A virtual reality-based warehouse management system and method

Abstract

This invention proposes a virtual reality-based warehouse management system and method. The virtual reality-based warehouse management system includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, intelligent shelves, a solution generation module, and a server. The camera module acquires image data of the warehouse; the warehouse modeling module uses the image data to build a BIM model of the warehouse; the storage information acquisition module and the attribute data acquisition module acquire storage space data, storage configuration data, and attribute data of stored and pending goods; the solution generation module generates storage solutions; and finally, the server generates 3D image data based on the warehouse BIM model and storage solutions. This system not only generates storage solutions for pending goods intuitively and efficiently but also flexibly selects the optimal storage solution based on the influence relationship between pending and stored goods.

Description

Technical Field

[0001] This invention relates to the field of warehouse management technology, and specifically to a warehouse management system and method based on virtual reality. Background Technology

[0002] Virtual reality (VR) is the combination of the virtual and the real. Theoretically, VR technology is a computer simulation system that creates and allows users to experience virtual worlds. It uses computers to generate a simulated environment, immersing the user in it. VR technology utilizes real-world data, generating electronic signals through computer technology, and combining this with various output devices to transform it into phenomena that people can perceive. These phenomena can be real objects or substances invisible to the naked eye, represented through three-dimensional models. Because these phenomena are not directly visible to us but rather simulated through computer technology, it is called virtual reality.

[0003] Traditional warehouse management primarily relies on recording product information such as name, arrival time, and quantity on packing slips for the corresponding shelves. Warehouse managers must rely on these packing slips or physically visit the warehouse to plan storage operations, which lacks the intuitive and efficient approach to inbound planning and the ability to flexibly develop storage plans based on the relationships between different products. Summary of the Invention

[0004] Based on the aforementioned problems, this invention proposes a virtual reality-based warehouse management system and method. It acquires warehouse image data through a camera module, uses this image data to create a BIM model of the warehouse through a warehouse modeling module, and then uses a storage information acquisition module and an attribute data acquisition module to acquire storage space data, storage configuration data, and attribute data of stored and pending goods. A scheme generation module generates storage schemes, and finally, the server generates 3D image data based on the warehouse's BIM model and storage schemes. This system not only generates storage schemes for pending goods intuitively and efficiently but also flexibly selects the optimal storage scheme based on the influence relationship between pending and stored goods.

[0005] In view of this, one aspect of the present invention proposes a virtual reality-based warehouse management system, comprising: a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, an intelligent shelf, a solution generation module, and a server;

[0006] The camera module is used to collect first image data of the warehouse;

[0007] The warehouse modeling module is used to acquire the three-dimensional data of the warehouse and establish the BIM model of the warehouse.

[0008] The storage information acquisition module is used to acquire the storage space data and storage configuration data of the warehouse from the BIM model;

[0009] The attribute data acquisition module is used to acquire first attribute data of stored goods, the first attribute data including at least the first volume, first weight, first storage environment requirements, and position of the stored goods on the smart shelf; and is also used to acquire second attribute data of goods to be stored, the second attribute data including at least the second volume, second weight, and second storage environment requirements of the goods to be stored.

[0010] The intelligent shelf is used to carry and secure goods, and is equipped with positioning tags;

[0011] The scheme generation module is used to generate a storage scheme based on the first attribute data and the second attribute data;

[0012] The server is used to generate 3D image data based on the BIM model of the warehouse and the storage scheme.

[0013] Optionally, the camera module is further configured to acquire second image data of the smart shelf;

[0014] The server is used for:

[0015] The deformation data of the smart shelf is calculated based on the second image data;

[0016] Obtain the third attribute data of the smart shelf, and calculate the actual load-bearing weight and maximum load-bearing weight of the smart shelf based on the third attribute data and the deformation data;

[0017] The quantity of goods to be stored that the smart shelf can store is calculated based on the actual load-bearing weight, the maximum load-bearing weight, and the second weight.

[0018] Optionally, the server is further configured to: calculate the mutual influence value between the goods to be stored and the goods already stored when they are stored in different locations based on the first storage environment requirements and the second storage environment requirements;

[0019] Based on the influence value, determine the storage location relationship between the goods to be stored and the goods already stored;

[0020] An animated image showing the relationship between the goods to be stored and the goods already stored when they are stored in different locations is generated, and a storage map of the goods to be stored is generated based on the storage location relationship.

[0021] Optionally, the server is further configured to generate a transportation route map of the goods to be stored based on the storage map and the BIM model;

[0022] The required type and quantity of transport robots are calculated based on the second volume of the goods to be stored and the quantity of the goods to be stored;

[0023] The transportation route map is sent to the transportation robot so that the transportation robot can generate a navigation route.

[0024] Optionally, it also includes an environmental monitoring and adjustment module, used to monitor changes in environmental data in real time and adjust the storage environment of the warehouse according to the first storage environment requirements and / or the second storage environment requirements;

[0025] The environmental monitoring and adjustment module is also used to monitor whether a disaster has occurred, and when a disaster occurs, it sends disaster data to the server.

[0026] The server is used to receive the disaster data and determine the corresponding processing plan based on the disaster data.

[0027] Another aspect of the present invention proposes a virtual reality-based warehouse management method, applied to a virtual reality-based warehouse management system. The virtual reality-based warehouse management system includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, intelligent shelves, a solution generation module, and a server. The virtual reality-based warehouse management method includes:

[0028] Collect the first image data of the warehouse;

[0029] Obtain the 3D data of the warehouse and build a BIM model of the warehouse;

[0030] Obtain the storage space data and storage configuration data of the warehouse from the BIM model;

[0031] Obtain first attribute data of the stored goods, the first attribute data including at least the first volume, first weight, first storage environment requirements, and position of the stored goods on the smart shelf;

[0032] Obtain the second attribute data of the goods to be stored, the second attribute data including at least the second volume, second weight, and second storage environment requirements of the goods to be stored;

[0033] A storage scheme is generated based on the first attribute data and the second attribute data;

[0034] Three-dimensional image data is generated based on the BIM model of the warehouse and the storage scheme.

[0035] Optionally, the virtual reality-based warehouse management method further includes:

[0036] Acquire the second image data of the smart shelf;

[0037] The deformation data of the smart shelf is calculated based on the second image data;

[0038] Obtain the third attribute data of the smart shelf, and calculate the actual load-bearing weight and maximum load-bearing weight of the smart shelf based on the third attribute data and the deformation data;

[0039] The quantity of goods to be stored that the smart shelf can store is calculated based on the actual load-bearing weight, the maximum load-bearing weight, and the second weight.

[0040] Optionally, the virtual reality-based warehouse management method further includes:

[0041] Calculate the mutual influence value between the goods to be stored and the goods already stored when they are stored in different locations based on the first storage environment requirements and the second storage environment requirements;

[0042] Based on the influence value, determine the storage location relationship between the goods to be stored and the goods already stored;

[0043] An animated image showing the relationship between the goods to be stored and the goods already stored when they are stored in different locations is generated, and a storage map of the goods to be stored is generated based on the storage location relationship.

[0044] Optionally, the virtual reality-based warehouse management method further includes:

[0045] Generate a transportation route map for the goods to be stored based on the storage map and the BIM model;

[0046] The required type and quantity of transport robots are calculated based on the second volume of the goods to be stored and the quantity of the goods to be stored;

[0047] The transportation route map is sent to the transportation robot so that the transportation robot can generate a navigation route.

[0048] Optionally, the method further includes:

[0049] Real-time monitoring of changes in environmental data, and adjustment of the storage environment of the warehouse according to the first storage environment requirements and / or the second storage environment requirements;

[0050] Monitor for potential disasters, and when a disaster occurs, send disaster data to the server.

[0051] The corresponding handling plan is determined based on the disaster data.

[0052] The virtual reality-based warehouse management system of this invention includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, intelligent shelves, a solution generation module, and a server. The camera module acquires image data of the warehouse; the warehouse modeling module uses this image data to build a BIM model of the warehouse; the storage information acquisition module and the attribute data acquisition module acquire storage space data, storage configuration data, and attribute data of stored and pending goods; the solution generation module generates storage solutions; and finally, the server generates 3D image data based on the warehouse's BIM model and the storage solutions. This system not only generates storage solutions for pending goods intuitively and efficiently but also flexibly selects the optimal storage solution based on the relationship between pending and stored goods. Attached Figure Description

[0053] Figure 1 This is a schematic block diagram of a virtual reality-based warehouse management system provided in one embodiment of the present invention;

[0054] Figure 2 This is a flowchart of a virtual reality-based warehouse management method provided in another embodiment of the present invention. Detailed Implementation

[0055] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0056] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0057] In the description of this invention, the term "multiple" refers to two or more. Unless otherwise explicitly defined, the terms "upper," "lower," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. The terms "connect," "install," "fix," etc., should be interpreted broadly. For example, "connect" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "multiple" means two or more.

[0058] In the description of this specification, the terms "one embodiment," "some implementations," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0059] The following reference Figures 1 to 2 This invention describes a virtual reality-based warehouse management system and method provided according to some embodiments of the present invention.

[0060] like Figure 1 As shown, one embodiment of the present invention provides a virtual reality-based warehouse management system, including: a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, an intelligent shelf, a solution generation module, and a server;

[0061] The camera module is used to collect first image data of the warehouse;

[0062] The warehouse modeling module is used to acquire the three-dimensional data of the warehouse and establish the BIM model of the warehouse.

[0063] It is understandable that BIM model, or Building Information Modeling, can be used to make the warehouse's BIM model more accurate and realistic. In addition to obtaining the first image data through the camera module (such as taking photos on-site through a drone and / or robot with a camera), the warehouse's architectural drawings can also be retrieved from an existing database. Architectural drawings mainly include architectural construction drawings, structural construction drawings, equipment construction drawings, as-built drawings, and engineering change documents. Architectural construction drawings show the planned location, external shape, and layout of the interior rooms of the building, including site plans, floor plans, elevations, sections, and construction details. Structural construction drawings show the structural type, layout, component types, and quantities of the building's load-bearing structure, including structural floor plans and structural details of each component. Equipment construction drawings show the layout and construction requirements of the building's water supply, drainage, heating, ventilation, power supply, and lighting equipment, including floor plans, system diagrams, and installation details for water supply, drainage, heating, ventilation, and electrical equipment. As-built drawings are drawn based on the actual construction situation, including the actual routing of pipes and the actual installation of other equipment in civil engineering, building construction, electrical installation, and water supply / drainage engineering. The required drawing type can be determined according to different needs in building the BIM model. After selecting the architectural drawings for the warehouse, the first image data and drawings can be imported into a BIM modeling platform (such as Revit) to build the warehouse's BIM model.

[0064] Alternatively, point cloud data of the existing building can be collected using drones or robots equipped with 3D laser scanners to obtain the actual geometric information of the warehouse. The BIM model built based on the point cloud data can express the true geometric and attribute information of the existing building. After obtaining the point cloud data and drawing data of the warehouse, BIM modeling is completed by importing the drawing data and point cloud data into the same BIM modeling platform (such as Revit). This method solves the problems of data loss or structural deformation during fusion and improves the accuracy of the fused BIM model.

[0065] Alternatively, the BIM model of the warehouse can be parsed, converted, rendered, and lightweighted before being imported into 3D modeling software (such as Smart3D) to generate a 3D model of the warehouse.

[0066] The storage information acquisition module is used to acquire the storage space data and storage configuration data of the warehouse from the BIM model;

[0067] The storage space data includes the volume of used storage space, the volume of available storage space, and the location of storage space; the storage configuration data includes the equipment parameters, quantity, and distribution map of facilities such as temperature control facilities, humidity control facilities, oxygen content control facilities, ventilation facilities, fire extinguishing facilities, waterproofing facilities, and hazardous materials handling facilities.

[0068] The storage space data and storage configuration data of the warehouse can provide a data reference for selecting the optimal storage solution.

[0069] The attribute data acquisition module is used to acquire first attribute data of stored goods, the first attribute data including at least the first volume, first weight, first storage environment requirements, and position of the stored goods on the smart shelf; and is also used to acquire second attribute data of goods to be stored, the second attribute data including at least the second volume, second weight, and second storage environment requirements of the goods to be stored.

[0070] The first attribute data of the stored goods includes at least the first volume, first weight, first storage environment requirements, and position on the smart shelf. It may also include image data (3D model, storage status diagram, etc.) of the stored goods. This data can be obtained from goods storage data stored on the server, by sensors installed on the smart shelf, or by on-site collection by a smart robot. Obtaining the first attribute data of the stored goods provides a data reference for formulating storage plans for the goods to be stored.

[0071] The intelligent shelf is used to carry and secure goods, and is equipped with positioning tags;

[0072] The intelligent shelving includes pressure sensors, temperature sensors, humidity sensors, gas analysis sensors, etc., and may also include a communication module for communicating with other terminals / devices / modules, a processor for processing data and issuing control commands, etc. The data collected by the sensors is processed and analyzed by the processor, and the processor generates corresponding commands, which are sent by the communication module to other terminals / devices / modules to enhance the collaborative capabilities of the warehouse management system.

[0073] The scheme generation module is used to generate a storage scheme based on the first attribute data and the second attribute data;

[0074] The second attribute data includes at least the second volume, second weight, and second storage environment requirements of the goods to be stored. By comparing it with the first attribute data of the already stored goods, the coexistence factor and incompatibility factor between the goods to be stored and the already stored goods can be obtained. By weighting the coexistence factor and the incompatibility factor, a basic storage plan can be derived. By combining the storage space data and storage configuration data of the warehouse, and comprehensively considering multiple factors, such as the setting of temperature control facilities, humidity control facilities, oxygen content control facilities, ventilation facilities, fire extinguishing facilities, waterproof facilities, and hazardous materials handling facilities, a better storage plan can be obtained.

[0075] The storage scheme includes, but is not limited to, the second attribute data and three-dimensional image data of the goods to be stored, storage location, storage quantity, warehousing time, storage duration, and the type and number of transport robots required.

[0076] The server is used to generate 3D image data based on the BIM model of the warehouse and the storage scheme.

[0077] After parsing, converting, rendering, and lightweighting the BIM model of the warehouse, it is imported into 3D modeling software (such as Smart3D) to generate a 3D model of the warehouse. Then, the processed image data of the stored goods is loaded into the 3D model of the warehouse to obtain a 3D model of the warehouse in its current state. Finally, combined with the 3D image data of the goods to be stored involved in the storage scheme, 3D image data is generated. The 3D image data can be played in the form of video, or it can be displayed in other forms. The embodiments of the present invention do not limit this.

[0078] It is understood that the virtual reality-based warehouse management system also includes smart glasses, which can import the storage scheme and the 3D image data into the smart glasses. When a user wears the smart glasses to inspect the warehouse and inspects an empty storage area where the goods to be stored will be stored, the 3D image of the goods to be stored is displayed on the display area of ​​the smart glasses at the location corresponding to the empty storage area, so that the user can see the storage status of the goods to be stored in advance on site, thereby improving the user experience and the precision of warehouse management.

[0079] The technical solution adopted in this embodiment, a virtual reality-based warehouse management system, includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, intelligent shelves, a solution generation module, and a server. The camera module acquires image data of the warehouse; the warehouse modeling module uses this image data to build a BIM model of the warehouse; the storage information acquisition module and the attribute data acquisition module acquire storage space data, storage configuration data, and attribute data of stored and pending goods; the solution generation module generates storage solutions; and finally, the server generates 3D image data based on the warehouse's BIM model and the storage solutions. This system not only generates storage solutions for pending goods intuitively and efficiently but also flexibly selects the optimal storage solution based on the influence relationship between pending and stored goods.

[0080] It should be known that, Figure 1 The block diagram of the virtual reality-based warehouse management system shown is for illustrative purposes only, and the number of modules shown does not limit the scope of protection of this invention.

[0081] In some possible embodiments of the present invention, the camera module is further configured to acquire second image data of the smart shelf;

[0082] The server is used for:

[0083] The deformation data of the smart shelf is calculated based on the second image data;

[0084] It is understandable that in practice, shelves will deform when loaded with goods; specific deformation situations include deformation and sinking at both ends of the shelf, deformation and sinking at one end of the shelf, and denting in the middle of the shelf. In the embodiments of the present invention, the camera module is a movable camera device, such as a drone, a robot, or a camera device installed on a movable carrier such as an unmanned vehicle. Of course, it can also be a camera device fixed on a carrier in the warehouse; the embodiments of the present invention do not limit this. The camera module can effectively capture the overall deformation of the smart shelf, and the various deformation situations of the smart shelf can be processed by the corresponding algorithms preset by the server, greatly improving the calculation accuracy. The deformation data can be obtained by comparing the original image data (i.e., image data under unloaded conditions) stored on the server with the second image data obtained by the camera module. Specifically, in a unified three-dimensional coordinate system, the difference in the front and rear coordinates of different parts of the smart shelf can be compared. Of course, the deformation data can also be obtained in other ways; the embodiments of the present invention do not limit this.

[0085] Obtain the third attribute data of the smart shelf, and calculate the actual load-bearing weight and maximum load-bearing weight of the smart shelf based on the third attribute data and the deformation data;

[0086] It should be noted that the third attribute data of the intelligent shelf includes, but is not limited to, the material of each component, the tensile strength and elastic coefficient of each component, the thickness of the beam, and the thickness of the shelf.

[0087] The actual load-bearing weight and maximum load-bearing weight of the smart shelf are calculated using the third attribute data and the deformation data.

[0088] In addition, the third attribute data may also include data collected by sensors on the smart shelf, including but not limited to pressure data collected by pressure sensors. The pressure data can be used together with the deformation data, elastic coefficient and other data to calculate the load-bearing weight, so as to ensure the accuracy of the calculation results of the actual load-bearing weight and the maximum load-bearing weight.

[0089] The quantity of goods to be stored that the smart shelf can store is calculated based on the actual load-bearing weight, the maximum load-bearing weight, and the second weight.

[0090] In some possible embodiments of the present invention, the server is further configured to: calculate the mutual influence value between the goods to be stored and the goods already stored when they are stored in different locations based on the first storage environment requirements and the second storage environment requirements;

[0091] Based on the influence value, determine the storage location relationship between the goods to be stored and the goods already stored;

[0092] It is understood that the impact value can be calculated using the following method: S1 is obtained by weighted summation of the requirement factors of the first storage environment; S2 is obtained by weighted summation of the requirement factors of the second environment; the difference between S2 and S2 is compared, with different differences corresponding to different impact values. The impact value is set to be inversely correlated with the distance between the goods to be stored and the goods already stored; that is, the larger the impact value, the larger the distance between them is required. When the first storage environment requirement and the second storage environment requirement have a storage inclusion relationship, there is no impact between the goods to be stored and the goods already stored, and there are no restrictions on their storage location.

[0093] Of course, the influence value can also be calculated using a well-trained influence value neural network.

[0094] An animated image showing the relationship between the goods to be stored and the goods already stored when they are stored in different locations is generated, and a storage map of the goods to be stored is generated based on the storage location relationship.

[0095] The animated images are simulated dynamic images, that is, based on the three-dimensional image of the warehouse, the effects of factors such as temperature and humidity required by the goods to be stored on the stored goods are added.

[0096] The storage diagram shows a comparison of the advantages and disadvantages of different storage locations, and indicates the optimal storage location.

[0097] In some possible embodiments of the present invention, the server is also configured to generate a transportation route map of the goods to be stored based on the storage map and the BIM model;

[0098] It is understood that the positioning tags of the smart shelf include location data. After obtaining the selected storage location from the storage map, a transportation route map of the goods to be stored after they arrive at the warehouse can be generated.

[0099] The required type and quantity of transport robots are calculated based on the second volume of the goods to be stored and the quantity of the goods to be stored;

[0100] The transportation route map is sent to the transportation robot so that the transportation robot can generate a navigation route.

[0101] In some possible embodiments of the present invention, the virtual reality-based warehouse management system further includes an environmental monitoring and adjustment module, which is used to monitor changes in environmental data in real time and adjust the storage environment of the warehouse according to the first storage environment requirements and / or the second storage environment requirements, so as to implement timely and dynamic adjustments to the storage environment and ensure the safety of stored goods.

[0102] The environmental monitoring and adjustment module is also used to monitor whether a disaster has occurred, and when a disaster occurs, it sends disaster data to the server.

[0103] The server is used to receive the disaster data and determine the corresponding processing plan based on the disaster data.

[0104] It is understood that the environmental monitoring and adjustment module can be installed on the smart shelf to monitor changes in environmental data in real time, and adjust the storage environment of the warehouse according to the first storage environment requirements and / or the second storage environment requirements, so as to implement timely and dynamic adjustments to the storage environment and ensure the safety of stored goods; when a disaster occurs in the warehouse, the disaster data is sent to the server, and the server provides corresponding processing solutions based on the disaster data and generates processing schematic image information based on the three-dimensional image of the warehouse, so as to facilitate manual or machine processing.

[0105] In addition, the server can also generate three-dimensional images that simulate the impact of environmental changes on stored goods, so as to achieve better control over the storage environment.

[0106] Please see Figure 2Another embodiment of the present invention proposes a virtual reality-based warehouse management method, applied to a virtual reality-based warehouse management system. The virtual reality-based warehouse management system includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, intelligent shelves, a solution generation module, and a server. The virtual reality-based warehouse management method includes:

[0107] Collect the first image data of the warehouse;

[0108] Obtain the 3D data of the warehouse and build a BIM model of the warehouse;

[0109] In this step, it can be understood that BIM model is Building Information Modeling (BIM). In order to make the BIM model of the warehouse more accurate and realistic, in addition to obtaining the first image data through the camera module (such as obtaining photos by taking pictures on site through a drone and / or robot with a camera), the architectural drawings of the warehouse can also be retrieved from an existing database. Architectural drawings mainly include architectural construction drawings, structural construction drawings, equipment construction drawings, as-built drawings, and engineering change documents. Architectural construction drawings show the planned location, external shape, and layout of the interior rooms of the building, including site plans, floor plans, elevations, sections, and construction details. Structural construction drawings show the structural type, layout, component types, and quantities of the building's load-bearing structure, including structural floor plans and structural details of each component. Equipment construction drawings show the layout and construction requirements of the building's water supply, drainage, heating, ventilation, power supply, and lighting equipment, including floor plans, system diagrams, and installation details for water supply, drainage, heating, ventilation, and electrical equipment. As-built drawings are drawn based on the actual construction situation, including the actual routing of pipes and the actual installation of other equipment in civil engineering, building construction, electrical installation, and water supply / drainage engineering. The required drawing type can be determined according to different needs in building the BIM model. After selecting the architectural drawings for the warehouse, the first image data and drawings can be imported into a BIM modeling platform (such as Revit) to build the warehouse's BIM model.

[0110] Alternatively, point cloud data of the existing building can be collected using drones or robots equipped with 3D laser scanners to obtain the actual geometric information of the warehouse. The BIM model built based on the point cloud data can express the true geometric and attribute information of the existing building. After obtaining the point cloud data and drawing data of the warehouse, BIM modeling is completed by importing the drawing data and point cloud data into the same BIM modeling platform (such as Revit). This method solves the problems of data loss or structural deformation during fusion and improves the accuracy of the fused BIM model.

[0111] Alternatively, the BIM model of the warehouse can be parsed, converted, rendered, and lightweighted before being imported into 3D modeling software (such as Smart3D) to generate a 3D model of the warehouse.

[0112] Obtain the storage space data and storage configuration data of the warehouse from the BIM model;

[0113] In this step, the storage space data includes the volume of used storage space, the volume of available storage space, and the location of storage space; the storage configuration data includes the equipment parameters, quantity, and distribution map of facilities such as temperature control facilities, humidity control facilities, oxygen content control facilities, ventilation facilities, fire extinguishing facilities, waterproofing facilities, and hazardous materials handling facilities.

[0114] The storage space data and storage configuration data of the warehouse can provide a data reference for selecting the optimal storage solution.

[0115] Obtain first attribute data of the stored goods, the first attribute data including at least the first volume, first weight, first storage environment requirements, and position of the stored goods on the smart shelf;

[0116] In this step, the first attribute data of the stored goods includes at least the first volume, first weight, first storage environment requirements, and position on the smart shelf. It may also include image data (3D model, storage status diagram, etc.) of the stored goods. This data can be obtained from goods storage data stored on the server, by sensors installed on the smart shelf, or by on-site collection by a smart robot. Obtaining the first attribute data of the stored goods provides a data reference for formulating a storage plan for the goods to be stored.

[0117] The intelligent shelving includes pressure sensors, temperature sensors, humidity sensors, gas analysis sensors, positioning tags, etc., and may also include a communication module for communicating with other terminals / devices / modules, a processor for processing data and issuing control commands, etc. The data collected by the sensors is processed and analyzed by the processor, which generates corresponding commands, which are then sent by the communication module to other terminals / devices / modules to enhance the collaborative capabilities of the warehouse management system.

[0118] Obtain the second attribute data of the goods to be stored, the second attribute data including at least the second volume, second weight, and second storage environment requirements of the goods to be stored;

[0119] A storage scheme is generated based on the first attribute data and the second attribute data;

[0120] In this step, the second attribute data includes at least the second volume, second weight, and second storage environment requirements of the goods to be stored. By comparing it with the first attribute data of the already stored goods, the coexistence factor and incompatibility factor between the goods to be stored and the already stored goods can be obtained. By weighting the coexistence factor and the incompatibility factor, a basic storage plan can be derived. By combining the storage space data and storage configuration data of the warehouse, and comprehensively considering multiple factors such as the setting of temperature control facilities, humidity control facilities, oxygen content control facilities, ventilation facilities, fire extinguishing facilities, waterproof facilities, and hazardous materials handling facilities, a better storage plan can be obtained.

[0121] The storage scheme includes, but is not limited to, the second attribute data and three-dimensional image data of the goods to be stored, storage location, storage quantity, warehousing time, storage duration, and the type and number of transport robots required.

[0122] Three-dimensional image data is generated based on the BIM model of the warehouse and the storage scheme.

[0123] In this step, the BIM model of the warehouse is parsed, converted, rendered, and lightweighted, then imported into 3D modeling software (such as Smart3D) to generate a 3D model of the warehouse. The processed image data of the stored goods is then loaded into the 3D model of the warehouse to obtain a 3D model of the warehouse in its current state. Finally, combined with the 3D image data of the goods to be stored involved in the storage scheme, 3D image data is generated. This 3D image data can be played in the form of video, or it can be displayed in other forms; the implementation of this invention does not limit this.

[0124] It is understood that the virtual reality-based warehouse management system also includes smart glasses, which can import the storage scheme and the 3D image data into the smart glasses. When a user wears the smart glasses to inspect the warehouse and inspects an empty storage area where the goods to be stored will be stored, the 3D image of the goods to be stored is displayed on the display area of ​​the smart glasses at the location corresponding to the empty storage area, so that the user can see the storage status of the goods to be stored in advance on site, thereby improving the user experience and the precision of warehouse management.

[0125] The technical solution adopted in this embodiment, a virtual reality-based warehouse management system, includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, intelligent shelves, a solution generation module, and a server. The camera module acquires image data of the warehouse; the warehouse modeling module uses this image data to build a BIM model of the warehouse; the storage information acquisition module and the attribute data acquisition module acquire storage space data, storage configuration data, and attribute data of stored and pending goods; the solution generation module generates storage solutions; and finally, the server generates 3D image data based on the warehouse's BIM model and the storage solutions. This system not only generates storage solutions for pending goods intuitively and efficiently but also flexibly selects the optimal storage solution based on the relationship between pending and stored goods.

[0126] In some possible embodiments of the present invention, the virtual reality-based warehouse management method further includes:

[0127] Acquire the second image data of the smart shelf;

[0128] The deformation data of the smart shelf is calculated based on the second image data;

[0129] In this step, it is understood that in practice, shelves will deform when loaded with goods; specific deformation situations include deformation and sinking at both ends of the shelf, deformation and sinking at one end of the shelf, and denting in the middle of the shelf. In the embodiments of the present invention, the camera module is a movable camera device, such as a drone, a robot, or a camera device installed on a movable carrier such as an unmanned vehicle. Of course, it can also be a camera device fixed on a carrier in the warehouse; the embodiments of the present invention do not limit this. The camera module can effectively capture the overall deformation of the smart shelf, and the various deformation situations of the smart shelf can be processed by the corresponding algorithms preset by the server, greatly improving the calculation accuracy. The deformation data can be obtained by comparing the original image data (i.e., image data under unloaded conditions) stored on the server with the second image data obtained by the camera module. Specifically, in a unified three-dimensional coordinate system, the difference in the front and rear coordinates of different parts of the smart shelf can be compared. Of course, the deformation data can also be obtained in other ways; the embodiments of the present invention do not limit this.

[0130] Obtain the third attribute data of the smart shelf, and calculate the actual load-bearing weight and maximum load-bearing weight of the smart shelf based on the third attribute data and the deformation data;

[0131] In this step, it should be noted that the third attribute data of the intelligent shelf includes, but is not limited to, the material of each component, the tensile strength and elastic coefficient of each component, the thickness of the beam, the thickness of the shelf, etc.

[0132] The actual load-bearing weight and maximum load-bearing weight of the smart shelf are calculated using the third attribute data and the deformation data.

[0133] In addition, the third attribute data may also include data collected by sensors on the smart shelf, including but not limited to pressure data collected by pressure sensors. The pressure data can be used together with the deformation data, elastic coefficient and other data to calculate the load-bearing weight, so as to ensure the accuracy of the calculation results of the actual load-bearing weight and the maximum load-bearing weight.

[0134] The quantity of goods to be stored that the smart shelf can store is calculated based on the actual load-bearing weight, the maximum load-bearing weight, and the second weight.

[0135] In some possible embodiments of the present invention, the virtual reality-based warehouse management method further includes:

[0136] Calculate the mutual influence value between the goods to be stored and the goods already stored when they are stored in different locations based on the first storage environment requirements and the second storage environment requirements;

[0137] Based on the influence value, determine the storage location relationship between the goods to be stored and the goods already stored;

[0138] In this step, it is understood that the impact value can be calculated using the following method: S1 is obtained by weighted summation of the requirement factors of the first storage environment; S2 is obtained by weighted summation of the requirement factors of the second environment; the difference between S2 and S2 is compared, with different differences corresponding to different impact values. The impact value is set to be inversely correlated with the distance between the goods to be stored and the goods already stored; that is, the larger the impact value, the larger the distance between them is required. When the first storage environment requirement and the second storage environment requirement have a storage inclusion relationship, there is no impact between the goods to be stored and the goods already stored, and there are no restrictions on their storage location.

[0139] Of course, the influence value can also be calculated using a well-trained influence value neural network.

[0140] An animated image showing the relationship between the goods to be stored and the goods already stored when they are stored in different locations is generated, and a storage map of the goods to be stored is generated based on the storage location relationship.

[0141] In this step, the animated image is a simulated dynamic image, that is, based on the three-dimensional image of the warehouse, the influence of factors such as temperature and humidity required by the goods to be stored on the stored goods is added.

[0142] The storage diagram shows a comparison of the advantages and disadvantages of different storage locations, and indicates the optimal storage location.

[0143] In some possible embodiments of the present invention, the virtual reality-based warehouse management method further includes:

[0144] Generate a transportation route map for the goods to be stored based on the storage map and the BIM model;

[0145] In this step, it is understood that the positioning tag of the smart shelf includes location data. After obtaining the selected storage location from the storage map, a transportation route map of the goods to be stored after they arrive at the warehouse can be generated.

[0146] The required type and quantity of transport robots are calculated based on the second volume of the goods to be stored and the quantity of the goods to be stored;

[0147] The transportation route map is sent to the transportation robot so that the transportation robot can generate a navigation route.

[0148] In some possible embodiments of the present invention, the method further includes:

[0149] Real-time monitoring of environmental data changes, and adjustment of the warehouse storage environment according to the first storage environment requirements and / or the second storage environment requirements, so as to implement timely and dynamic adjustments to the storage environment and ensure the safety of stored goods;

[0150] Monitor for potential disasters, and when a disaster occurs, send disaster data to the server.

[0151] The corresponding handling plan is determined based on the disaster data.

[0152] Understandably, in this step, changes in environmental data are monitored in real time, and the storage environment of the warehouse is adjusted according to the first storage environment requirements and / or the second storage environment requirements to implement timely and dynamic adjustments to the storage environment and ensure the safety of stored goods. When a disaster occurs in the warehouse, disaster data is sent to the server, which provides corresponding processing solutions based on the disaster data and generates processing schematic image information based on the three-dimensional image of the warehouse to facilitate manual or machine processing.

[0153] In addition, the server can also generate three-dimensional images that simulate the impact of environmental changes on stored goods, so as to achieve better control over the storage environment.

[0154] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0155] As described above, these embodiments of the present invention do not exhaustively cover all details, nor do they limit the invention to the specific embodiments described. Clearly, many modifications and variations can be made based on the above description. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to effectively utilize the invention and its modifications. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A warehouse management system based on virtual reality, characterized in that, include: The system includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, a smart shelf, a solution generation module, and a server. The camera module is used to collect first image data of the warehouse; The warehouse modeling module is used to acquire the three-dimensional data of the warehouse and establish the BIM model of the warehouse. The storage information acquisition module is used to acquire the storage space data and storage configuration data of the warehouse from the BIM model; The attribute data acquisition module is used to acquire first attribute data of stored goods, the first attribute data including at least the first volume, first weight, first storage environment requirements, and position of the stored goods on the smart shelf; and is also used to acquire second attribute data of goods to be stored, the second attribute data including at least the second volume, second weight, and second storage environment requirements of the goods to be stored. The intelligent shelf is used to carry and secure goods, and is equipped with positioning tags; The scheme generation module is used to generate a storage scheme based on the first attribute data and the second attribute data; The server is used to generate three-dimensional image data based on the BIM model of the warehouse and the storage scheme; The camera module is also used to acquire second image data of the smart shelf; The server is used for: The deformation data of the smart shelf is calculated based on the second image data; Obtain the third attribute data of the smart shelf, and calculate the actual load-bearing weight and maximum load-bearing weight of the smart shelf based on the third attribute data and the deformation data; The quantity of goods to be stored that the smart shelf can store is calculated based on the actual load-bearing weight, the maximum load-bearing weight, and the second weight. The server is further configured to: calculate the mutual influence value between the goods to be stored and the goods already stored when they are stored in different locations, based on the first storage environment requirements and the second storage environment requirements; Based on the influence value, determine the storage location relationship between the goods to be stored and the goods already stored; An animated image showing the relationship between the goods to be stored and the goods already stored when they are stored in different locations is generated, and a storage map of the goods to be stored is generated based on the storage location relationship. The method for calculating the impact value includes: weighting and summing each requirement factor of the first storage environment requirement to obtain S1; weighting and summing each requirement factor of the second storage environment requirement to obtain S2; comparing the difference between S1 and S2, with different differences corresponding to different impact values; and setting the impact value to be inversely correlated with the distance between the goods to be stored and the goods already stored, that is, the larger the impact value, the larger the distance between the two is required.

2. The virtual reality-based warehouse management system according to claim 1, characterized in that, The server is also used to generate a transportation route map of the goods to be stored based on the storage map and the BIM model; The required type and quantity of transport robots are calculated based on the second volume of the goods to be stored and the quantity of the goods to be stored; The transportation route map is sent to the transportation robot so that the transportation robot can generate a navigation route.

3. The virtual reality-based warehouse management system according to claim 2, characterized in that, It also includes an environmental monitoring and adjustment module, used to monitor changes in environmental data in real time and adjust the storage environment of the warehouse according to the first storage environment requirements and / or the second storage environment requirements; The environmental monitoring and adjustment module is also used to monitor whether a disaster has occurred, and when a disaster occurs, it sends disaster data to the server. The server is used to receive the disaster data and determine the corresponding processing plan based on the disaster data.

4. A virtual reality-based warehouse management method, applied to a virtual reality-based warehouse management system, characterized in that, The virtual reality-based warehouse management system includes a camera module, a warehouse modeling module, a storage information acquisition module, an attribute data acquisition module, intelligent shelves, a solution generation module, and a server. The virtual reality-based warehouse management method includes: Collect the first image data of the warehouse; Obtain the 3D data of the warehouse and build a BIM model of the warehouse; Obtain the storage space data and storage configuration data of the warehouse from the BIM model; Obtain first attribute data of the stored goods, the first attribute data including at least the first volume, first weight, first storage environment requirements, and position of the stored goods on the smart shelf; Obtain the second attribute data of the goods to be stored, the second attribute data including at least the second volume, second weight, and second storage environment requirements of the goods to be stored; A storage scheme is generated based on the first attribute data and the second attribute data; Generate 3D image data based on the BIM model of the warehouse and the storage plan; Acquire the second image data of the smart shelf; The deformation data of the smart shelf is calculated based on the second image data; Obtain the third attribute data of the smart shelf, and calculate the actual load-bearing weight and maximum load-bearing weight of the smart shelf based on the third attribute data and the deformation data; The quantity of goods to be stored that the smart shelf can store is calculated based on the actual load-bearing weight, the maximum load-bearing weight, and the second weight. Calculate the mutual influence value between the goods to be stored and the goods already stored when they are stored in different locations based on the first storage environment requirements and the second storage environment requirements; Based on the influence value, determine the storage location relationship between the goods to be stored and the goods already stored; An animated image showing the relationship between the goods to be stored and the goods already stored when they are stored in different locations is generated, and a storage map of the goods to be stored is generated based on the storage location relationship. The method for calculating the impact value includes: weighting and summing each requirement factor of the first storage environment requirement to obtain S1; weighting and summing each requirement factor of the second storage environment requirement to obtain S2; comparing the difference between S1 and S2, with different differences corresponding to different impact values; and setting the impact value to be inversely correlated with the distance between the goods to be stored and the goods already stored, that is, the larger the impact value, the larger the distance between the two is required.

5. The warehouse management method based on virtual reality according to claim 4, characterized in that, The virtual reality-based warehouse management method also includes: Generate a transportation route map for the goods to be stored based on the storage map and the BIM model; The required type and quantity of transport robots are calculated based on the second volume of the goods to be stored and the quantity of the goods to be stored; The transportation route map is sent to the transportation robot so that the transportation robot can generate a navigation route.

6. The warehouse management method based on virtual reality according to claim 5, characterized in that, The method further includes: Real-time monitoring of changes in environmental data, and adjustment of the storage environment of the warehouse according to the first storage environment requirements and / or the second storage environment requirements; Monitor for potential disasters, and when a disaster occurs, send disaster data to the server. The corresponding handling plan is determined based on the disaster data.

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