to light up the light-emitting positioning guiding device 104 through the enterprise information processing system, it can be identified as unqualified and the light-emitting positioning guiding device 104 will not be lit. Also, when the positioning terminal 105 is unqualified, it refuses to execute the light-emitting guiding action. In some embodiments, the matching authentication of whether a certain current positioning terminal 105 ID is qualified can be achieved by binding the ID of the qualified positioning terminal 105 and the target light-emitting sequence planned for the corresponding assigned task. If it is found through matching that the current positioning terminal 105 ID is not bound to the target light-emitting sequence or is different from the qualified target light-emitting sequence, then it is unqualified.

[0105] In some embodiments, the warehouse information processing system 106 may be connected to a user terminal including a display (such as a desktop computer, a laptop computer, a tablet computer, a smart phone, etc.), and display a graphical interface with various data in the intelligent warehouse system through the display to present the overall warehouse operation status to the user. For example, it can display queries such as the location of goods, in / out warehouse data, inventory data, topographic floor plans, AGV locations and working status, etc.

[0106] As an example, the warehouse information processing system 106 is configured to provide a material query graphical interface in response to a user operation. The material query graphical interface includes a goods query interface for querying materials and a location guidance control corresponding to the queried goods. For example, the goods query interface may include a field for inputting goods information, a button for clicking to start the query, etc. The location guidance control may be a "location query" button corresponding to the queried goods. When the location guidance control accepts a user operation (such as being clicked), a warehouse floor plan including a planned route leading to the location of the corresponding goods may be displayed on the material query graphical interface, and a corresponding group of target light-emitting positioning and guiding devices 104 may be instructed to perform a light-emitting guiding action. Thus, the user can efficiently complete the required goods query and route planning for the corresponding location through the material query graphical interface.

[0107] In some embodiments, the warehouse information processing system 106 may also support the function of searching for goods by image. Figure 8The implementation principle is shown in . The warehouse information processing system 106 includes a goods image matching module. The goods image matching module can be used to respond to a retrieval request for a goods image containing the goods to be retrieved, and match the first image feature extracted from the goods image with a preset material image feature library to determine the goods attribute information associated with the second image feature that matches the first image feature to reply to the retrieval request. As an example, the retrieval request can come from, for example, the above-mentioned goods query, and an interface for uploading an image to retrieve goods can be provided. In some embodiments, by pre-extracting the features of the images of each preset material and storing them, the efficiency of comparison can be accelerated. In some embodiments, the goods image matching module can implement the extraction of the first image feature and the second image feature based on a pre-trained model for feature extraction using artificial intelligence (such as based on CNN). Preferably, the preset material image feature library can select a database for efficient search, such as a database that supports a distributed search and analysis engine (such as Elasticsearch), and an index can be established for the pre-extracted second image features, and the materials can be quickly located in the database by using the approximate nearest neighbor search (KNN) algorithm. Thus, by combining the database and the pre-trained model, efficient goods search and management can be achieved. This process utilizes the powerful search and analysis capabilities of the database and can be efficiently executed in a large-scale dataset. It helps to strengthen the user's ability to identify and locate unfamiliar materials and greatly improves the retrieval efficiency of materials.

[0108] In some embodiments, the warehouse information processing system 106 can also utilize an artificial intelligence (AI) model to make predictions based on warehouse data to facilitate precise decision-making for warehouse management.

[0109] In some examples, the intelligent warehouse system further includes sorting equipment, such as sorting robots, etc. The

[0110] The sorting equipment is communicatively connected to the warehouse information processing system 106, such as a wired or wireless connection. The sorting equipment can have image acquisition capabilities (such as being equipped with a camera) to collect and identify the image feature information of the goods to be sorted, and use a target recognition model to obtain the sorted target area that matches the classification based on the image feature information and perform sorting. The target recognition model can be implemented based on an AI recognition model of CNN, such as YOLO, etc. Preferably, by obtaining a set of goods attribute information of the goods to be sorted, the clustering results of the set of goods attribute information are matched to the corresponding sorted target areas corresponding to each preset classification and sorted, so that the goods can be sorted batch by batch, accelerating the sorting efficiency.

[0111] In some embodiments, the monitoring and analysis can be performed based on the operating parameters of the equipment in the warehouse to predict their maintenance actions. For example, through machine learning models: including supervised learning, unsupervised learning, and support vector machines, etc. For instance, historical wear data is used to train a classifier or a regression model to identify patterns that may cause wear. These models can predict when specific components may experience wear that requires maintenance, so as to schedule the optimal time for maintenance. Another example is through deep neural network models, especially convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are suitable for processing complex time series data, such as vibration signals, temperature changes, etc. They can automatically extract features and capture dependencies over a long time span, and are very effective for early detection of minor anomalies. More simply, based on the preset rules of condition monitoring and threshold setting, the safe operating ranges of key parameters (such as vibration level, temperature) can be set by a rule-based method. An alarm is triggered when the real-time monitoring data shows that it exceeds the preset threshold.

[0112] In some embodiments, the warehouse layout can also be optimized through AI technology. For example, the warehouse information processing system 106 is used to obtain historical cargo attribute information distribution data based on the historical inventory data of the goods (such as the quantity distribution of goods on different specifications, etc., without limitation), and use the layout time series prediction model to predict the predicted distribution of cargo attribute information within a preset time period based on the historical cargo attribute information distribution data. To obtain a layout plan of the cargo storage unit 101 in the warehouse according to the predicted distribution of the cargo attribute information, and obtain a layout adjustment strategy for the cargo storage unit 101 accordingly. The layout time series prediction model can be implemented based on deep neural network models such as RNN and LSTM, and can predict the future cargo attribute information distribution according to the historical cargo attribute information distribution sequence. For example, according to the cargo attribute information distribution sequence from t - n to t time slots, predict the predicted cargo attribute information distribution at t + 1, add the predicted cargo attribute information distribution at t + 1 to the sequence to obtain the cargo attribute information distribution sequence from t - n to t + 1, and then predict the predicted cargo attribute information distribution at t + 2, and so on until the predicted cargo attribute information distribution within the preset time period from t + 1 to t + m is obtained. Corresponding warehouse layout plans can be formulated for them. For example, if it is predicted that the quantity of a certain specification of goods will increase, then the storage space for goods with an appropriate volume / load-bearing capacity will be increased accordingly. Another example is that if there are more goods on the shelves and fewer goods in the ground storage area, then the shelves will be increased and the ground storage area will be reduced, etc.

[0113]

Big Data Analysis and Prediction Related to Goods

[0114] In some embodiments, based on the idea of time series prediction, future warehouse goods data can be predicted according to historical warehouse goods data, so as to facilitate formulating appropriate goods management strategies in advance. For example, predicting actions such as warehousing deployment and replenishment, which will not be listed one by one. The following is an example for illustration.

[0115] In one example, the warehouse information processing system 106 includes a warehousing deployment strategy prediction module for predicting a warehousing deployment strategy according to inbound / outbound goods data. As Figure 9 shown, the warehousing deployment strategy prediction module includes: a logistics prediction module 901, an inbound / outbound prediction module 902, and a warehousing scheduling module 903.

[0116] The logistics prediction module 901 is configured to collect the logistics transportation information of each logistics transportation vehicle with inbound / outbound behavior with the warehouse in the future from the transportation logistics database, and predict the first inbound / outbound predicted goods data of the goods delivered by each logistics transportation vehicle to the destination time slot of the warehouse based on this; the destination time slots of each logistics transportation vehicle form a destination time slot sequence in the order of time slots. In some embodiments, taking a port warehouse as an example, the logistics transportation vehicle can be a ship, and the logistics scheduling data of the ships with inbound / outbound behavior with the warehouse in the future will be presented in public databases and websites, so the arrival time can be determined according to their scheduling time. Moreover, the attribute information of the goods loaded on the ship can also be obtained in advance.

[0117] The inbound / outbound prediction module 902 is configured to use the inbound / outbound time series prediction model to predict the second inbound / outbound predicted goods data of each future time slot in the future preset duration and the corresponding first warehousing allocation resource prediction information of the next time slot one by one according to the instantaneously updated historical inbound / outbound actual data of the warehouse; wherein, the future preset duration includes one or more of the destination time slots. In some embodiments, the inbound / outbound time series prediction model can be implemented based on RNN, LSTM, etc., and the future inbound / outbound data can be predicted through the historical inbound / outbound data of the warehouse. In some embodiments, the prediction of inbound data and the prediction of outbound data can be completed by different sub-models. The first warehousing allocation resource prediction information can be the predicted inventory distribution data. According to the inventory distribution data S at time t-1 t-1 superimposed with the goods inbound / outbound data at time t-1, the S at time t can be obtained t . Therefore, according to the first warehousing allocation resource prediction information of the previous moment superimposed with the predicted goods inbound / outbound data, the first warehousing allocation resource prediction information of the next moment can be predicted.

[0118] Among them, there is a time slot overlap in the future predictions of the logistics prediction module 901 and the inbound / outbound prediction module 902. Thus, the prediction data in the overlapping time slots can be superimposed, thereby achieving a more accurate prediction effect.

[0119] The warehousing scheduling module 903 is used to traverse in the order of the destination time slot sequence, and superimpose the predicted first inbound / outbound cargo data of the logistics prediction module in the current destination time slot to the second inbound / outbound predicted cargo data predicted by the inbound / outbound prediction module, so as to obtain the updated inbound / outbound cargo prediction data of the current destination time slot; and match the first warehousing allocation resource prediction information of the current destination time slot with the updated inbound / outbound cargo prediction data, and update the inventory allocation strategy in the time slots before the current destination time slot according to the matching result. For example, through the logistics prediction module, it is predicted that ships A and B will arrive at the port at time slot t + 1. Ship A has x1 quantity of cargo C to be warehoused, and ship B has y1 quantity of cargo D to be out of the warehouse. Through the inbound / outbound prediction module, it is predicted that the warehouse will have x2 (assuming x1 > x2) quantity of cargo C out of the warehouse at time slot t + 1, and y2 quantity of cargo D out of the warehouse at time slot t + 1. Then the updated inbound / outbound cargo prediction data is superimposed: cargo C is warehoused x1 - x2, and cargo D is out of the warehouse y2 + y1. Thus, when matching the inventory allocation strategy, it can be analyzed that the vacant space quantity x2 left for the shipment of cargo C is less than the inbound quantity x1. Then, adding the remaining other suitable vacant space quantity x3 for C, whether it can meet the demand, that is, whether x3 + x2 is greater than x1. If the demand cannot be met, inventory allocation is carried out to create enough vacant space. For cargo D out of the warehouse y2 + y1, record the predicted vacant space of y2 + y1 for other cargo to use.

[0120] In another example, corresponding to the inbound / outbound requirements of the enterprise commodity scenario that the warehouse needs to meet, the replenishment strategy can also be predicted in combination with the inventory situation of the commodity. The warehouse information processing system 106 further includes: a replenishment time sequence prediction module for replenishment prediction. The replenishment time sequence prediction module is used to execute an intelligent replenishment prediction process, as Figure 10 shown, the process includes:

[0121] Step S1001: Use the inventory time sequence prediction model to predict the predicted inventory quantity of the target cargo in the future time slot based on the historical inventory data, and use the project demand time sequence prediction model to obtain the predicted cargo shipment demand quantity of the target cargo in the future time slot based on the prediction of the historical project demand cargo data of the target cargo or based on the planned project demand shipment cargo data.

[0122] In some embodiments, the inventory time sequence prediction model is used to predict the predicted inventory quantity in the future time slot according to the historical inventory data. And, according to the project (such as related to sales orders from various channels) demand, it can include the predicted shipment demand quantity determined from the historical project demand prediction or the actual determined planned project (such as the signed order).

[0123] Step S1002: Compare the predicted inventory with the predicted demand for goods to be shipped.

[0124] Through comparison, determine whether the predicted inventory is insufficient for the predicted demand for goods to be shipped, i.e., a shortage situation.

[0125] Step S1003: When there is a first predicted inventory shortage in the comparison, accordingly determine to execute a replenishment strategy in the current time slot.

[0126] Among them, the replenishment strategy includes: determining a first replenishment quantity to make up for the first predicted inventory shortage; predicting the predicted replenishment quantity in a future time slot based on the historical replenishment quantity data of one or more suppliers for the target goods; selecting one supplier whose predicted replenishment quantity can meet the first predicted inventory shortage or multiple suppliers whose sum of predicted replenishment quantities can meet the first predicted inventory shortage as target suppliers to execute the replenishment action. Specifically, after determining the first predicted inventory shortage, the corresponding first replenishment quantity in the future time slot is obtained. Since replenishment is required from suppliers, it is also necessary to predict whether the predicted replenishment quantity of the selected suppliers in the future time slot can meet the demand of the first predicted inventory shortage. If the predicted replenishment quantity of one supplier can meet the first replenishment quantity, it is selected as the target supplier; if the predicted replenishment quantity of one supplier cannot meet the first replenishment quantity, additional suppliers are added until the sum of the predicted replenishment quantities of multiple suppliers can meet the first replenishment quantity, and the multiple suppliers are used as the target co-suppliers.

[0127] In some embodiments, a visual digital twin warehouse can also be formed for the warehouse for users to intuitively view and understand the actual operating status in the warehouse.

[0128] As an example, the warehouse information processing system 106 includes: a twin warehousing system obtained by virtualizing the intelligent warehousing system 100, and displaying the operation data of the twin warehousing system through an intelligent warehousing visualization graphical interface, where the operation data includes the material information of the goods in the warehouse; the operating state of the twin warehousing system is updated consistently according to the data change of the intelligent warehousing system 100.

[0129] Specifically, the twin warehousing system includes: a twin storage unit corresponding to the goods storage unit 101 for performing virtual storage or virtual retrieval actions of goods; a twin conveying unit corresponding to the goods conveying unit 102, including: a twin transporting sub-unit for transporting twin goods in the twin warehouse and a twin handling sub-unit for disposing of goods to the twin storage unit.

[0130]

Comprehensive security monitoring and other intelligent functions

[0131] In some embodiments, the warehouse information processing system 106 is communicatively connected to the multiple monitoring and sensing devices, and integrally displays the monitoring data of the multiple monitoring and sensing devices on the intelligent warehousing visualization graphic interface; the warehouse information processing system 106 is further configured to form and output an alarm message in response to determining the occurrence of an alarm event based on the monitoring data. The implementation and communication architecture of various monitoring and sensing devices have been described in the previous embodiments, and will not be elaborated here. In some embodiments, through a B-S architecture, the intelligent warehousing visualization graphic interface can be displayed through a web page, and various charts can be formed and displayed for the integration of the monitoring data of the multiple monitoring and sensing devices, such as common charts like bar charts and line charts, or combined charts drawn for different monitoring data.

[0132] As Figure 11 shown, a schematic flowchart of a warehouse guiding and controlling method according to an embodiment of the present disclosure is presented. The method can be applied to the intelligent warehousing system 100 in the previous embodiments, and is used to control a group of light-emitting positioning guiding devices 104 in the warehouse to achieve guiding. The light-emitting positioning guiding device 104 is configured to emit at least one type of signal light (such as characteristic frequency, color, etc.) to indicate its location. Each light-emitting positioning guiding device 104 has an information set (i.e., fingerprint, for example) generated based on an associated light-emitting device identifier, location information, and light-emitting characteristics. Since the principles, implementation details, etc. in this embodiment have been described in the previous embodiments, they will not be repeated here.

[0133] The method includes:

[0134] Step S1101: Obtain the goods attribute information of the goods, and generate the planned route for the inbound / outbound of the goods based on the destination location corresponding to the goods attribute information.

[0135] Step S1102: Determine a group of target light-emitting positioning guiding devices 104 according to the matching relationship between the location information of a group of the light-emitting positioning guiding devices 104 and the planned route, and instruct them to perform the light-emitting guiding action.

[0136] As Figure 12 shown, a module schematic diagram of a warehouse guiding and controlling device provided in an embodiment of the present disclosure is presented. The device can be applied to the intelligent warehousing system 100 in the previous embodiments, and is used to control a group of light-emitting positioning guiding devices 104 in the warehouse to achieve guiding. The light-emitting positioning guiding device 104 is configured to emit at least one type of signal light (such as characteristic frequency, color, etc.) to indicate its location. Each light-emitting positioning guiding device 104 has an information set (i.e., fingerprint, for example) generated based on an associated light-emitting device identifier, location information, and light-emitting characteristics. Since the principles, implementation details, etc. in this embodiment have been described in the previous embodiments, they will not be repeated here.

[0137] In Figure 12 it, the device includes:

[0138] A route planning module 1201, configured to obtain the cargo attribute information of the cargo, and generate a planned route for the inbound / outbound of the cargo based on the destination location corresponding to the cargo attribute information.

[0139] A guiding and controlling module 1202, configured to determine a group of target light-emitting positioning guiding devices 104 according to the matching relationship between the position information of a group of the light-emitting positioning guiding devices 104 and the planned route, and instruct them to perform a light-emitting guiding action.

[0140] It should be specifically noted that, in the previous embodiments, each "module" mentioned can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program or an instruction product. The computer program or instruction product includes one or a group of computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions according to the present disclosure are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer program or instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0141] And, Figure 12 The device disclosed in the embodiments can be implemented by other module partitioning methods. The device embodiments shown above are only illustrative. For example, the partitioning of the modules is only a logical function partitioning. In actual implementation, there can be other partitioning methods. For example, a group of modules or modules can be combined or can be dynamically integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of the devices or modules can be in an electrical or other form.

[0142] In addition, each "module" and sub-module in the previous embodiments can be dynamically integrated in a processing component, or each module can exist physically alone, or two or more modules can be dynamically integrated in a component. The above-mentioned dynamic component can be implemented in the form of hardware or in the form of a software function module. When the above-mentioned dynamic component is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a magnetic disk, an optical disc, etc.

[0143] It should be particularly noted that the flowcharts of the above embodiments of the present disclosure represent processes or methods that can be understood as representing modules, segments, or portions of code of executable instructions including one or more sets of steps configured to implement specific logical functions or processes. And the scope of the preferred embodiments of the present disclosure includes additional implementations, where functions can be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed.

[0144] For example, Figure 10 , Figure 11 etc. The order of each step in the method embodiments may be changed in a specific scenario and is not limited to the above representation.

[0145] As Figure 13 shown, a schematic structural diagram of a computer device in an embodiment of the present disclosure is shown. The warehouse information processing system 106 may be implemented based on one or more of the computer devices. In some embodiments, the warehouse information processing system 106 may be implemented as a cloud platform, and then the computer device may be implemented as a server. Or, in other embodiments, the computer device may also be implemented as a desktop computer, a laptop computer, a tablet computer, a smart phone, etc. or a cluster thereof.

[0146] The computer device 1300 includes a bus 1301, a processor 1302, and a memory 1303. Communication can be carried out between the processor 1302 and the memory 1303 through the bus 1301. A computer program or instruction may be stored in the memory 1303. The processor 1302 realizes various functions of the warehouse information processing system 106 in the previous embodiments by running the computer program or instruction in the memory 1303, including Figure 11 the method processes in

[0147] The bus 1301 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, although only a thick line is used in the figure, it does not mean that there is only one bus or one type of bus.

[0148] In some embodiments, the processor 1302 may be implemented as a Central Processing Unit (CPU), a micro reaction processing unit (MCU), a System On Chip, or a Field Programmable Gate Array (FPGA), etc. The memory 1303 may include volatile memory for temporarily storing data when running a program, such as Random Access Memory (RAM).

[0149] The memory 1303 may further include non-volatile memory for data storage, such as Read-Only Memory (ROM), flash memory, a Hard Disk Drive (HDD), or a Solid-State Disk (SSD).

[0150] In some embodiments, the computer unit 1300 may further include a communicator 1304. The communicator 1304 is used for external communication. In a specific example, the communicator 1304 may include one or a group of wired and / or wireless communication circuit modules. For example, the communicator 1304 may include one or more of a wired network card, a USB module, a serial interface module, etc. The wireless communication protocols followed by the wireless communication module include, for example, Near Field Communication (NFC) technology, Infrared (IR) technology, Global System for Mobile communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time-Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), Bluetooth (BT), Global Navigation Satellite System (GNSS), etc.

[0151] In an embodiment of the present disclosure, a computer-readable storage medium may also be provided, storing a computer program or instruction, and when the computer program or instruction is run, the steps in the previous method embodiment are implemented.

[0152] That is, the method steps in the above embodiments are implemented as software or computer code that can be stored in a recording medium (such as a CD ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code that is originally stored in a remote recording medium or a non-transitory machine-readable medium and downloaded through a network and will be stored in a local recording medium, so that the method represented herein can be stored in such software processing on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA).

[0153] In an embodiment of the present disclosure, a computer program product may also be provided, including one or more computer programs or instructions, and when the one or more computer programs or instructions are run, the method steps in the previous embodiments are fully or partially executed. The computer program product includes one or more computer programs or instructions.

[0154] The computer program or instruction can be stored in a readable storage medium, or transmitted from one readable storage medium to another. For example, the computer program or instruction can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless manner. The readable storage medium can be any available medium that can be accessed, or a data storage device such as a server or data center integrating one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium can be a volatile or non-volatile storage medium, or can include both volatile and non-volatile types of storage media.

[0155] In summary, the present disclosure relates to intelligent warehousing, and provides an intelligent warehousing system and a warehouse guiding and control method. The system includes: a goods storage unit, a goods conveying unit, a goods sensing unit, a group of light-emitting positioning and guiding devices, a positioning terminal, and a warehouse information processing system communicatively connected to them. The positioning terminal collects signal light for matching an associated information set to determine the location of the terminal. The warehouse information processing system obtains the goods attribute information of the goods, and generates an inbound / outbound planning route for the goods based on the destination location corresponding to the goods attribute information. And, a group of target light-emitting positioning and guiding devices are determined according to the matching relationship between the position information of the light-emitting positioning and guiding devices and the planning route, and they are instructed to perform a light guiding action.

[0156] The above embodiments are only illustrative of the principles and effects of the present disclosure, and are not intended to limit the present disclosure. Any person familiar with this technology can modify or change the above embodiments without departing from the spirit and scope of the present disclosure. Therefore, all equivalent modifications or changes made by those with ordinary knowledge in the technical field without departing from the spirit and technical idea disclosed by the present disclosure should still be covered by the protection scope of the present disclosure.

Claims

1. A smart warehousing system, characterized in that: Applied in warehouses, including: The cargo storage unit is located in the warehouse and has a storage space for cargo; A cargo transport unit, provided in the warehouse, comprising: a cargo transport subunit for transporting cargo within the warehouse, and a cargo handling subunit for disposing cargo to the cargo storage unit; A cargo sensing unit is at least arranged at a storage entry location, a storage exit location and a cargo storage unit, and is used to sense cargo and collect cargo attribute information; A group of light-emitting positioning and guiding devices, distributed in the warehouse, for emitting at least one type of signal light to indicate the location; wherein each light-emitting positioning and guiding device has an information set generated based on an associated light-emitting device identification, location information and light-emitting characteristics, for optical communication with the outside to determine the location based on the information set; the signal lights of the light-emitting positioning and guiding devices have different light-emitting characteristics; the group of light-emitting positioning and guiding devices is used to provide a group of target light-emitting positioning and guiding devices that perform light-emitting guidance actions corresponding to the current planned route; A positioning terminal, which can be carried and moved by the cargo transport unit or the staff, and is used to collect the signal light so as to match the associated information set according to the signal light to determine the location of the terminal; The warehouse information processing system is communicatively connected with the cargo conveying unit, the cargo sensing unit, each of the light-emitting positioning and guiding devices and the positioning terminal, and is used to obtain cargo attribute information of the cargo, and generate a planned route for the cargo to enter / exit the warehouse based on the destination location corresponding to the cargo attribute information; and, based on the matching relationship between the location information of a group of the light-emitting positioning and guiding devices and the planned route, a group of target light-emitting positioning and guiding devices is determined, and they are instructed to perform light-emitting guidance actions.

2. The intelligent warehousing system according to claim 1, characterized in that: The warehouse information processing system includes a storage and allocation strategy prediction module for predicting storage and allocation strategies based on inbound / outbound cargo data; The storage allocation strategy prediction module includes: The logistics prediction module is used to collect logistics transportation information of each logistics transportation vehicle that will have future inbound / outbound shipment behavior with the warehouse from the transportation logistics database, and predict the first inbound / outbound forecast cargo data of the destination time slot of the cargo delivered by each logistics transportation vehicle arriving at the warehouse; the destination time slots of each logistics transportation vehicle constitute a destination time slot sequence in the order of time slots; The inbound / outbound forecasting module is used to use the inbound / outbound time series forecasting model to forecast the second inbound / outbound forecasted cargo data of each future time slot in the future preset time length and the first storage allocation resource forecasting information of the corresponding next time slot according to the real-time updated historical inbound / outbound actual data of the warehouse; wherein the future preset time length includes one or more of the destination time slots; The warehousing scheduling module is used to traverse in order according to the sequence of destination time slots, and add the first inbound / outbound cargo data predicted by the logistics prediction module in the current destination time slot to the second inbound / outbound predicted cargo data predicted by the inbound / outbound prediction module to obtain the inbound / outbound cargo prediction update data of the current destination time slot; and match the inbound / outbound cargo prediction update data with the first warehousing allocation resource prediction information of the current destination time slot, and update the inventory allocation strategy of the time slot before the current destination time slot according to the matching result.

3. The intelligent warehousing system according to claim 1, characterized in that: The warehouse information processing system includes: a replenishment timing prediction module, which is used to execute an intelligent replenishment prediction process, including: using an inventory timing prediction model to predict the predicted inventory quantity of a target commodity in a future time slot based on historical inventory data, using a project demand timing prediction model to predict the historical project demand cargo data of the target commodity or based on the planned project demand shipment cargo data to obtain the predicted shipment demand quantity of the target commodity in the future time slot; comparing the predicted inventory quantity with the predicted shipment demand quantity of the cargo; when the comparison shows a first predicted inventory shortage, determining to execute a replenishment strategy in the current time slot accordingly; wherein the replenishment strategy includes: determining a first replenishment quantity to make up for the first predicted inventory shortage; predicting the predicted stock quantity in the future time slot based on the historical stock quantity data of one or more suppliers for the target commodity; selecting a supplier whose predicted stock quantity can meet the first predicted inventory shortage or multiple suppliers whose sum of predicted stock quantities can meet the first predicted inventory shortage as target suppliers to execute the replenishment action.

4. The intelligent warehousing system according to claim 1, characterized in that: The warehouse information processing system includes a recommended cargo location module, which is used to determine a matching recommended cargo storage space in a cargo storage unit according to cargo attribute information of the cargo in response to a cargo entry record being generated, and to perform a virtual storage action of storing the cargo in a virtual recommended space corresponding to the recommended cargo storage space, so as to obtain a virtual warehouse entry record; when the cargo is actually stored, the corresponding recommended storage space is determined based on the virtual storage space of the virtual warehouse entry record, and in response to the completion of the actual storage action, an actual warehouse entry record is formed; The cargo storage unit has storage unit attribute information, and the cargo conveying unit has conveying unit attribute information; and the step of determining a matching recommended cargo storage space according to the cargo attribute information of the cargo includes: Based on the establishment of an in / out warehouse matching chain among cargo attribute information, storage unit attribute information and transport unit attribute information, the recommended cargo storage space, the allocated cargo transport subunit and the allocated cargo handling subunit in the cargo storage unit corresponding to the cargo are determined, including at least one of the following: 1) Determining cargo transport subunits and cargo handling subunits with matching volume / load-bearing capacity, and recommended cargo storage space with matching volume / load-bearing capacity / height according to the volume / weight of the cargo; wherein the volume / load-bearing capacity of the matching cargo transport subunit and the recommended cargo storage space is positively correlated with the volume / weight of the cargo, and the height of the recommended cargo storage space is negatively correlated with the volume / weight of the cargo; 2) Determining cargo transport subunits and cargo handling subunits that meet the category transportation conditions, and matching category partitions according to the category of the cargo. Recommended cargo storage space; the category transportation conditions include cargo transport subunits and / or cargo handling subunits with hazard protection capabilities / temperature control capabilities for cargo with hazardous properties / temperature requirements; the category partitions are used for cross-contamination isolation / temperature isolation / avoiding confusion between cargo with contamination / temperature requirements / similarities; 3) Select and determine the recommended cargo storage space of the matching frequency partition according to the cargo outbound frequency / inbound frequency / shelf life; wherein the distance between the location of the recommended cargo storage space and the inbound location / outbound location is negatively correlated with the cargo outbound frequency / inbound frequency, and positively correlated with the remaining shelf life of the cargo; the height of the recommended cargo storage space is negatively correlated with the cargo outbound frequency / inbound frequency, and positively correlated with the remaining shelf life, and is determined in combination with the volume / weight superposition.

5. The intelligent warehousing system according to claim 4, characterized in that: When there are multiple alternative cargo storage spaces, the warehouse information processing system is used to select a recommended cargo storage space with the goal of maximizing space utilization of the cargo storage space and minimizing the distance between cargo storage spaces where cargoes with similar / related cargo attribute information are located.

6. The intelligent warehousing system according to claim 1 or 4, characterized in that: The warehouse information processing system includes: a twin warehousing system obtained by virtualizing the smart warehousing system, and displaying the operating data of the twin warehousing system through a smart warehousing visualization graphic interface, wherein the operating data includes material information of goods in the warehouse; the operating status of the twin warehousing system is consistently updated according to the data changes of the smart warehousing system; the twin warehousing system includes: a twin storage unit corresponding to the goods storage unit, used for performing a virtual storage action or a virtual retrieval action of goods; a twin conveying unit corresponding to the goods conveying unit, including: a twin conveying subunit for conveying twin goods in a twin warehouse, and a twin handling subunit for disposing of goods to the twin storage unit; And / or, the smart warehousing system also includes a variety of monitoring sensor devices distributed in the warehouse, which are used to collect monitoring data on the warehouse environment, equipment and / or goods; the warehouse information processing system is communicated with the various monitoring sensor devices, and the monitoring data of the various monitoring sensor devices are integrated and displayed in the smart warehousing visualization graphic interface; the warehouse information processing system is also used to respond to the occurrence of an alarm event determined based on the monitoring data and generate an alarm information output.

7. The intelligent warehousing system according to claim 1, characterized in that: The warehouse information processing system is used to obtain historical cargo attribute information distribution data based on the historical inventory data of the cargo, and use the layout time series prediction model to predict the predicted distribution of cargo attribute information within a preset time period based on the historical cargo attribute information distribution data, so as to obtain an adapted layout plan of the cargo storage unit in the warehouse according to the predicted distribution of the cargo attribute information, and obtain a layout adjustment strategy of the cargo storage unit accordingly.

8. The intelligent warehousing system according to claim 1, characterized in that: Also includes: The sorting equipment is communicatively connected with the warehouse information processing system; the sorting equipment is used to collect and identify image feature information of the goods to be sorted, obtain a sorting target area of ​​a matching classification according to the image feature information using a target recognition model and perform sorting; and / or obtain a group of goods attribute information of the goods to be sorted, match the clustering results of the group of goods attribute information in a preset classification to the sorting target area corresponding to each preset classification and perform sorting.

9. The intelligent warehousing system according to claim 1, characterized in that: The warehouse information processing system includes a light-emitting guidance control module, which is used to sort a determined group of target light-emitting positioning guidance devices according to a planned route to obtain a target light-emitting sequence; And, based on the target light-emitting sequence, a group of the target light-emitting positioning and guiding devices are made to emit light in sequence, including: in response to the target positioning terminal in a planned route of a transportation task completing the communication confirmation of the corresponding information set by collecting signal light from the currently illuminated target light-emitting positioning and guiding device, the currently illuminated target light-emitting positioning and guiding device is extinguished and the next target light-emitting positioning and guiding device is illuminated.

10. The intelligent warehousing system according to claim 1, characterized in that: The warehouse information processing system includes a light-emitting guidance control module, which is used to sort a determined group of target light-emitting positioning guidance devices according to a planned route to obtain a target light-emitting sequence; And, based on the target light-emitting sequence, a group of the target light-emitting positioning guidance devices are made to emit light together, including: in response to the completion of communication confirmation based on the information set between the target light-emitting positioning guidance devices in the planned route of a transportation task and the target positioning terminal, the target light-emitting positioning guidance devices that have completed the communication confirmation are turned off.

11. The intelligent warehousing system according to claim 1, characterized in that: Each of the light-emitting positioning guidance devices includes a guide light and a limit light with different light-emitting characteristics; the warehouse information processing system includes a light-emitting guidance control module, which is used to make the guide lights of a group of the target light-emitting positioning guidance devices light up together or in sequence; wherein, in response to a communication confirmation indicating a wrong route travel event between a target light-emitting positioning guidance device and a target positioning terminal based on the information set, the limit light of the target light-emitting positioning guidance device forms a light in the wrong direction of travel while the guide light does not light up.

12. The intelligent warehousing system according to claim 1, 9, 10 or 11, characterized in that: The warehouse information processing system is used to provide a material query graphical interface in response to user operations, and the material query graphical interface includes a cargo query interface for querying materials, and a location guidance control corresponding to the queried cargo; in response to the location guidance control accepting user operations, it displays a warehouse plan including a planned route leading to the location of the corresponding cargo, and instructs a corresponding set of target light-emitting positioning guidance devices to perform a light-emitting guidance action.

13. The intelligent storage system according to claim 1, 9, 10 or 11, characterized in that: The warehouse information processing system is further used to determine the eligibility of the positioning terminal relative to the collected light-emitting positioning guidance device according to the signal characteristics of the signal light collected by the light-emitting positioning guidance device; and, when the positioning terminal is not qualified, refuse to perform the light-emitting guidance action; and / or, The warehouse information processing system is integrated with a warehouse management system (WMS) and a warehouse control system (WCS) for communicating and controlling a cargo transport unit; or, in addition to being integrated with a warehouse management system (WMS) and a warehouse control system (WCS), the warehouse information processing system is also integrated with at least one of the following: an enterprise resource planning system (ERP); a product lifecycle management system (PLM); a manufacturing execution system (MES); and / or, The warehouse information processing system includes a cargo image matching module, which is used to respond to a search request containing a cargo image of the cargo to be searched, by matching a first image feature extracted from the cargo image with a preset cargo image feature library, so as to determine cargo attribute information associated with a second image feature matching the first image feature to reply to the search request; and / or, The light-emitting positioning guide device is implemented as a lighting device.

14. A warehouse guidance control method, characterized in that: Applicable to the control of a group of light-emitting positioning and guiding devices in a warehouse; the light-emitting positioning and guiding devices are used to emit at least one type of signal light to indicate the location; Each light-emitting positioning and guiding device has an information set generated based on an associated light-emitting device identification, location information, and light-emitting characteristics; The method comprises: Acquire cargo attribute information of the cargo, and generate a planned route for the cargo to enter / exit the warehouse based on the destination location corresponding to the cargo attribute information; A group of target light-emitting positioning and guiding devices is determined according to the matching relationship between the position information of a group of the light-emitting positioning and guiding devices and the planned route, and they are instructed to perform light-emitting guidance actions.

Images