A digital twin-driven warehouse visualization platform risk control system

Abstract

The present invention relates to a digital twin-driven warehouse visualization platform risk control system, which belongs to the field of data processing. Among them, the system includes a warehouse visualization platform construction module, a warehouse planning module, and a warehouse risk control module; the warehouse visualization platform construction module includes a data acquisition module, a digital twin model construction module, and a platform construction module, the data acquisition module is used to collect warehouse visualization platform construction data, the digital twin model construction module is used to construct a multivariate digital twin group based on the warehouse visualization platform construction data, and the platform construction module is used to build a warehouse visualization platform through a multivariate digital twin group; the warehouse planning module is used to plan the warehouse route for the warehoused goods based on the warehouse visualization platform; the warehouse risk control module is used to monitor the contact risk information of the goods during the warehouse and transportation process based on the warehouse visualization platform. The present invention realizes the reasonable construction of a visualization platform for scientific management of warehoused goods and reduces the risks during the storage and transportation of goods.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and specifically relates to a warehouse visualization platform risk control system driven by digital twins. Background Art

[0002] The warehouse visualization platform is a technical platform that uses advanced technology to visualize the warehouse. Based on technologies such as big data analysis, IoT sensors, cloud computing, and data visualization, it integrates various information in the warehouse into an intuitive dashboard so that managers can monitor, analyze, and optimize warehouse activities in real time. However, the existing warehouse visualization platform risk control measures are still imperfect, and the risk monitoring of the mutual influence between stored goods and the transportation process of goods is insufficient. Once some goods are damaged or leaked, it is easy to affect the surrounding goods.

[0003] Digital twin is an emerging technology that can simulate specific affairs of the physical world based on the digital model of a physical entity. It dynamically presents the past and current behaviors and processes of a physical entity in a digital form, thereby achieving effective monitoring and management of the physical entity. Summary of the invention

[0004] In order to solve the above-mentioned problems existing in the prior art, the present invention provides a warehouse visualization platform risk control system driven by a digital twin.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A digital twin-driven warehouse visualization platform risk control system, the warehouse visualization platform risk control system comprising a warehouse visualization platform building module, a warehouse entry planning module, and a warehouse risk control module;

[0007] The warehouse visualization platform construction module includes a data acquisition module, a digital twin model construction module, and a platform construction module. The data acquisition module is used to collect warehouse visualization platform construction data. The digital twin model construction module is used to construct a multivariate digital twin group based on the warehouse visualization platform construction data. The platform construction module is used to build a warehouse visualization platform through the multivariate digital twin group.

[0008] The warehousing planning module is used to plan warehousing routes for warehousing goods based on the warehousing visualization platform;

[0009] The warehouse risk control module is used to monitor the contact risk information of goods during warehousing and transportation based on the warehouse visualization platform, and the contact risk information includes high-risk information and no-risk information.

[0010] Preferably, the warehouse visualization platform construction data includes warehouse design data and warehouse real-time data. The warehouse design data is used to reflect the warehouse geometric model situation, and the warehouse real-time data is used to reflect the current status of the warehouse. The warehouse design data includes the overall warehouse design drawing, cargo pallets, cargo locations, warehouse boundaries, and warehouse fixed equipment. The warehouse real-time data includes handling equipment and handling equipment operation routes, existing goods, conveying equipment and conveying equipment operation routes; the multi-element digital twin group includes warehouse physical entities, warehouse virtual models, twin data, warehouse cargo information, and information links.

[0011] Preferably, the warehouse virtual model is a virtual model constructed based on the data of the warehouse visualization platform; the twin data is data information in the warehouse operation process, including cargo transportation information, equipment movement information, cargo entry and exit information, real-time sensor data, historical operation data, workload data, and maintenance record data; the stored cargo information includes basic information of stored cargo and stored cargo coding. The basic information of stored cargo includes cargo type, cargo warehousing time, cargo warehousing floor, cargo warehousing location, cargo storage location, and cargo storage precautions. The stored cargo coding is obtained based on the basic information of stored cargo. The stored cargo coding includes warehousing cargo coding and in-warehouse cargo coding. The information link is the information transmission and parsing method of the warehouse visualization platform, which is realized by RFID tag technology.

[0012] Preferably, the coding rule of the warehouse goods coding is:

[0013] Based on the basic information of the stored goods, the storage floor number, storage cargo position number, storage storage location number, storage time number, cargo type number and special number of the stored goods are obtained. The cargo type number represents the cargo type of the stored goods, including liquid cargo, flammable cargo and corrosive cargo. The special number represents the storage precautions of the goods, including waterproof cargo, easily ignited cargo and easily corrosive cargo. The cargo type number is uppercase English letters, and the special number is lowercase English letters. The mutually exclusive cargo type number and special number are represented by the same group of uppercase and lowercase letters, which are defined as mutually exclusive codes. The storage floor number, the storage cargo position number, the storage storage location number, the storage time number, the cargo type number and the special number are combined in sequence to generate the stored goods code and construct a stored goods RFID tag.

[0014] Preferably, the planning of the warehousing route includes:

[0015] Dividing the warehouse visualization platform into warehouse grids, and marking the warehouse grids where obstacles exist as inaccessible grids;

[0016] The RFID tag of the stored goods is read by an RFID reader / writer, and the goods corresponding to the in-warehouse goods code having the mutually exclusive code with the warehoused goods code are marked as mutually exclusive goods, and the storage grid where the mutually exclusive goods are located and the adjacent storage grids are marked as the inaccessible grids;

[0017] Mark the remaining storage grids as access grids;

[0018] Setting a warehouse entrance grid and a terminal grid, wherein the terminal grid is the storage grid where the goods storage position of the goods entering the warehouse is located;

[0019] Obtaining a first cost function from the warehouse entrance grid to the pass grid and a second cost function from the pass grid to the terminal grid;

[0020] Obtaining a total cost function based on the first cost function and the second cost function, wherein the total cost function is the sum of the first cost function and the second cost function;

[0021] Based on the total cost function, the warehouse entry route is planned by adjusting the interference threat probability weight, the path length cost weight and the smoothness cost weight.

[0022] Preferably, the expression of the first cost function is h s，n =h s，n-1 +d n，n-1 +p s，n +C s，n , n = 1, 2, ..., N, where h s,n is the first cost function from the entrance grid to the nth pass grid, h s,n-1 is the first cost function from the entrance grid to the n-1th pass grid, d n,n-1 is the distance from the nth pass grid to the n-1th pass grid, p s,n is the interference threat probability from the entrance grid to the nth pass grid, C s,n is the smoothness cost from the entrance grid to the nth pass grid, N is the number of pass grids; the expression of the second cost function is Among them, h n,e is the second cost function from the nth passing grid to the end grid, p n,e is the interference threat probability from the nth pass grid to the end grid, L n,e is the path length cost from the nth pass grid to the end grid, C n,e is the smoothness cost from the nth passing grid to the end grid, p sum is the average interference threat probability from all passing grids to the end grid, L maxis the maximum path length cost from all passing grids to the end grid, C max is the maximum smoothness cost from all pass grids to the end grid, ω1 is the interference threat probability weight, ω2 is the path length cost weight, and ω3 is the smoothness cost weight.

[0023] Preferably, the warehouse risk control module specifically includes:

[0024] Divide the virtual handling equipment used to represent the goods transported into the warehouse in the warehouse visualization platform into triangular facets and obtain the vertex coordinates of the triangular facets, and calculate the virtual handling equipment vector based on the vertex coordinates of the triangular facets;

[0025] Constructing bounding boxes for the triangular facets, and representing the relationship between the bounding boxes through a covariance matrix;

[0026] An impassable grid bounding box and an impassable grid covariance matrix of the impassable grid are obtained, and the orientation and size of the bounding box and the impassable grid bounding box are obtained by solving the eigenvalues ​​and eigenvectors of the covariance matrix and the impassable grid covariance matrix, so as to obtain a bounding box distance between the bounding box and the impassable grid bounding box, and when the bounding box distance is less than or equal to a preset bounding box distance threshold, the high-risk information is output, and when the bounding box distance is greater than the preset bounding box distance threshold, the risk-free information is output.

[0027] A digital twin-driven warehouse visualization platform risk control method, used to execute the above-mentioned warehouse visualization platform risk control system, comprising:

[0028] Collecting warehouse visualization platform construction data, constructing a multivariate digital twin group based on the warehouse visualization platform construction data, and building a warehouse visualization platform through the multivariate digital twin group;

[0029] Planning a warehousing route for incoming goods based on the warehousing visualization platform;

[0030] The contact risk information of goods during warehousing and transportation is monitored based on the warehouse visualization platform, and the contact risk information includes high-risk information and no-risk information.

[0031] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned warehouse visualization platform risk control system is implemented.

[0032] A storage medium containing computer executable instructions, which are used to execute the above-mentioned warehouse visualization platform risk control system when executed by a computer processor.

[0033] The beneficial effects of the present invention are:

[0034] (1) By building a warehouse visualization platform, various warehouse information is integrated into an intuitive dashboard so that managers can monitor, analyze and optimize warehouse activities in real time, plan the warehouse routes of goods reasonably, monitor the contact risk information of goods during warehousing and transportation, and avoid the adverse effects of goods leakage or damage on surrounding goods;

[0035] (2) Using RFID tag technology to read the storage cargo codes, intuitively display cargo information and precautions during storage and transportation, while preventing cargo from being too close to each other;

[0036] (3) By defining mutually exclusive codes, mutually exclusive commodity type codes and special codes are represented by the same set of uppercase and lowercase letters, making the mutually exclusive relationship between commodities clear at a glance;

[0037] (4) By marking the storage grid where mutually exclusive goods are located and the adjacent storage grids as inaccessible grids, and flexibly designing the goods entry routes based on the inaccessible grids, contact between mutually exclusive goods can be avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0039] Figure 1 This is a flow chart of the steps of a digital twin-driven warehouse visualization platform risk control system of the present invention. DETAILED DESCRIPTION

[0040] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0041] The working principle and use process of the present invention:

[0042] See also Figure 1 , a digital twin-driven warehouse visualization platform risk control system, including a warehouse visualization platform building module, a warehouse entry planning module, and a warehouse risk control module:

[0043] The warehouse visualization platform construction module includes a data acquisition module, a digital twin model construction module, and a platform construction module. The data acquisition module is used to collect warehouse visualization platform construction data. The digital twin model construction module is used to construct a multivariate digital twin group based on the warehouse visualization platform construction data. The platform construction module is used to build a warehouse visualization platform through the multivariate digital twin group.

[0044] The warehousing planning module is used to plan warehousing routes for warehousing goods based on the warehousing visualization platform;

[0045] The warehouse risk control module is used to monitor the contact risk information of goods during warehousing and transportation based on the warehouse visualization platform, and the contact risk information includes high-risk information and no-risk information.

[0046] In this embodiment, the warehouse visualization platform construction data includes warehouse design data and warehouse real-time data. The warehouse design data is used to reflect the warehouse geometric model, and the warehouse real-time data is used to reflect the current status of the warehouse. The warehouse design data includes but is not limited to the overall warehouse design drawing, cargo pallets, cargo locations, warehouse boundaries, and warehouse fixed equipment. The warehouse real-time data includes but is not limited to handling equipment and handling equipment operation routes, existing goods, conveying equipment and conveying equipment operation routes; the multi-element digital twin group includes warehouse physical entities, warehouse virtual models, twin data, warehouse cargo information, and information links.

[0047] In this embodiment, the warehouse virtual model is a virtual model constructed based on the data of the warehouse visualization platform; the twin data is data information in the warehouse operation process, including but not limited to cargo transportation information, equipment movement information, cargo in and out of the warehouse information, real-time sensor data, historical operation data, workload data, and maintenance record data; the stored cargo information includes basic information of stored cargo and stored cargo codes. The basic information of stored cargo includes but is not limited to cargo type, cargo warehousing time, cargo warehousing floor, cargo warehousing location, cargo storage location, and cargo storage precautions. The stored cargo code is obtained based on the basic information of stored cargo, and the stored cargo code includes warehousing cargo code and in-warehouse cargo code; the information link is the information transmission and analysis method of the warehouse visualization platform, which is realized through RFID tag technology.

[0048] In this embodiment, the coding rule of the warehouse goods coding is:

[0049] Based on the basic information of the stored goods, the storage floor number, storage cargo position number, storage storage location number, storage time number, cargo type number and special number of the stored goods are obtained. The cargo type number represents the cargo type of the stored goods, including but not limited to liquid cargo, flammable cargo and corrosive cargo. The special number represents the storage precautions of the cargo, including but not limited to waterproof cargo, easily ignited cargo and easily corrosive cargo. The cargo type number is uppercase English letters, and the special number is lowercase English letters. The mutually exclusive cargo type number and special number are represented by the same group of uppercase and lowercase letters, which are defined as mutually exclusive codes. For example, the liquid cargo number is A, and the waterproof cargo number is a. The storage floor number, the storage cargo position number, the storage storage location number, the storage time number, the cargo type number and the special number are combined in sequence to generate the storage cargo code and construct the storage cargo RFID tag, so as to intuitively display the cargo information and precautions in the storage and transportation process, and at the same time avoid the cargo that is easy to affect each other from being too close.

[0050] In this embodiment, planning a warehousing route for warehousing goods based on the warehousing visualization platform can be implemented through the following steps:

[0051] Dividing the warehouse visualization platform into warehouse grids, and marking the warehouse grids where obstacles exist as inaccessible grids;

[0052] The RFID tag of the stored goods is read by an RFID reader / writer, and the goods corresponding to the in-warehouse goods code having the mutually exclusive code with the warehoused goods code are marked as mutually exclusive goods, and the storage grid where the mutually exclusive goods are located and the adjacent storage grids are marked as the inaccessible grids;

[0053] Mark the remaining storage grids as access grids;

[0054] Setting a warehouse entrance grid and a terminal grid, wherein the terminal grid is the storage grid where the goods storage position of the goods entering the warehouse is located;

[0055] Obtain a first cost function from the warehouse entrance grid to the pass grid and a second cost function from the pass grid to the terminal grid. The expression of the first cost function is h s，n =h s，n-1 +d n，n-1 +p s，n +C s,n ,n=1,2,...,Nwhere h s,n is the first cost function from the entrance grid to the nth pass grid, h s,n-1 is the first cost function from the entrance grid to the n-1th pass grid, dn,n-1 is the distance from the nth pass grid to the n-1th pass grid, p s,n is the interference threat probability from the entrance grid to the nth pass grid, C s,n is the smoothness cost from the entrance grid to the nth pass grid, N is the number of pass grids; the expression of the second cost function is Among them, h n,e is the second cost function from the nth passing grid to the end grid, p n,e is the interference threat probability from the nth pass grid to the end grid, L n,e is the path length cost from the nth pass grid to the end grid, C n,e is the smoothness cost from the nth passing grid to the end grid, p sum is the average interference threat probability from all passing grids to the end grid, L max is the maximum path length cost from all passing grids to the end grid, C max is the maximum value of the smoothness cost from all passing grids to the end grid, ω1 is the interference threat probability weight, ω2 is the path length cost weight, and ω3 is the smoothness cost weight;

[0056] Obtaining a total cost function based on the first cost function and the second cost function, wherein the total cost function is the sum of the first cost function and the second cost function;

[0057] Based on the total cost function, the warehouse entry route is planned by adjusting the interference threat probability weight, the path length cost weight and the smoothness cost weight. When it is necessary to select a route with less interference threat, the interference threat probability weight is increased; when it is necessary to select a route with less path length cost, the path length cost weight is increased; when it is necessary to select a route with less smoothness cost, the smoothness cost weight is increased.

[0058] In this embodiment, monitoring the contact risk information of goods during warehousing and transportation based on the warehouse visualization platform can be implemented through the following steps:

[0059] The virtual handling equipment used to represent the goods transported into the warehouse in the warehouse visualization platform is divided into triangular facets and the vertex coordinates of the triangular facets are obtained. The virtual handling equipment vector is calculated based on the vertex coordinates of the triangular facets. The calculation formula is: Where T is the virtual handling device vector, m is the number of triangles, (X j ,Y j ,Z j ) are the coordinates of the triangle vertices of the jth triangle;

[0060] Construct bounding boxes for the triangular facets, and represent the relationship between the bounding boxes through the covariance matrix. The expression of the covariance matrix is: Where U is the covariance matrix;

[0061] An impassable grid bounding box and an impassable grid covariance matrix of the impassable grid are obtained, and the orientation and size of the bounding box and the impassable grid bounding box are obtained by solving the eigenvalues ​​and eigenvectors of the covariance matrix and the impassable grid covariance matrix, so as to obtain a bounding box distance between the bounding box and the impassable grid bounding box, and when the bounding box distance is less than or equal to a preset bounding box distance threshold, the high-risk information is output, and when the bounding box distance is greater than the preset bounding box distance threshold, the risk-free information is output.

[0062] A digital twin-driven warehouse visualization platform risk control method, comprising:

[0063] Collecting warehouse visualization platform construction data, constructing a multivariate digital twin group based on the warehouse visualization platform construction data, and building a warehouse visualization platform through the multivariate digital twin group;

[0064] Planning a warehousing route for incoming goods based on the warehousing visualization platform;

[0065] The contact risk information of goods during warehousing and transportation is monitored based on the warehouse visualization platform, and the contact risk information includes high-risk information and no-risk information.

[0066] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0067] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0068] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0069] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A digital twin-driven warehouse visualization platform risk control system, characterized in that: The warehouse visualization platform risk control system includes a warehouse visualization platform building module, a warehouse entry planning module, and a warehouse risk control module; The warehouse visualization platform construction module includes a data acquisition module, a digital twin model construction module, and a platform construction module. The data acquisition module is used to collect warehouse visualization platform construction data. The digital twin model construction module is used to construct a multivariate digital twin group based on the warehouse visualization platform construction data. The platform construction module is used to build a warehouse visualization platform through the multivariate digital twin group. The warehousing planning module is used to plan warehousing routes for warehousing goods based on the warehousing visualization platform; The warehouse risk control module is used to monitor the contact risk information of goods during warehousing and transportation based on the warehouse visualization platform, and the contact risk information includes high-risk information and no-risk information.

2. The warehouse visualization platform risk control system according to claim 1 is characterized in that: The warehouse visualization platform construction data includes warehouse design data and warehouse real-time data. The warehouse design data is used to reflect the warehouse geometric model, and the warehouse real-time data is used to reflect the current status of the warehouse. The warehouse design data includes the overall warehouse design drawing, cargo pallets, cargo locations, warehouse boundaries, and warehouse fixed equipment. The warehouse real-time data includes handling equipment and handling equipment operation routes, existing goods, conveying equipment and conveying equipment operation routes; the multi-element digital twin group includes warehouse physical entities, warehouse virtual models, twin data, warehouse cargo information, and information links.

3. The warehouse visualization platform risk control system according to claim 2 is characterized in that: The warehouse virtual model is a virtual model constructed based on the data of the warehouse visualization platform; the twin data is data information in the warehouse operation process, including cargo transportation information, equipment movement information, cargo entry and exit information, real-time sensor data, historical operation data, workload data, and maintenance record data; the stored cargo information includes basic information of stored cargo and stored cargo code. The basic information of stored cargo includes cargo type, cargo warehousing time, cargo warehousing floor, cargo warehousing location, cargo storage location, and cargo storage precautions. The stored cargo code is obtained based on the basic information of stored cargo. The stored cargo code includes warehouse entry cargo code and in-warehouse cargo code; the information link is the information transmission and analysis method of the warehouse visualization platform, which is realized through RFID tag technology.

4. The warehouse visualization platform risk control system according to claim 3 is characterized in that: The coding rules for the warehouse goods coding are: Based on the basic information of the stored goods, the storage floor number, storage cargo position number, storage storage location number, storage time number, cargo type number and special number of the stored goods are obtained. The cargo type number represents the cargo type of the stored goods, including liquid cargo, flammable cargo and corrosive cargo. The special number represents the storage precautions of the goods, including waterproof cargo, easily ignited cargo and easily corrosive cargo. The cargo type number is uppercase English letters, and the special number is lowercase English letters. The mutually exclusive cargo type number and special number are represented by the same group of uppercase and lowercase letters, which are defined as mutually exclusive codes. The storage floor number, the storage cargo position number, the storage storage location number, the storage time number, the cargo type number and the special number are combined in sequence to generate the stored goods code and construct a stored goods RFID tag.

5. The warehouse visualization platform risk control system according to claim 4 is characterized in that: The planned warehousing route includes: Dividing the warehouse visualization platform into warehouse grids, and marking the warehouse grids where obstacles exist as inaccessible grids; The RFID tag of the stored goods is read by an RFID reader / writer, and the goods corresponding to the in-warehouse goods code having the mutually exclusive code with the warehoused goods code are marked as mutually exclusive goods, and the storage grid where the mutually exclusive goods are located and the adjacent storage grids are marked as the inaccessible grids; Mark the remaining storage grids as access grids; Setting a warehouse entrance grid and a terminal grid, wherein the terminal grid is the storage grid where the goods storage position of the goods entering the warehouse is located; Obtaining a first cost function from the warehouse entrance grid to the pass grid and a second cost function from the pass grid to the terminal grid; Obtaining a total cost function based on the first cost function and the second cost function, wherein the total cost function is the sum of the first cost function and the second cost function; Based on the total cost function, the warehouse entry route is planned by adjusting the interference threat probability weight, the path length cost weight and the smoothness cost weight.

6. The warehouse visualization platform risk control system according to claim 5 is characterized in that: The expression of the first cost function is h s，n =h s，n-1 +d n，n-1 +p s，n +C s，n , n = 1, 2, ..., N, where h s,n is the first cost function from the entrance grid to the nth pass grid, h s,n-1 is the first cost function from the entrance grid to the n-1th pass grid, d n,n-1 is the distance from the nth pass grid to the n-1th pass grid, p s,n is the interference threat probability from the entrance grid to the nth pass grid, C s,n is the smoothness cost from the entrance grid to the nth pass grid, N is the number of pass grids; the expression of the second cost function is Among them, h n,e is the second cost function from the nth passing grid to the end grid, p n,e is the interference threat probability from the nth pass grid to the end grid, L n,e is the path length cost from the nth pass grid to the end grid, C n,e is the smoothness cost from the nth passing grid to the end grid, p sum is the average interference threat probability from all passing grids to the end grid, L max is the maximum path length cost from all passing grids to the end grid, C max is the maximum smoothness cost from all pass grids to the end grid, ω1 is the interference threat probability weight, ω2 is the path length cost weight, and ω3 is the smoothness cost weight.

7. The warehouse visualization platform risk control system according to claim 5 is characterized in that: The warehouse risk control module specifically includes: Divide the virtual handling equipment used to represent the goods transported into the warehouse in the warehouse visualization platform into triangular facets and obtain the vertex coordinates of the triangular facets, and calculate the virtual handling equipment vector based on the vertex coordinates of the triangular facets; Constructing bounding boxes for the triangular facets, and representing the relationship between the bounding boxes through a covariance matrix; An impassable grid bounding box and an impassable grid covariance matrix of the impassable grid are obtained, and the orientation and size of the bounding box and the impassable grid bounding box are obtained by solving the eigenvalues ​​and eigenvectors of the covariance matrix and the impassable grid covariance matrix, so as to obtain a bounding box distance between the bounding box and the impassable grid bounding box, and when the bounding box distance is less than or equal to a preset bounding box distance threshold, the high-risk information is output, and when the bounding box distance is greater than the preset bounding box distance threshold, the risk-free information is output.

8. A digital twin-driven warehouse visualization platform risk control method, characterized in that: The method is applied to the warehouse visualization platform risk control system as described in any one of claims 1 to 7, comprising: Collecting warehouse visualization platform construction data, constructing a multivariate digital twin group based on the warehouse visualization platform construction data, and building a warehouse visualization platform through the multivariate digital twin group; Planning a warehousing route for incoming goods based on the warehousing visualization platform; The contact risk information of goods during warehousing and transportation is monitored based on the warehouse visualization platform, and the contact risk information includes high-risk information and no-risk information.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the warehouse visualization platform risk control system as described in any one of claims 1-7 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, are used to execute the warehouse visualization platform risk control system as described in any one of claims 1-7.

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