CN113506055A - Article warehousing method and device - Google Patents
Article warehousing method and device Download PDFInfo
- Publication number
- CN113506055A CN113506055A CN202110699703.8A CN202110699703A CN113506055A CN 113506055 A CN113506055 A CN 113506055A CN 202110699703 A CN202110699703 A CN 202110699703A CN 113506055 A CN113506055 A CN 113506055A
- Authority
- CN
- China
- Prior art keywords
- article
- storage
- warehousing
- target
- item
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 238000012549 training Methods 0.000 claims description 42
- 230000032258 transport Effects 0.000 claims description 13
- 239000000284 extract Substances 0.000 claims description 5
- 230000008569 process Effects 0.000 abstract description 9
- 239000002609 medium Substances 0.000 description 12
- 238000004806 packaging method and process Methods 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 4
- 235000013611 frozen food Nutrition 0.000 description 4
- 238000012937 correction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000012856 packing Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000012120 mounting media Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 235000014102 seafood Nutrition 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device
- G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Human Resources & Organizations (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Engineering & Computer Science (AREA)
Abstract
The embodiment of the application discloses an article warehousing method and device. According to the technical scheme provided by the embodiment of the application, the target article is identified, the article information of the target article is obtained, whether the article information accords with the warehousing condition is checked based on the article information, if the article information accords with the warehousing condition, the warehousing request is generated, the warehousing request is input into a pre-trained warehousing model to output the storage condition, the corresponding storage place is obtained according to the current idle storage capacity and the storage condition, and therefore the target article is stored to the position corresponding to the storage place; the whole process is automatically processed, manual intervention is avoided, the error cost is reduced, and the warehousing efficiency and the accuracy are improved.
Description
Technical Field
The embodiment of the application relates to the technical field of warehousing management, in particular to a method and a device for warehousing articles. An apparatus and a storage medium.
Background
With the explosion of the e-commerce industry in recent years, the development of the logistics industry is driven, and higher requirements are put forward for the logistics industry. The traditional logistics industry depends on manpower, is slow, and cannot meet the requirements of a large number of current e-commerce transactions.
And warehousing the goods, namely, the process of checking and accepting various received goods, classifying and recording the goods passing the checking and accepting, and storing the goods to corresponding positions in a warehouse. In the current warehousing management, goods are mainly checked manually before being warehoused, so that the efficiency is low, and mistakes are easily made.
Disclosure of Invention
The embodiment of the application provides a method, a device, equipment and a storage medium for warehousing articles, so as to realize automatic verification of the warehoused articles and improve warehousing efficiency.
In a first aspect, an embodiment of the present application provides an article warehousing method, including:
identifying a target item, and acquiring item information of the target item, wherein the item information comprises an item size, an item attribute, a delivery place and a receiving place;
checking whether the target article meets warehousing conditions or not based on the article information, and generating a warehousing request when the warehousing conditions are met, wherein the warehousing request carries the article information;
inputting the warehousing request as an input feature into a pre-trained warehousing model to output matched storage conditions, wherein the storage conditions comprise a storage environment and a storage space;
and acquiring the current idle storage capacity, obtaining a storage place corresponding to the target article according to the current idle storage capacity and the storage condition, and binding the storage place with the article information.
Further, the identifying a target item and acquiring item information of the target item include:
acquiring three-dimensional image data of the target object, and acquiring the object size of the target object according to the three-dimensional image data;
and reading the item label on the target item, and acquiring the item attribute, the delivery place and the receiving place.
Further, the identifying a target item and acquiring item information of the target item include:
acquiring image data of a conveying belt, and acquiring three-dimensional image data of an article when the article is detected to be on the conveying belt according to the image data;
detecting whether an identification code on the surface of the article is identified according to the three-dimensional image data, defining the article as a target article when the identification code is identified, and acquiring article attributes, a delivery place and a receiving place of the target article according to the identification code;
and acquiring the object size of the target object according to the three-dimensional image data.
Further, the checking whether the target article meets the warehousing condition based on the article information includes:
detecting whether the target article meets the warehousing specification requirement or not according to the article information;
and when the target article meets the requirement of the warehousing specification, comparing the article attribute of the target article with the pre-stored article attribute, and when the article attribute of the target article is consistent with the pre-stored article attribute, defining that the warehousing condition is met.
Further, the warehousing model is obtained by training in the following way:
acquiring historical article information and historical storage places corresponding to the historical article information respectively;
selecting historical article information corresponding to a first preset proportion from the historical article information as model input data, and selecting historical article information corresponding to a second preset proportion as training input data;
selecting a historical storage place corresponding to model input data as model output data, and selecting a historical storage place corresponding to the training input data as training output data
And establishing a training model according to the model input data and the model output data, and correcting the training model according to the training input data and the training output data to obtain a warehousing model.
Further, acquiring a current free storage capacity, and obtaining a storage location corresponding to the target item according to the current free storage capacity and the storage condition, includes:
acquiring current idle storage capacity, wherein the current idle storage capacity comprises storage intervals corresponding to different article attributes;
and selecting a corresponding storage interval from the current idle storage capacity according to the storage condition, and distributing a corresponding storage place according to a preset distribution rule.
Further, the method also comprises the following steps:
and sending the storage place and the article information to a transport vehicle so that the transport vehicle extracts the target article according to the article information and transports the target article to the storage place.
In a second aspect, an embodiment of the present application provides an article warehousing device, including:
a target item identification module: the system is used for identifying a target item and acquiring item information of the target item, wherein the item information comprises an item size, an item attribute, a delivery place and a receiving place;
a warehousing condition judgment module: the system is used for detecting whether the target article meets warehousing conditions or not based on the article information, and generating a warehousing request when the warehousing conditions are met, wherein the warehousing request carries the article information;
a storage condition generation module: the storage system is used for inputting the warehousing request as an input feature into a pre-trained warehousing model so as to output matched storage conditions, wherein the storage conditions comprise a storage environment and a storage space;
a storage location acquisition module: the system is used for acquiring the current free storage capacity, obtaining a storage place corresponding to a target article according to the current free storage capacity and the storage condition, and binding the storage place with article information.
Further, in the target object identification module, identifying a target object and acquiring object information of the target object includes:
acquiring three-dimensional image data of the target object, and acquiring the object size of the target object according to the three-dimensional image data;
and reading the item label on the target item, and acquiring the item attribute, the delivery place and the receiving place.
Further, in the target object identification module, identifying a target object and acquiring object information of the target object includes:
acquiring image data of a conveying belt, and acquiring three-dimensional image data of an article when the article is detected to be on the conveying belt according to the image data;
detecting whether an identification code on the surface of the article is identified according to the three-dimensional image data, defining the article as a target article when the identification code is identified, and acquiring article attributes, a delivery place and a receiving place of the target article according to the identification code;
and acquiring the object size of the target object according to the three-dimensional image data.
Further, the warehousing condition judgment module, based on the article information, checks whether the target article meets the warehousing condition, including:
detecting whether the target article meets the warehousing specification requirement or not according to the article information;
and when the target article meets the requirement of the warehousing specification, comparing the article attribute of the target article with the pre-stored article attribute, and when the article attribute of the target article is consistent with the pre-stored article attribute, defining that the warehousing condition is met.
Further, the warehousing model is obtained by training in the following way:
acquiring historical article information and historical storage places corresponding to the historical article information respectively;
selecting historical article information corresponding to a first preset proportion from the historical article information as model input data, and selecting historical article information corresponding to a second preset proportion as training input data;
selecting a historical storage place corresponding to model input data as model output data, and selecting a historical storage place corresponding to the training input data as training output data;
and establishing a training model according to the model input data and the model output data, and correcting the training model according to the training input data and the training output data to obtain a warehousing model.
Further, the obtaining, in the storage location obtaining module, a current free storage capacity, and obtaining a storage location corresponding to the target item according to the current free storage capacity and the storage condition includes:
acquiring current idle storage capacity, wherein the current idle storage capacity comprises storage intervals corresponding to different article attributes;
and selecting a corresponding storage interval from the current idle storage capacity according to the storage condition, and distributing a corresponding storage place according to a preset distribution rule.
The system further comprises a delivery information sending module, which is used for sending the storage location and the article information to a delivery vehicle, so that the delivery vehicle extracts the target article according to the article information and delivers the target article to the storage location.
In a third aspect, an embodiment of the present application provides a computer device, including: a memory and one or more processors;
the memory for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors may be caused to implement the method of warehousing articles as described in the first aspect.
In a fourth aspect, embodiments of the present application provide a storage medium containing computer-executable instructions for performing the method of warehousing items as described in the first aspect when executed by a computer processor.
According to the method and the device, the target article is identified, the article information of the target article is obtained, whether the article information meets the warehousing condition is checked based on the article information, if yes, the warehousing request is generated, the warehousing request is input into a pre-trained warehousing model to output the storage condition, the corresponding storage place is obtained according to the current idle storage capacity and the storage condition, and therefore the target article is stored to the position corresponding to the storage place; the whole process is automatically processed, manual intervention is avoided, the error cost is reduced, and the warehousing efficiency and the accuracy are improved.
Drawings
Fig. 1 is a flowchart of an article warehousing method provided in an embodiment of the present application;
fig. 2 is a flowchart of another article warehousing method provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of an article warehousing device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an article warehousing device provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The embodiment of the application provides a method, a device, equipment and a storage medium for warehousing articles. According to the method and the device, the target article is identified, the article information of the target article is obtained, whether the article information meets the warehousing condition is checked based on the article information, if yes, the warehousing request is generated, the warehousing request is input into a pre-trained warehousing model to output the storage condition, the corresponding storage place is obtained according to the current idle storage capacity and the storage condition, and therefore the target article is stored to the position corresponding to the storage place; the whole process is automatically processed, manual intervention is avoided, the error cost is reduced, and the warehousing efficiency and the accuracy are improved. .
The following are detailed below.
Example one
Fig. 1 is a flowchart of an article warehousing method provided in an embodiment of the present application, where the article warehousing method provided in the embodiment of the present application may be executed by an article warehousing device, and the article warehousing device may be implemented in a hardware and/or software manner and integrated in a computer device.
The following description will be given taking an example in which the article warehousing device executes the article warehousing method. Referring to fig. 1, the article warehousing method includes:
101: identifying a target item, and acquiring item information of the target item, wherein the item information comprises an item size, an item attribute, a delivery place and a receiving place.
In the embodiment, the target article refers to an article that needs to be put in storage. Taking express parcels in logistics as an example, each parcel needing to be put in storage is a target object. Wherein, the target object has already been formed with the extranal packing, and the extranal packing can be the carton, also can be the wrapping bag. And defining that the articles which are not formed into the external package do not meet the warehousing requirements. The target object is identified by the camera, the outline of the target object is identified, the object label on the target object is read by the reader, and other information of the target object is acquired.
According to an exemplary embodiment, an article warehousing system is provided, which includes a processor, a reader and a camera, wherein the camera is configured to acquire image data of a target article, and the reader is configured to read an article tag on the target article.
Specifically, the method comprises the following steps:
acquiring three-dimensional image data of the target object, and acquiring the object size of the target object according to the three-dimensional image data; in the step, three-dimensional image data of the target object is acquired through the camera, and the target object in the three-dimensional image data is subjected to contour calculation by combining with a prestored calculation reference to obtain the three-dimensional size of the target object, namely the size of the object.
And reading the item label on the target item, and acquiring the item attribute, the delivery place and the receiving place. In this step, the article tag is read by a reader, specifically, the reader is, for example, an RFID reader, and the article tag is an RFID article tag. In the process of packaging the target item, an item label is attached to the outer package, and the item label integrates item attributes, a delivery location and a receiving location. The integration of the information corresponding to the item label may be, for example, generating a packaging order before packaging the item, wherein the packaging order has the item attribute, the delivery location and the receiving location as input. The item attributes may further include item type, storage conditions, shipping conditions, and the like. Seafood, for example, requires ice chest storage.
102: and checking whether the target article meets warehousing conditions or not based on the article information, and generating a warehousing request when the warehousing conditions are met, wherein the warehousing request carries the article information.
And checking each article to be warehoused to ensure the accuracy of warehousing. In the embodiment, the warehousing condition of the target article is inspected, the article information is compared with the warehousing condition, and the article which does not meet the warehousing condition is removed or an alarm is sent out. And further generating a warehousing request for the target articles meeting the warehousing conditions, and waiting for warehousing and storing.
Specifically, whether the target article meets the warehousing specification requirement is detected according to article information; and when the target article meets the requirement of the warehousing specification, comparing the article attribute of the target article with the pre-stored article attribute, and when the article attribute of the target article is consistent with the pre-stored article attribute, defining that the warehousing condition is met.
The warehousing condition is input by a manager in advance to form a comparison rule and is stored in the processor, namely the warehousing specification requirement. For example, the warehousing conditions may include a size minimum limit, a maximum limit, a weight limit, and the like.
In the embodiment, further, when the object information detects that the target object meets the requirement of the warehousing specification, the object attribute is checked. In the processor, article attributes corresponding to different target articles are prestored. Illustratively, when the target object is in a packaging stage, the object property of the target object is integrated in the service platform, and is also assigned to the object tag, the object tag corresponds to the identification code, and the identification code is bound with the object tag and is sent to the processor. And (4) sticking the printed article label on the target article. Therefore, in the stage of warehousing verification, the article information is obtained by reading the article tags, the article attributes in the article information are compared with the pre-stored article attributes, and when the article attributes are different from the pre-stored article attributes, the condition that the article is warehoused wrongly is indicated, and prompt alarm can be given. And when the requirement of the warehousing specification is met, the comparison of the attributes of the articles is also met, the warehousing condition is indicated to be met, and a warehousing request is generated.
103: and inputting the warehousing request as an input feature into a pre-trained warehousing model to output matched storage conditions, wherein the storage conditions comprise a storage environment and a storage space.
In an embodiment, the storage request is generated by a processor, and the storage request may be sent to a unit responsible for storage condition calculation, or a server separately calculating storage conditions is provided, where a storage model is trained in advance, and when the storage request is received, storage condition calculation is started. For example, if the article information in the corresponding warehousing request is a frozen product, the output storage condition is necessarily a refrigerated storage section.
The warehousing model is obtained by training in the following mode:
acquiring historical article information and historical storage places corresponding to the historical article information respectively; selecting historical article information corresponding to a first preset proportion from the historical article information as model input data, and selecting historical article information corresponding to a second preset proportion as training input data; selecting a historical storage place corresponding to model input data as model output data, and selecting a historical storage place corresponding to the training input data as training output data; and establishing a training model according to the model input data and the model output data, and correcting the training model according to the training input data and the training output data to obtain a warehousing model.
Illustratively, 100 groups of historical item information are selected, and correspondingly, 100 groups of historical storage places corresponding to the item information are selected. The first preset proportion and the second preset proportion are proportion values considered to be set according to actual conditions, such as two thirds, thirty percent, twenty percent and the like. The first preset proportion and the second preset proportion are relative, in the embodiment, the first preset proportion plus the second preset proportion is equal to 1, that is, the number of samples of the first preset proportion plus the number of samples of the second preset proportion is equal to the total sample capacity. In the embodiment, 100 groups of historical item information and 100 groups of historical storage locations are taken as the total sample capacity, if the first preset proportion is seventy percent, and the second preset proportion is thirty percent, 70 groups of historical item information are selected as model input data according to the first preset proportion, 70 groups of historical storage locations are selected as model output data, and a training model is constructed. In addition, 30 sets of historical item information and historical storage locations are used as correction data to correct the constructed training model, specifically, thirty sets of historical item information are used as input data to be input into the training model, and whether the obtained storage locations correspond to thirty sets of historical storage locations is detected, so that error adjustment and correction are performed.
104: and acquiring the current idle storage capacity, obtaining a storage place corresponding to the target article according to the current idle storage capacity and the storage condition, and binding the storage place with the article information.
In the embodiment, the current free storage capacity refers to a free storage interval of the entire storage area, and if the storage area is, for example, a storage cabinet, the current free storage capacity is the number of free storage cabinets and corresponds to the location information of the free storage cabinets. Specifically, the current idle storage capacity is obtained, wherein the current idle storage capacity comprises storage intervals corresponding to different article attributes; and selecting a corresponding storage interval from the current idle storage capacity according to the storage condition, and distributing a corresponding storage place according to a preset distribution rule. For example, if the object attribute corresponds to that the target object is a frozen food, the object attribute corresponds to a storage interval for storing the frozen food, that is, a storage interval for storing the frozen food needs to be selected from the current free storage capacity. And when a plurality of corresponding storage sections exist, storing the frozen food according to other auxiliary storage rules. If the target object can be stored in the remaining three storage sections, and the preset storage rule is that the target object is stored from top to bottom, the target object is stored in the uppermost section of the remaining three storage sections.
Example two
Fig. 2 illustrates another article warehousing method according to an embodiment of the present application, and as illustrated in fig. 2, the article warehousing method includes:
201: the method comprises the steps of collecting image data of a conveying belt, and collecting three-dimensional image data of an article when the article is detected to be on the conveying belt according to the image data.
In an embodiment, the article warehousing system includes a conveyor belt for transporting the target articles from one location to another, for subsequent storage of the target articles to the storage area by the transport cart. The articles to be put in storage need to be placed on the conveying belt, so that the conveying belt is subjected to real-time image acquisition, and whether the articles exist on the current conveying belt can be known through comparison and analysis of image data. When an item is present, the item is further subjected to three-dimensional image data scanning.
202: and detecting whether an identification code on the surface of the article is identified or not according to the three-dimensional image data, defining the article as a target article when the identification code is identified, and acquiring the article attribute, the delivery place and the receiving place of the target article according to the identification code.
The outer package of the target object is provided with an object label, the object label is provided with a unique identification code, the identification code can be acquired through image acquisition, for example, the identification code is a string of characters or a string of numbers, and the object information corresponding to the identification code can be acquired after the identification code is acquired.
203: and acquiring the object size of the target object according to the three-dimensional image data.
According to the three-dimensional image data, the three-dimensional outline of the target object can be obtained, and therefore the size of the object can be obtained. The article information is configured based on the article size, the article attribute, and the like.
204: and checking whether the target article meets warehousing conditions or not based on the article information, and generating a warehousing request when the warehousing conditions are met, wherein the warehousing request carries the article information.
205: and inputting the warehousing request as an input feature into a pre-trained warehousing model to output matched storage conditions, wherein the storage conditions comprise a storage environment and a storage space.
206: and acquiring the current idle storage capacity, obtaining a storage place corresponding to the target article according to the current idle storage capacity and the storage condition, and binding the storage place with the article information.
207: and sending the storage place and the article information to a transport vehicle so that the transport vehicle extracts the target article according to the article information and transports the target article to the storage place.
After the storage location of the target object is confirmed, the storage location and the object information are sent to a transport vehicle, the transport vehicle has a positioning function, a path can be automatically planned for transport, and the target object can be transported to the storage location from one position.
EXAMPLE III
Fig. 3 shows an article warehousing device provided by an embodiment of the present application, and referring to fig. 3, the article warehousing device includes a target article identification module 301, a warehousing condition judgment module 302, a storage condition generation module 303, and a storage location acquisition module 304, where the target article identification module 301 is configured to identify a target article and acquire article information of the target article, where the article information includes an article size, an article attribute, a delivery location, and a receiving location; a warehousing condition judgment module 302, configured to check whether the target article meets warehousing conditions based on the article information, and generate a warehousing request when the warehousing conditions are met, where the warehousing request carries the article information; a storage condition generating module 303, configured to input the warehousing request as an input feature into a pre-trained warehousing model to output a matching storage condition, where the storage condition includes a storage environment and a storage space; a storage location obtaining module 304, configured to obtain a current free storage capacity, obtain a storage location corresponding to a target item according to the current free storage capacity and the storage condition, and bind the storage location with item information.
Specifically, in the target item identification module 301, identifying a target item and acquiring item information of the target item includes: acquiring three-dimensional image data of the target object, and acquiring the object size of the target object according to the three-dimensional image data; and reading the item label on the target item, and acquiring the item attribute, the delivery place and the receiving place.
As another example, in the target item identification module 301, identifying a target item and acquiring item information of the target item includes: acquiring image data of a conveying belt, and acquiring three-dimensional image data of an article when the article is detected to be on the conveying belt according to the image data; detecting whether an identification code on the surface of the article is identified according to the three-dimensional image data, defining the article as a target article when the identification code is identified, and acquiring article attributes, a delivery place and a receiving place of the target article according to the identification code; and acquiring the article size of the article according to the three-dimensional image data.
As a preferable real-time manner, the checking, by the warehousing condition judgment module 302, whether the target item meets the warehousing condition based on the item information includes: detecting whether the target article meets the warehousing specification requirement or not according to the article information; and when the target article meets the requirement of the warehousing specification, comparing the article attribute of the target article with the pre-stored article attribute, and when the article attribute of the target article is consistent with the pre-stored article attribute, defining that the warehousing condition is met.
In the embodiment, the warehousing model is obtained by training in the following way: acquiring historical article information and historical storage places corresponding to the historical article information respectively; selecting historical article information corresponding to a first preset proportion from the historical article information as model input data, and selecting historical article information corresponding to a second preset proportion as training input data; selecting a historical storage place corresponding to model input data as model output data, and selecting a historical storage place corresponding to the training input data as training output data; and establishing a training model according to the model input data and the model output data, and correcting the training model according to the training input data and the training output data to obtain a warehousing model.
Preferably, the obtaining module 304 for a storage location obtains a current free storage capacity, and obtains a storage location corresponding to the target item according to the current free storage capacity and the storage condition, and includes: acquiring current idle storage capacity, wherein the current idle storage capacity comprises storage intervals corresponding to different article attributes; and selecting a corresponding storage interval from the current idle storage capacity according to the storage condition, and distributing a corresponding storage place according to a preset distribution rule.
Further, embodiments may further include a delivery information sending module 305 for sending the storage location and the item information to the delivery vehicle, so that the delivery vehicle extracts the target item according to the item information and delivers the target item to the storage location.
As shown in fig. 4, an embodiment of the present application further provides an article warehousing device, including: a memory 401 and one or more processors 402; the memory 401 is used for storing one or more programs; when executed by the one or more processors 402, cause the one or more processors to implement an item warehousing method as described herein.
An embodiment of the present application further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are executed by a computer processor to perform the method for warehousing articles provided in the foregoing embodiment, and the method for warehousing articles includes: identifying a target item, and acquiring item information of the target item, wherein the item information comprises an item size, an item attribute, a delivery place and a receiving place; checking whether the target article meets warehousing conditions or not based on the article information, and generating a warehousing request when the warehousing conditions are met, wherein the warehousing request carries the article information; inputting the warehousing request as an input feature into a pre-trained warehousing model to output matched storage conditions, wherein the storage conditions comprise a storage environment and a storage space; and acquiring the current idle storage capacity, obtaining a storage place corresponding to the target article according to the current idle storage capacity and the storage condition, and binding the storage place with the article information.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system connected to the first computer system through a network (such as the internet). The second computer system may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided in the embodiments of the present application and containing computer-executable instructions is not limited to the article warehousing method described above, and may also execute related operations in the article warehousing method provided in any embodiment of the present application.
The article warehousing device, the equipment and the storage medium provided in the above embodiments may execute the article warehousing method provided in any embodiment of the present application, and the technical details not described in detail in the above embodiments may refer to the article warehousing method provided in any embodiment of the present application.
The foregoing is considered as illustrative of the preferred embodiments of the invention and the technical principles employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.
Claims (10)
1. An article warehousing method, characterized by comprising:
identifying a target item, and acquiring item information of the target item, wherein the item information comprises an item size, an item attribute, a delivery place and a receiving place;
checking whether the target article meets warehousing conditions or not based on the article information, and generating a warehousing request when the warehousing conditions are met, wherein the warehousing request carries the article information;
inputting the warehousing request as an input feature into a pre-trained warehousing model to output matched storage conditions, wherein the storage conditions comprise a storage environment and a storage space;
and acquiring the current idle storage capacity, obtaining a storage place corresponding to the target article according to the current idle storage capacity and the storage condition, and binding the storage place with the article information.
2. The method according to claim 1, wherein the identifying a target item and acquiring item information of the target item includes:
acquiring three-dimensional image data of the target object, and acquiring the object size of the target object according to the three-dimensional image data;
and reading the item label on the target item, and acquiring the item attribute, the delivery place and the receiving place.
3. The method according to claim 1, wherein the identifying a target item and acquiring item information of the target item includes:
acquiring image data of a conveying belt, and acquiring three-dimensional image data of an article when the article is detected to be on the conveying belt according to the image data;
detecting whether an identification code on the surface of the article is identified according to the three-dimensional image data, defining the article as a target article when the identification code is identified, and acquiring article attributes, a delivery place and a receiving place of the target article according to the identification code;
and acquiring the object size of the target object according to the three-dimensional image data.
4. The article warehousing method according to claim 1, wherein the checking whether the target article satisfies warehousing conditions based on the article information includes:
detecting whether the target article meets the warehousing specification requirement or not according to the article information;
and when the target article meets the requirement of the warehousing specification, comparing the article attribute of the target article with the pre-stored article attribute, and when the article attribute of the target article is consistent with the pre-stored article attribute, defining that the warehousing condition is met.
5. The method according to claim 1, wherein the warehousing model is trained by:
acquiring historical article information and historical storage places corresponding to the historical article information respectively;
selecting historical article information corresponding to a first preset proportion from the historical article information as model input data, and selecting historical article information corresponding to a second preset proportion as training input data;
selecting a historical storage place corresponding to model input data as model output data, and selecting a historical storage place corresponding to the training input data as training output data;
and establishing a training model according to the model input data and the model output data, and correcting the training model according to the training input data and the training output data to obtain a warehousing model.
6. The method for warehousing the articles according to claim 1, wherein obtaining a current free storage capacity, and obtaining a storage location corresponding to the target article according to the current free storage capacity and the storage condition comprises:
acquiring current idle storage capacity, wherein the current idle storage capacity comprises storage intervals corresponding to different article attributes;
and selecting a corresponding storage interval from the current idle storage capacity according to the storage condition, and distributing a corresponding storage place according to a preset distribution rule.
7. The method according to any one of claims 1 to 6, further comprising:
and sending the storage place and the article information to a transport vehicle so that the transport vehicle extracts the target article according to the article information and transports the target article to the storage place.
8. An article warehousing device, characterized by comprising:
a target item identification module: the system is used for identifying a target item and acquiring item information of the target item, wherein the item information comprises an item size, an item attribute, a delivery place and a receiving place;
a warehousing condition judgment module: the system is used for detecting whether the target article meets warehousing conditions or not based on the article information, and generating a warehousing request when the warehousing conditions are met, wherein the warehousing request carries the article information;
a storage condition generation module: the storage system is used for inputting the warehousing request as an input feature into a pre-trained warehousing model so as to output matched storage conditions, wherein the storage conditions comprise a storage environment and a storage space;
a storage location acquisition module: the system is used for acquiring the current free storage capacity, obtaining a storage place corresponding to a target article according to the current free storage capacity and the storage condition, and binding the storage place with article information.
9. An article warehousing device, characterized by comprising: a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method of warehousing items as recited in any of claims 1-7.
10. A storage medium containing computer-executable instructions for performing the method of warehousing items as recited in any one of claims 1-7 when executed by a computer processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110699703.8A CN113506055A (en) | 2021-06-23 | 2021-06-23 | Article warehousing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110699703.8A CN113506055A (en) | 2021-06-23 | 2021-06-23 | Article warehousing method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113506055A true CN113506055A (en) | 2021-10-15 |
Family
ID=78010914
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110699703.8A Pending CN113506055A (en) | 2021-06-23 | 2021-06-23 | Article warehousing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113506055A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114913926A (en) * | 2022-05-31 | 2022-08-16 | 青岛中康原能细胞生物科技有限公司 | Cell warehousing method, device and equipment |
| CN115140471A (en) * | 2022-06-29 | 2022-10-04 | 山东西部智能科技有限公司 | Article management method, system, equipment and computer readable storage medium |
| CN115375221A (en) * | 2022-07-12 | 2022-11-22 | 北京三维天地科技股份有限公司 | Sample storage system |
| CN116167689A (en) * | 2022-12-16 | 2023-05-26 | 江苏东衡智能科技有限公司 | Battery storage logistics safety control method and system |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105701631A (en) * | 2016-01-06 | 2016-06-22 | 北京京东尚科信息技术有限公司 | Commodity warehousing method and warehouse management system |
| CN107341629A (en) * | 2017-05-24 | 2017-11-10 | 国网北京市电力公司 | Bay assignment method and device |
| CN109658021A (en) * | 2018-11-08 | 2019-04-19 | 国科恒泰（北京）医疗科技股份有限公司 | Determine the method and device of commodity locations |
| CN109784805A (en) * | 2018-12-13 | 2019-05-21 | 平安科技（深圳）有限公司 | It receives management method, device, equipment and storage medium |
| CN110348789A (en) * | 2019-07-12 | 2019-10-18 | 黑梭智慧技术(北京)有限公司 | Method and apparatus based on unmanned dispensing device dispatching cargo |
| CN110599067A (en) * | 2019-09-27 | 2019-12-20 | 珠海格力电器股份有限公司 | Storage allocation method, storage medium and electronic equipment |
| CN110910059A (en) * | 2019-11-05 | 2020-03-24 | 广州穗能通综合能源有限责任公司 | Warehousing control method, device and system for power equipment and computer equipment |
| CN111142598A (en) * | 2019-12-30 | 2020-05-12 | 广州享药户联优选科技有限公司 | Internal environment control method and device of intelligent medicine chest |
| CN111415087A (en) * | 2020-03-17 | 2020-07-14 | 华润电力技术研究院有限公司 | Partitioned storage device, method, equipment and medium for coal storage of coal yard |
| CN111709687A (en) * | 2020-06-18 | 2020-09-25 | 上海明略人工智能(集团)有限公司 | Article warehousing system and article warehousing method |
| WO2021068645A1 (en) * | 2019-10-09 | 2021-04-15 | 北京京东振世信息技术有限公司 | Method and apparatus for determining warehousing storage location, electronic device, and storage medium |
| CN112950103A (en) * | 2019-12-10 | 2021-06-11 | 菜鸟智能物流控股有限公司 | Logistics object storage device, management method thereof, electronic device and computer-readable storage medium |
-
2021
- 2021-06-23 CN CN202110699703.8A patent/CN113506055A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105701631A (en) * | 2016-01-06 | 2016-06-22 | 北京京东尚科信息技术有限公司 | Commodity warehousing method and warehouse management system |
| CN107341629A (en) * | 2017-05-24 | 2017-11-10 | 国网北京市电力公司 | Bay assignment method and device |
| CN109658021A (en) * | 2018-11-08 | 2019-04-19 | 国科恒泰（北京）医疗科技股份有限公司 | Determine the method and device of commodity locations |
| CN109784805A (en) * | 2018-12-13 | 2019-05-21 | 平安科技（深圳）有限公司 | It receives management method, device, equipment and storage medium |
| CN110348789A (en) * | 2019-07-12 | 2019-10-18 | 黑梭智慧技术(北京)有限公司 | Method and apparatus based on unmanned dispensing device dispatching cargo |
| CN110599067A (en) * | 2019-09-27 | 2019-12-20 | 珠海格力电器股份有限公司 | Storage allocation method, storage medium and electronic equipment |
| WO2021068645A1 (en) * | 2019-10-09 | 2021-04-15 | 北京京东振世信息技术有限公司 | Method and apparatus for determining warehousing storage location, electronic device, and storage medium |
| CN110910059A (en) * | 2019-11-05 | 2020-03-24 | 广州穗能通综合能源有限责任公司 | Warehousing control method, device and system for power equipment and computer equipment |
| CN112950103A (en) * | 2019-12-10 | 2021-06-11 | 菜鸟智能物流控股有限公司 | Logistics object storage device, management method thereof, electronic device and computer-readable storage medium |
| CN111142598A (en) * | 2019-12-30 | 2020-05-12 | 广州享药户联优选科技有限公司 | Internal environment control method and device of intelligent medicine chest |
| CN111415087A (en) * | 2020-03-17 | 2020-07-14 | 华润电力技术研究院有限公司 | Partitioned storage device, method, equipment and medium for coal storage of coal yard |
| CN111709687A (en) * | 2020-06-18 | 2020-09-25 | 上海明略人工智能(集团)有限公司 | Article warehousing system and article warehousing method |
Non-Patent Citations (2)
| Title |
|---|
| 刘翔: "《数据仓库与数据挖掘技术》", 31 August 2005, 上海交通大学出版社, pages: 229 - 231 * |
| 赵佳妮等: "《仓储配送管理》", 31 August 2015, 国防工业出版社, pages: 65 - 67 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114913926A (en) * | 2022-05-31 | 2022-08-16 | 青岛中康原能细胞生物科技有限公司 | Cell warehousing method, device and equipment |
| CN114913926B (en) * | 2022-05-31 | 2023-08-22 | 青岛瑞源细胞生物科技开发有限公司 | Cell warehousing method, device and equipment |
| CN115140471A (en) * | 2022-06-29 | 2022-10-04 | 山东西部智能科技有限公司 | Article management method, system, equipment and computer readable storage medium |
| CN115140471B (en) * | 2022-06-29 | 2024-01-02 | 山东西部智能科技有限公司 | Article management method, system, equipment and computer readable storage medium |
| CN115375221A (en) * | 2022-07-12 | 2022-11-22 | 北京三维天地科技股份有限公司 | Sample storage system |
| CN116167689A (en) * | 2022-12-16 | 2023-05-26 | 江苏东衡智能科技有限公司 | Battery storage logistics safety control method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110414638B (en) | Three-dimensional warehouse management system and management method based on RFID | |
| CN113506055A (en) | Article warehousing method and device | |
| US7602288B2 (en) | Method for slap-and-ship RFID labeling | |
| US20160117631A1 (en) | Orphaned item identification | |
| US20180268348A1 (en) | Automated Receipt of Inbound Parcels and Items | |
| CN113498524A (en) | Delivery system | |
| US11948124B2 (en) | Shipment record systems and methods | |
| US20050231370A1 (en) | ID issue management system, article information management system and ID issue management method | |
| JP2019534219A (en) | Identification and tracking of bundled units | |
| EP3549078A1 (en) | Process for rfid certification of carton content | |
| CN105531715A (en) | Detecting item interaction and movement | |
| US20220129836A1 (en) | Vision product inference based on package detect and brand classification with active learning | |
| CN103229199A (en) | Dynamic route planning | |
| CN110969396A (en) | Automatic order picking method and system | |
| JP2017019586A (en) | Physical distribution system and physical distribution management method | |
| US11783606B2 (en) | Delivery system | |
| CN112824990A (en) | Cargo information detection method and system, robot and processing terminal | |
| KR102518380B1 (en) | Outgoing packing video management method and system using invoice information recognition | |
| US10579964B1 (en) | Method, apparatus and system for goods replenishment | |
| US20160117630A1 (en) | Orphaned package identification | |
| CN114626780A (en) | Warehouse-out operation method, electronic equipment, medium and product | |
| CN110723454B (en) | Large package sorting method and device, electronic equipment and storage medium | |
| CN114154863A (en) | Container cargo loading quality detection method, server, terminal and storage medium | |
| US9972044B1 (en) | Sending custom greeting cards with gifts in a high velocity environment | |
| US20230376884A1 (en) | Package location services and routing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |