3D modeling method and system based on logistics park and storage materials

Abstract

The invention provides a 3D modeling method and system based on a logistics park and storage materials, relates to the technical field of 3D modeling, and solves the technical problem of low storage data accuracy of the storage materials in the logistics park. The method comprises the following steps: in response to a 3D modeling instruction for materials, an unmanned aerial vehicle in a logistics park sends a broadcast signal in a broadcast form; the electronic tag receives the broadcast signal and sends a feedback signal for the broadcast signal according to the to-be-modeled data; the feedback signal comprises target storage data conforming to the to-be-modeled data and a material identifier of a target material corresponding to the electronic tag; scanning equipment arranged on the unmanned aerial vehicle scans all the electronic tags in the logistics park so as to receive a feedback signal; and the data processing system corresponding to the unmanned aerial vehicle performs storage material 3D modeling on the condition of each target material in the logistics park based on the target storage data and the material identifier in the feedback signal to obtain a storage material 3D model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of 3D modeling, in particular to a 3D modeling method and system based on a logistics park and warehouse materials. BACKGROUND

[0002] At present, the material state data of the stored materials in the logistics park is managed through an information management platform. For example, the warehouse management system (WMS) of the information management platform uniformly manages the whole process of warehouse acceptance, storage location allocation, and warehouse review; the automatic storage system (AS / RS) integrates stacker, conveying line and intelligent control system by using automatic storage and operation technology to realize high-density storage and accurate retrieval; and the automatic sorting line and intelligent packaging system are combined to support high-frequency order processing. However, the storage data accuracy of the warehouse materials in the logistics park is low at present. SUMMARY

[0003] The purpose of the present application is to provide a 3D modeling method and system based on a logistics park and warehouse materials to solve the technical problem of low storage data accuracy of warehouse materials in the logistics park.

[0004] In a first aspect, the present application provides a 3D modeling method based on a logistics park and warehouse materials, all materials in the logistics park are provided with electronic tags; the electronic tags are provided with storage data of the corresponding materials in the logistics park, the storage data includes the content of the materials, the time when the materials enter the logistics park, the storage type of the materials in the logistics park, the storage mode of the materials in the logistics park, and the storage location of the materials in the logistics park; the method comprises: In response to the 3D modeling instruction for the materials, the drone in the logistics park sends a broadcast signal in the form of broadcast; the broadcast signal contains at least one of the following: the content of the modeled goods, the modeled materials entering the logistics park within a target time, the modeled storage type in the logistics park, the modeled materials stored in the logistics park in a target storage mode, and the modeled materials stored at a target storage location; The electronic tag receives the broadcast signal and sends a feedback signal for the broadcast signal according to the modeled data; the feedback signal contains the target storage data conforming to the modeled data and the material identification of the target materials corresponding to the electronic tag; The scanning device provided on the drone scans all the electronic tags in the logistics park to receive the feedback signal; The data processing system corresponding to the unmanned aerial vehicle performs 3D modeling of the storage materials based on the target storage data in the feedback signal and the material identification, and obtains a 3D model of the storage materials.

[0005] In a possible implementation, the electronic tag receives the broadcast signal, and sends a feedback signal for the broadcast signal according to the to-be-modeled data, including: The electronic tag receives the to-be-modeled data in the broadcast signal; The electronic tag filters target storage data from the storage data set by itself according to the to-be-modeled data; The electronic tag sends a feedback signal for the broadcast signal based on the target storage data.

[0006] In a possible implementation, the electronic tag is provided with a gyroscope; the content of the material has anti-damage movement standard data corresponding thereto; and the method further includes: The actual vibration data of the material is monitored by the gyroscope; The damage degree monitoring result of the material is analyzed according to the actual vibration data and the anti-damage movement standard data corresponding to the material; In response to a damage detection instruction for the material, the unmanned aerial vehicle sends a detection signal in a broadcast form; The electronic tag receives the detection signal and sends a reply signal for the detection signal; the reply signal contains the damage degree monitoring result of the material corresponding to the electronic tag; The scanning device scans all the electronic tags in the logistics park to receive the reply signal.

[0007] In a possible implementation, the damage degree monitoring result of the material is analyzed according to the actual vibration data and the anti-damage movement standard data corresponding to the material, including: The damage degree monitoring result of the material is analyzed according to the actual vibration data and the anti-damage movement standard data corresponding to the material by the following formula: RMS= ; wherein x(t) is the actual vibration acceleration value of the material monitored by the gyroscope at time t, T is the monitoring time period of the gyroscope, and RMS represents the actual vibration intensity of the material; = ; wherein is the maximum variation range of the vibration of the material; DamageIndex =w 1x + w 2x + w 3x∑( ) wherein, represents the maximum allowed RMS value, is the maximum allowed peak value of the vibration amplitude of the goods, is the vibration amplitude value at frequency f, is the maximum allowed amplitude at a specific key frequency f, w 1, w 2, w 3 are the specified weight coefficients of each parameter respectively, and DamageIndex is the damage degree monitoring result of the goods.

[0008] In one possible implementation, after the scanning device scans all the electronic tags in the logistics park to receive the reply signals, the method further comprises: The data processing system corresponding to the unmanned aerial vehicle determines the to-be-screened goods from all the goods according to the damage degree monitoring result in the reply signal, controls the unmanned aerial vehicle to go to the position of the to-be-screened goods, and controls the mechanical arm arranged on the unmanned aerial vehicle to unseal the packaging of the to-be-screened goods; The data processing system controls the image acquisition device arranged on the unmanned aerial vehicle to acquire the images of the goods in the to-be-screened goods, and identifies whether the goods in the to-be-screened goods are damaged based on the images of the goods.

[0009] In one possible implementation, the method further comprises: In response to the extraction instruction for the first goods, the unmanned aerial vehicle sends an extraction signal; wherein the extraction signal contains an extraction condition, and the extraction condition contains at least one of the extracted content of the goods, the goods entering the logistics park within a first time, the goods of a first storage type, the goods stored in the logistics park in a first storage manner, and the goods stored at a first storage location; The electronic tag receives the extraction condition in the extraction signal, and judges whether the goods corresponding to the electronic tag match the extraction condition according to the extraction condition and the storage data set by the electronic tag; the electronic tag is provided with a prompt light; If the goods corresponding to the electronic tag match the extraction condition, the prompt light arranged in the electronic tag is controlled to operate; The image acquisition device arranged on the unmanned aerial vehicle identifies the first electronic tag running the prompt light, controls the unmanned aerial vehicle to fly to the position of the first electronic tag, and controls the mechanical arm arranged on the unmanned aerial vehicle to extract the first material corresponding to the first electronic tag from the plurality of materials.

[0010] In one possible implementation, after the image acquisition device arranged on the unmanned aerial vehicle identifies the first electronic tag running the prompt light, the method further includes: comparing the first storage data stored in the first electronic tag with the model storage data of the virtual material corresponding to the first electronic tag in the 3D model of the storage material; If it is detected through comparison that the first storage data does not match the model storage data, the 3D model of the storage material is corrected according to the first storage data, so that the 3D model of the storage material is kept updated.

[0011] In a second aspect, the application provides a 3D modeling system based on a logistics park and storage materials. All materials in the logistics park are provided with electronic tags. The electronic tags are provided with storage data of corresponding materials in the logistics park. The storage data includes the content of the materials, the time when the materials enter the logistics park, the storage type of the materials in the logistics park, the storage mode of the materials in the logistics park, and the storage position of the materials in the logistics park. The 3D modeling system based on the logistics park and the storage materials includes: A first sending module is configured to send a broadcast signal in a broadcast form by an unmanned aerial vehicle in the logistics park in response to a 3D modeling instruction for the materials. The broadcast signal includes to-be-modeled data, which includes at least one of to-be-modeled content, to-be-modeled materials entering the logistics park within a target time, to-be-modeled storage types in the logistics park, to-be-modeled materials stored in the logistics park in a target storage mode, and to-be-modeled materials stored at a target storage position. A second sending module is configured to receive the broadcast signal by the electronic tags and send a feedback signal for the broadcast signal according to the to-be-modeled data. The feedback signal includes target storage data conforming to the to-be-modeled data and a material identifier of a target material corresponding to the electronic tag. A scanning module is configured to scan all the electronic tags in the logistics park by a scanning device arranged on the unmanned aerial vehicle to receive the feedback signal. A modeling module is used for the data processing system corresponding to the drone to perform 3D modeling of the storage materials for each target material in the logistics park based on the target storage data and the material identification in the feedback signal to obtain a 3D model of the storage materials.

[0012] In a third aspect, the present application provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0013] In a fourth aspect, the present application further provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to execute the method described in the first aspect above.

[0014] This application brings the following beneficial effects: The application provides a 3D modeling method and system based on a logistics park and warehouse materials, all materials in the logistics park are provided with electronic tags, the electronic tags are provided with storage data of the corresponding materials in the logistics park, the storage data includes the material content, the time when the material enters the logistics park, the storage type of the material in the logistics park, the storage mode of the material in the logistics park and the storage position of the material in the logistics park, the method can respond to the 3D modeling instruction for the material, the unmanned aerial vehicle in the logistics park sends a broadcast signal in the form of broadcast, the broadcast signal contains to-be-modeled data, the to-be-modeled data contains at least one of the to-be-modeled material content, the to-be-modeled material entering the logistics park within a target time, the to-be-modeled storage type in the logistics park, the to-be-modeled material stored in the logistics park in a target storage mode and the to-be-modeled material stored at a target storage position, the electronic tag receives the broadcast signal and sends a feedback signal for the broadcast signal according to the to-be-modeled data, the feedback signal contains the target storage data conforming to the to-be-modeled data and the material identification of the target material corresponding to the electronic tag, a scanning device arranged on the unmanned aerial vehicle scans all the electronic tags in the logistics park to receive the feedback signal, and a data processing system corresponding to the unmanned aerial vehicle performs 3D modeling of the storage material in the logistics park according to the target storage data in the feedback signal and the material identification, to obtain a 3D model of the storage material. In the present application, the cooperation of the unmanned aerial vehicle and the electronic tag can update and obtain accurate storage data in real time, including material content, entering time, storage type, mode and position information, so that the inventory record is more accurate, thereby improving the accuracy of the storage data of the storage material in the logistics park, and solving the technical problem of low accuracy of the storage data of the storage material in the logistics park. Moreover, based on the unique electronic tag of each material, the system can screen according to specific attributes (such as entering time, storage type, etc.), and intuitively display the specific distribution of the material in the warehouse through 3D modeling, greatly enhancing the efficiency of material tracking and management.

[0015] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0017] Figure 1A flowchart of a 3D modeling method based on a logistics park and warehouse materials is provided for the embodiments of the present application. Figure 2 An example of a warehouse material 3D model in the 3D modeling method based on a logistics park and warehouse materials provided for the embodiments of the present application is shown. Figure 3 A structural diagram of a 3D modeling device based on a logistics park and warehouse materials provided for the embodiments of the present application is shown. Figure 4 A structural diagram of an electronic device provided by the embodiments of the present application is shown. DETAILED DESCRIPTION

[0018] To make the purposes, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions of the present application will be described in detail below with reference to the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0019] The terms "comprise" and "have" and any variations thereof mentioned in the embodiments of the present application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include other steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or device.

[0020] At present, the warehouse data accuracy of warehouse materials in a logistics park is low. Based on this, the embodiments of the present application provide a 3D modeling method and system based on a logistics park and warehouse materials, which can solve the technical problem of low warehouse data accuracy of warehouse materials in a logistics park.

[0021] The embodiments of the present application will be further described below with reference to the drawings.

[0022] Figure 1 A flowchart of a 3D modeling method based on a logistics park and warehouse materials provided for the embodiments of the present application is shown. In the logistics park, all materials are provided with electronic tags. The electronic tags are provided with warehouse data of the corresponding materials in the logistics park, which includes the content of the materials, the time when the materials enter the logistics park, the warehouse type to which the materials belong in the logistics park, the storage method of the materials in the logistics park, and the storage location of the materials in the logistics park. As shown in the figure, the method includes: Figure 1 ​Step S110, in response to the 3D modeling instruction for the material, the drone in the logistics park sends out a broadcast signal in the form of broadcast.

[0023] The broadcast signal contains the to-be-modeled data, which contains at least one of the to-be-modeled material content, the to-be-modeled material entering the logistics park within the target time, the to-be-modeled storage type in the logistics park, the to-be-modeled material stored in the target storage mode in the logistics park, and the to-be-modeled material stored at the target storage location.

[0024] For example, the 3D modeling instruction for a specific material is sent to the system through the control center or mobile application. After the system receives the instruction, the most suitable drone is selected for the task according to the location and characteristics of the material, and the instruction is sent to the selected drone. According to the location of the material and the surrounding environment, the best flight path is calculated to avoid obstacles and efficiently complete the task. The drone automatically takes off according to the preset program and flies to the target location along the planned path. After arriving at the target location, the drone uses the sensors carried to take multi-angle photos or scans of the material, collecting the necessary data for 3D modeling. Some advanced systems can perform preliminary data processing directly on the drone to improve efficiency. Then, the collected data is integrated into a unified format, and a broadcast signal is generated. For broadcast release, the drone sends a signal containing 3D model data or other related information in the form of broadcast through its communication module.

[0025] Step S120, the electronic tag receives the broadcast signal and sends a feedback signal for the broadcast signal according to the to-be-modeled data.

[0026] The feedback signal contains target storage data consistent with the to-be-modeled data and material identification of the target material corresponding to the electronic tag.

[0027] In some embodiments, the above step S120 can specifically include the following steps: the electronic tag receives the to-be-modeled data in the broadcast signal; the electronic tag filters the target storage data consistent with the to-be-modeled data from the storage data set by itself according to the to-be-modeled data; and the electronic tag sends a feedback signal for the broadcast signal based on the target storage data.

[0028] Through the electronic tag, the target storage data meeting the requirements can be quickly filtered from a large amount of storage data stored by the electronic tag according to the received to-be-modeled data. This means that the system can quickly locate the information of the relevant goods or materials in a large amount of information, greatly improving the efficiency and accuracy of data processing.

[0029] Step S130, the scanning device provided on the drone scans all electronic tags in the logistics park to receive the feedback signal.

[0030] For example, the UAV takes off according to the preset flight path and starts to perform the scanning task. During this process, the UAV keeps stable flight to ensure that the scanning device can work accurately. After the scanning device on the UAV is started, it begins to scan all electronic tags in the logistics park. These electronic tags can be attached to goods, shelves or other logistics facilities. The system sends a broadcast signal of the data to be modeled to the electronic tags in some way (such as a wireless network). After each electronic tag receives this signal, it determines whether it matches the data to be modeled according to the data stored in it and prepares the corresponding feedback information.

[0031] When the electronic tag determines that it meets the requirements of the data to be modeled, it can send a feedback signal. The scanning device on the UAV is responsible for receiving these feedback signals and transmitting them back to the central processing system. The received feedback signals contain important information about the goods associated with the electronic tags. The central processing system summarizes and analyzes all the received feedback signals to update inventory information, track the location of goods or perform other management operations.

[0032] In step S140, the data processing system corresponding to the UAV models the situation of each target material in the logistics park based on the target storage data in the feedback signal and the material identifier, to obtain a 3D model of the storage material.

[0033] The above-mentioned 3D model of the storage material is as shown in Figure 2 In the embodiments of the present application, through the cooperation of the UAV and the electronic tag, accurate storage data can be updated and obtained in real time, including information such as the content of the goods, the entering time, the storage type, the mode and the location, so that the inventory record is more accurate, and the accuracy of the storage data of the storage material in the logistics park is improved. Moreover, based on the unique electronic tag of each material, the system can filter according to specific attributes (such as entering time, storage type, etc.), and intuitively display the specific distribution of the material in the warehouse through 3D modeling, greatly enhancing the efficiency of material tracking and management.

[0034] In some embodiments, a gyroscope is arranged in the electronic tag; the content of the goods of the material corresponds to damage prevention movement standard data; the method can further include the following steps: The actual vibration data of the material is monitored through the gyroscope; the damage degree monitoring result of the material is analyzed according to the actual vibration data and the damage prevention movement standard data corresponding to the material; in response to the damage detection instruction for the material, the UAV sends a detection signal in the form of a broadcast; the electronic tag receives the detection signal and sends a reply signal for the detection signal; the reply signal contains the damage degree monitoring result of the material corresponding to the electronic tag; the scanning device scans all electronic tags in the logistics park to receive the reply signal.

[0035] By integrating a gyroscope in the electronic tag, the actual vibration of the goods during transportation and storage can be monitored in real time, ensuring that any abnormal vibration that may cause damage can be captured in time. Moreover, by combining the damage-prevention movement standard data specific to each item, the system can compare the actual vibration data, more accurately analyze and evaluate the possibility or degree of damage to the goods, and provide a basis for subsequent processing.

[0036] In some embodiments, the above-mentioned analysis of the damage degree monitoring result of the goods according to the actual vibration data and the damage-prevention movement standard data corresponding to the goods can specifically include the following steps: According to the actual vibration data and the damage-prevention movement standard data corresponding to the goods, the damage degree monitoring result of the goods is analyzed by the following formula: RMS= ; wherein x(t) is the actual vibration acceleration value of the goods monitored by the gyroscope at time t, T is the monitoring time period of the gyroscope, and RMS represents the actual vibration intensity of the goods. = ; wherein is the maximum variation range of the vibration of the goods; DamageIndex = w 1× + w 2× + w 3×∑( ); wherein represents the maximum allowed RMS value, is the maximum allowed vibration amplitude peak value of the goods, is the vibration amplitude value at frequency f, is the maximum allowed amplitude at a specific key frequency f, w 1, w 2, w 3 are the specified weight coefficients of each parameter, and DamageIndex is the damage degree monitoring result of the goods.

[0037] In the embodiments of the present application, the damage degree monitoring result of the goods is analyzed by the above-mentioned formula, which can make the damage degree monitoring result data of the goods more accurate and improve the accuracy of the damage degree monitoring of the goods.

[0038] In some embodiments, after the scanning device scans all electronic tags in the logistics park to receive the reply signal, the method can further include the following steps: The data processing system corresponding to the drone determines the materials to be screened from all materials based on the damage degree monitoring results in the reply signal, controls the drone to fly to the location of the materials to be screened, and controls the robotic arm installed on the drone to unpack the packaging of the materials to be screened; The data processing system controls the image acquisition device installed on the drone to collect images of items in the materials to be screened, and identifies whether the items in the materials to be screened are damaged based on the image of the items.

[0039] The data processing system automatically identifies materials requiring further inspection based on damage monitoring results from the electronic tags' response signals, eliminating the need for manual prejudgment and significantly saving time and labor costs. Furthermore, by controlling drones to locate materials for screening and using an onboard robotic arm to perform packaging and unpacking operations, precise manipulation of specific materials is achieved, minimizing the potential for errors or damage caused by human intervention.

[0040] In some embodiments, the method may further include the following steps: In response to a retrieval instruction for a first material, the drone transmits a retrieval signal; wherein the retrieval signal includes retrieval conditions, and the retrieval conditions include at least one of the following: the content of the item to be retrieved, retrieval of materials that have entered the logistics park within a first time period, retrieval of materials of a first storage type, retrieval of materials stored in the logistics park in a first storage method, and retrieval of materials stored at a first storage location; The electronic tag receives the extraction conditions in the extraction signal and determines whether the corresponding material matches the extraction conditions based on the extraction conditions and the storage data set by itself; a prompt light is set in the electronic tag; If the material corresponding to the electronic tag itself matches the extraction conditions, the prompt light set in the control itself will operate; The image acquisition device provided on the UAV identifies the first electronic tag of the operation prompt light, controls the UAV to fly to the position of the first electronic tag, and controls the mechanical arm provided on the UAV to extract the first material corresponding to the first electronic tag from multiple materials.

[0041] The extraction signal sent by the unmanned aerial vehicle contains specific extraction conditions, and the electronic tag can intelligently match according to these conditions and its own stored storage data. This mechanism ensures that only materials that meet the extraction requirements will be selected, greatly improving the accuracy of material extraction. Moreover, once the electronic tag determines that the corresponding material meets the conditions, it will activate the prompt light, and the image acquisition device on the unmanned aerial vehicle can identify these running prompt lights and guide the unmanned aerial vehicle to fly accurately to the corresponding material location. This way avoids the time consumption and possible errors of manual searching for materials, improving operational efficiency. Furthermore, the entire extraction process is almost completely automated, from sending extraction instructions, condition matching, to the final material extraction, all of which are completed independently by the system. This not only significantly shortens the processing time, but also reduces the demand for manpower, especially when facing a large number of materials, which can better demonstrate its efficiency.

[0042] In some embodiments, after the image acquisition device on the unmanned aerial vehicle identifies the first electronic tag with a running prompt light, the method can further include the following steps: comparing the first storage data stored in the first electronic tag with the model storage data of the virtual material corresponding to the first electronic tag in the storage material 3D model; If it is detected through comparison that the first storage data does not match the model storage data, the storage material 3D model is corrected according to the first storage data to keep the storage material 3D model updated.

[0043] By comparing and correcting the actual storage data (first storage data) with the data in the virtual 3D model, the consistency between the two can be ensured, which greatly reduces the errors caused by inconsistent data. Furthermore, through the automatic comparison and correction process, data differences can be quickly identified and corrected without human intervention, thereby improving the overall efficiency and accuracy of inventory management.

[0044] For the intelligent storage of the above-mentioned warehouse materials 3D model, in the three-dimensional visualization scene, the user can manage and view various types of storage data. Storage occupancy: support real-time display and viewing of various types of storage occupancy through various chart forms, including total storage quantity, current storage usage rate, etc. Material occupancy storage ranking: support real-time display of storage occupancy ranking through various chart forms, various types of material usage proportion, etc. Storage utilization: support real-time display of various storage usage situation through various chart forms, such as daily, weekly, monthly, and annual storage usage situation. Display the storage management situation in a visual form, support to view each storage, the storage location of goods, etc. Support fast query and positioning of the specific location of goods, support fuzzy query function. Racking area state display: occupied storage is displayed in red, and idle storage is displayed in green. Clicking on a row or a column can expand and display. Clicking on the storage tray displays the basic information of the goods stored in the storage (project, sub-warehouse attribute, warehouse age, purchase order number). Clicking on the goods can display the tray number, box number and corresponding barcode of the terminal material.

[0045] For warehouse operation management, in the three-dimensional visualization scene, the user can manage forklift positioning and operation personnel data: support real-time restoration of forklift operation real-time positioning in the three-dimensional scene, and display forklift operation status, operation market and other data; support forklift positioning management, support for positioning to mark the specific location of all forklifts in the warehouse; and support for statistics of forklift usage rate, vacancy rate and other data through chart form. For device working condition, support to mark the spatial distribution of all video monitoring devices in the park in the three-dimensional environment. Support real-time video switching of a single camera, picture zooming in and out. Support association with other system devices under the non-video monitoring subsystem, search for surrounding video monitoring points, and click to view real-time monitoring pictures of the searched monitoring probes. Device operation and alarm: support to display the running status of all video monitoring devices in the park in different colors. (Such as: alarm in red). Support to count the number of video devices and the number of alarms in the form of information panel. Support linkage with AI video monitoring in the three-dimensional scene, count the proportion of AI alarm types, and call up the alarm detail list. Through AI video monitoring, deploy six scene monitoring algorithms of "not wearing safety helmet, material placement pressing line, occupying road, perimeter intrusion, open fire, and smoking", realize 7x24 hours automatic supervision and alarm.

[0046] The intelligent management system realizes the automation and intelligentization of the logistics park by integrating overview, warehouse, security, vehicle and environmental monitoring modules. Accurately control materials, monitor safety in real time, optimize vehicle scheduling, and intelligently adjust the environment, greatly improving the operation efficiency and safety level of the park.

[0047] The scheme is aimed at calculating and displaying professional indicators related to warehouse logistics, and refines the management dimensions according to the material categories and different sub-libraries, improves the degree of fine management of the park, optimizes the material management mode, and realizes the visual sharing of idle resources.

[0048] The five modules of overview, warehouse, security, vehicle and environment monitoring are integrated in the digital twin platform. The intelligent warehouse module visualizes the shelf life and displays indicators such as sub-library inventory proportion. The intelligent security module also accesses AI intelligent video analysis. Through the docking of AI intelligent video analysis technology, real-time intelligent analysis and violation warning of monitoring video can be realized, and online intelligent supervision is achieved. Through this scheme, the park operation cost can be reduced by 800,000 yuan, the overall operation efficiency can be improved by 40%, and the resource equipment utilization efficiency can be improved by 20% in economic benefits.

[0049] Figure 3 A structural schematic diagram of a 3D modeling device based on a logistics park and warehouse materials is provided. An electronic tag is provided on all materials in the logistics park; the electronic tag is provided with storage data of the corresponding materials in the logistics park, and the storage data includes the content of the materials, the time when the materials enter the logistics park, the storage type of the materials in the logistics park, the storage mode of the materials in the logistics park, and the storage position of the materials in the logistics park. As shown in Figure 3 The 3D modeling device based on the logistics park and the warehouse materials 300 includes: A first sending module 301 is configured to send a broadcast signal in broadcast form in response to a 3D modeling instruction for the materials; the broadcast signal contains to-be-modeled data, and the to-be-modeled data contains at least one of to-be-modeled material content, to-be-modeled materials entering the logistics park within a target time, to-be-modeled storage types in the logistics park, to-be-modeled materials stored in the logistics park in a target storage mode, and to-be-modeled materials stored at a target storage position; A second sending module 302 is configured to receive the broadcast signal by the electronic tag, and send a feedback signal for the broadcast signal according to the to-be-modeled data; the feedback signal contains target storage data conforming to the to-be-modeled data and a material identifier of the target material corresponding to the electronic tag; A scanning module 303 is configured to scan all the electronic tags in the logistics park by a scanning device provided on the unmanned aerial vehicle to receive the feedback signal; The modeling module 304 is configured to perform 3D modeling of the target logistics park and the target warehouse material based on the target warehouse data in the feedback signal and the material identifier, to obtain a 3D model of the target warehouse material.

[0050] The 3D modeling device based on the logistics park and the warehouse material provided by the embodiments of the present application has the same technical features as the 3D modeling method based on the logistics park and the warehouse material provided by the above embodiments, and can solve the same technical problems and achieve the same technical effects.

[0051] The electronic device provided by the embodiments of the present application, as shown in Figure 4 The electronic device 400 includes a processor 402 and a memory 401, and the memory stores a computer program executable on the processor, and the processor executes the computer program to implement the steps of the method provided by the above embodiments.

[0052] Referring to Figure 4 The electronic device further includes a bus 403 and a communication interface 404, and the processor 402, the communication interface 404 and the memory 401 are connected through the bus 403; and the processor 402 is configured to execute the executable modules stored in the memory 401, such as computer programs.

[0053] The memory 401 can include a high-speed random access memory (RAM) and can also include a non-volatile memory such as at least one disk memory. The communication between the system network element and at least one other network element is realized through at least one communication interface 404 (which can be wired or wireless), and the Internet, a wide area network, a local area network, a metropolitan area network, etc. can be used.

[0054] The bus 403 can be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0055] The memory 401 is configured to store a program, and the processor 402 executes the program after receiving an execution instruction. The method executed by the device defined by the process disclosed in any of the embodiments of the present application can be applied to the processor 402 or implemented by the processor 402.

[0056] The processor 402 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 402 or by instructions in the form of software. The above-mentioned processor 402 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in memory 401, and processor 402 reads the information in memory 401 and, in conjunction with its hardware, completes the steps of the above method.

[0057] Corresponding to the above-mentioned 3D modeling method based on logistics parks and warehouse materials, an embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by the processor, the computer-executable instructions prompt the processor to execute the steps of the above-mentioned 3D modeling method based on logistics parks and warehouse materials.

[0058] The 3D modeling device based on the logistics park and storage materials provided in the embodiment of the present application can be specific hardware on the equipment or software or firmware installed on the equipment. The implementation principle and technical effects of the device provided in the embodiment of the present application are the same as those in the aforementioned method embodiment. For the sake of brief description, for parts not mentioned in the device embodiment, reference can be made to the corresponding content in the aforementioned method embodiment. Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices and units described above can all refer to the corresponding processes in the aforementioned method embodiment, and will not be repeated here.

[0059] In the embodiments of the present application, it should be understood that the disclosed apparatus and method can be implemented in other manners. The embodiments described above are merely specific implementation manners of the present application, and for example, the division of the units is only a logical function division, and there can be another division manner in actual implementation; for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the among different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electric, mechanical or other forms.

[0060] For another example, the flowcharts and block diagrams in the drawings show the possible implementation architectures, functions and operations of the apparatus, method and computer program product according to the embodiments of the present application. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different orders from that shown in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and the combination of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0061] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e. they can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0062] In addition, each functional unit in the embodiments provided by the present application can be integrated into one processing unit, or each unit can exist physically as a separate unit, or two or more units can be integrated into one unit.

[0063] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the 3D modeling method based on logistics park and warehouse materials described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program code storage media.

[0064] It should be noted that: similar reference numbers and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings, in addition, the terms "first", "second", "third" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0065] Finally, it should be noted that: the above-described embodiments are only specific embodiments of the present application, used to illustrate the technical solutions of the present application, and not to limit them, the protection scope of the present application is not limited thereto, although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand: any person skilled in the art within the technical scope disclosed by the present application, they can still modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications, changes or replacements do not make the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application. All should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A 3D modeling method based on logistics parks and warehouse materials, characterized in that: All materials in the logistics park are provided with electronic tags; the electronic tags are provided with storage data of the corresponding materials in the logistics park, the storage data including the content of the materials, the time when the materials entered the logistics park, the storage type of the materials in the logistics park, the storage method of the materials in the logistics park, and the storage location of the materials in the logistics park; the method includes: In response to a 3D modeling instruction for the material, the drone in the logistics park sends a broadcast signal in a broadcasting form; the broadcast signal includes data to be modeled, and the data to be modeled includes at least one of the following: content of the item to be modeled, materials to be modeled that enter the logistics park within a target time, storage types to be modeled in the logistics park, materials to be modeled stored in the logistics park in a target storage method, and materials to be modeled stored at a target storage location; The electronic tag receives the broadcast signal and sends a feedback signal in response to the broadcast signal according to the data to be modeled; the feedback signal includes target warehouse data that matches the data to be modeled and a material identifier of the target material corresponding to the electronic tag; The scanning device provided on the drone scans all the electronic tags in the logistics park to receive the feedback signal; The data processing system corresponding to the drone performs 3D storage material modeling on the situation of each target material in the logistics park based on the target storage data and the material identification in the feedback signal to obtain a 3D storage material model.

2. The method according to claim 1, characterized in that The electronic tag receives the broadcast signal and sends a feedback signal for the broadcast signal according to the data to be modeled, including: The electronic tag receives the data to be modeled in the broadcast signal; The electronic tag selects target warehouse data that matches the data to be modeled from the warehouse data set by the electronic tag according to the data to be modeled; The electronic tag sends a feedback signal to the broadcast signal based on the target storage data.

3. The method according to claim 1, characterized in that The electronic tag is provided with a gyroscope; the content of the material item corresponds to anti-damage movement standard data; the method further includes: monitoring actual vibration data of the material by using the gyroscope; Analyzing a damage degree monitoring result of the material according to the actual vibration data and the damage prevention movement standard data corresponding to the material; In response to a damage detection instruction for the material, the drone sends a detection signal in a broadcast form; The electronic tag receives the detection signal and sends a response signal in response to the detection signal; the response signal includes the damage degree monitoring result of the material corresponding to the electronic tag; The scanning device scans all the electronic tags in the logistics park to receive the reply signal.

4. The method according to claim 3, characterized in that The analyzing the damage degree monitoring result of the material based on the actual vibration data and the damage prevention movement standard data corresponding to the material includes: According to the actual vibration data and the damage prevention movement standard data corresponding to the material, the damage degree monitoring result of the material is analyzed by the following formula: RMS= Wherein, x(t) is the actual vibration acceleration value of the material monitored by the gyroscope at time t, T is the monitoring time period of the gyroscope, and RMS represents the actual vibration intensity of the material; = ;in, is the maximum range of vibration of the material; DamageIndex = w 1× + w 2× + w 3×∑（ ）； in, Indicates the maximum allowed RMS value, is the maximum permissible peak vibration amplitude of the material, is the vibration amplitude value at frequency f, is the maximum allowable amplitude at a specific critical frequency f, w 1. w 2. w 3 are the specified weight coefficients of each parameter, and DamageIndex is the monitoring result of the damage degree of the material.

5. The method according to claim 3, characterized in that After the scanning device scans all the electronic tags in the logistics park to receive the reply signal, the method further includes: The data processing system corresponding to the drone determines the materials to be screened from all the materials according to the damage degree monitoring result in the reply signal, controls the drone to fly to the location of the materials to be screened, and controls the robotic arm provided on the drone to unpack the packaging of the materials to be screened; The data processing system controls the image acquisition device provided on the drone to acquire images of items in the materials to be screened, and identifies whether the items in the materials to be screened are damaged based on the images of the items.

6. The method according to claim 1, characterized in that The method further comprises: In response to a retrieval instruction for a first material, the drone sends a retrieval signal; wherein the retrieval signal includes a retrieval condition, the retrieval condition including at least one of the following: content of the item to be retrieved, retrieval of materials that enter the logistics park within a first time period, retrieval of materials of a first storage type, retrieval of materials stored in the logistics park in a first storage method, and retrieval of materials stored at a first storage location; The electronic tag receives the extraction condition in the extraction signal, and determines whether the material corresponding to the electronic tag matches the extraction condition based on the extraction condition and the storage data set by the electronic tag; the electronic tag is provided with a prompt light; If the material corresponding to the electronic tag itself matches the extraction condition, the prompt light set in the electronic tag is controlled to operate; The image acquisition device provided on the drone identifies the first electronic tag running the prompt light, controls the drone to fly to the position of the first electronic tag, and controls the robotic arm provided on the drone to extract the first material corresponding to the first electronic tag from the plurality of materials.

7. The method according to claim 6, characterized in that After the image acquisition device provided on the UAV recognizes the first electronic tag of the prompt light, the method further includes: Comparing the first storage data stored in the first electronic tag with the model storage data of the virtual material corresponding to the first electronic tag in the 3D model of the storage material; If it is detected through comparison that the first storage data is inconsistent with the model storage data, the 3D model of the stored materials is corrected according to the first storage data to keep the 3D model of the stored materials updated.

8. A 3D modeling system based on logistics parks and warehouse materials, characterized by: All materials in the logistics park are provided with electronic tags; the electronic tags are provided with storage data of the corresponding materials in the logistics park, and the storage data includes the content of the materials, the time when the materials entered the logistics park, the storage type of the materials in the logistics park, the storage method of the materials in the logistics park, and the storage location of the materials in the logistics park; The 3D modeling system based on logistics parks and warehouse materials includes: A first sending module is configured to, in response to a 3D modeling instruction for the material, cause the drone in the logistics park to send a broadcast signal in a broadcasting form; the broadcast signal includes data to be modeled, and the data to be modeled includes at least one of the following: content of the item to be modeled, materials to be modeled that enter the logistics park within a target time, a storage type to be modeled in the logistics park, materials to be modeled stored in the logistics park in a target storage method, and materials to be modeled stored at a target storage location; A second sending module is configured for the electronic tag to receive the broadcast signal and send a feedback signal in response to the broadcast signal according to the data to be modeled; the feedback signal includes target warehouse data that matches the data to be modeled and a material identifier of the target material corresponding to the electronic tag; A scanning module, configured to use a scanning device provided on the drone to scan all the electronic tags in the logistics park to receive the feedback signal; A modeling module is used for the data processing system corresponding to the drone to perform 3D modeling of the storage materials for each target material in the logistics park based on the target storage data and the material identification in the feedback signal to obtain a 3D model of the storage materials.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to execute the method according to any one of claims 1 to 7.

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