Intelligent book positioning and sorting system and method based on virtual reality augmented technology

Abstract

The present invention relates to the field of virtual reality enhancement technology, and in particular to an intelligent book positioning and sorting system and method based on virtual reality enhancement technology. The method comprises the following steps: acquiring environmental scanning data and environmental perception images; performing internal space contour feature recognition on the environmental scanning data to obtain internal geometric contour feature data of the library; performing library geometric contour feature recognition on the environmental perception image to obtain internal geometric contour feature data of the library; constructing a library virtual reality environment through the internal space structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library. The present invention improves the accuracy, real-time update, environmental modeling and operation efficiency of traditional book positioning and sorting by integrating virtual reality enhancement technology, UWB positioning, intelligent path planning and automatic control.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality enhancement technology, and in particular to an intelligent book positioning and sorting system and method based on virtual reality enhancement technology. Background Art

[0002] At first, libraries used barcode and RFID technologies to improve the automation level of book management. Barcode technology simplifies the borrowing and returning of books, but it still has limitations in the accuracy and efficiency of positioning and sorting. The introduction of RFID technology makes book tracking and inventory management more efficient, but it is still not adaptable enough to real-time positioning and complex environments. With the rise of virtual reality and augmented reality technologies, library management systems have been innovated. Virtual reality technology provides librarians with a more intuitive way to locate and manage books by building a three-dimensional virtual environment. Augmented reality technology helps managers quickly identify and locate books by superimposing virtual information in the actual library environment, thereby improving the accuracy and efficiency of sorting. In recent years, combined with machine learning and artificial intelligence technologies, intelligent book positioning and sorting methods based on virtual reality augmented technology have begun to be applied. However, the spatial data and book information of traditional libraries are often not fully integrated, resulting in limited construction and enhancement of virtual environments. At the same time, path planning usually ignores real-time environmental changes and obstacle avoidance requirements, resulting in insufficient path optimization, which in turn leads to low efficiency and accuracy in the book positioning and sorting process. Summary of the invention

[0003] Based on this, it is necessary to provide an intelligent book positioning and sorting system and method based on virtual reality augmented technology to solve at least one of the above technical problems.

[0004] To achieve the above purpose, an intelligent book positioning and sorting method based on virtual reality augmented technology is provided, the method comprising the following steps:

[0005] Step S1: Acquire environmental scanning data and environmental perception images; perform internal space contour feature recognition on the environmental scanning data to obtain internal geometric contour feature data of the library; perform library geometric contour feature recognition on the environmental perception image to obtain internal geometric contour feature data of the library; construct a library virtual reality environment through the internal space structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library;

[0006] Step S2: obtaining library book data, including library book text type data and library book image type data; classifying book types according to the library book text type data to generate library book type data; extracting cover image features of the library book image type data based on the library book type data to obtain book cover image feature data; importing the book cover text information data and the book cover image feature data into a virtual three-dimensional library to generate a virtual reality enhanced interface to obtain virtual reality enhanced interface data;

[0007] Step S3: Deploy UWB signal base stations using the virtual three-dimensional library; attach UWB tags to books based on the UWB signal base stations according to the virtual reality enhanced interface data to generate book tag data; connect nodes through the UWB signal base stations and the book tag data to generate a UWB book positioning network; dynamically update the virtual reality enhanced interface data based on the UWB book positioning network to generate real-time book location data;

[0008] Step S4: obtaining the user's current location information data; calculating the shortest obstacle-avoiding book-picking path based on the real-time book location data and the virtual three-dimensional library, and generating optimized book-picking path data; mapping the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, and generating a dynamic path display interface; generating robot grasping path navigation instructions according to the dynamic path display interface, and obtaining robot path navigation instructions to perform intelligent book positioning and sorting operations.

[0009] The present invention can accurately identify the geometric contour features of the library by acquiring environmental scanning data and environmental perception images, ensuring that the construction of the virtual three-dimensional library is real and detailed. The generated virtual three-dimensional library provides a visual environment for subsequent operations, helping users to understand and manage the internal structure of the library more intuitively. By classifying and extracting features from the text and image data of library books, the information of each book can be accurately displayed in the virtual three-dimensional library. The generation of a virtual reality enhanced interface enables users to browse and locate books intuitively in a virtual environment, improving the operating efficiency and user experience of the library. By using UWB signal base stations and tags, high-precision positioning of books is achieved, and the real-time location of books can be accurately tracked. The dynamic update of real-time book location data ensures the immediacy of the location of books in the library and improves the accuracy and reliability of book positioning. By calculating the shortest obstacle avoidance book picking path and generating optimized book picking path data, the efficiency of book picking is improved, and the operation time and error are reduced. The dynamic display of the path and the generation of robot path navigation instructions realize intelligent operation, automatically complete the book positioning and sorting tasks, and improve the overall work efficiency. Therefore, the present invention improves the accuracy, real-time updating, environmental modeling and operational efficiency of traditional book positioning and sorting by integrating virtual reality enhancement technology, UWB positioning, intelligent path planning and automatic control.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S11: Obtaining environment scanning data and environment perception images through a laser radar sensor and a depth camera;

[0012] Step S12: performing image preprocessing on the environment perception image to generate a standard environment perception image, wherein the image preprocessing includes image filtering, image brightness enhancement and image grayscale value transformation; performing multi-view image fusion on the standard environment perception image to generate a multi-view fusion image;

[0013] Step S13: Performing library internal space structure analysis on the environmental scanning data to generate library internal space structure data; performing library geometric contour feature recognition on the multi-view fusion image to obtain library internal geometric contour feature data;

[0014] Step S14: constructing a virtual reality environment of the library through the internal spatial structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library.

[0015] The present invention uses a laser radar sensor and a depth camera to obtain high-precision environmental scanning data and perception images to ensure a comprehensive perception of the library's internal environment. Through image preprocessing technology (filtering, brightness enhancement, grayscale value transformation), the image quality is significantly improved, making the details inside the library clearer. Multi-view image fusion technology provides a three-dimensional perception of the library's internal space, enhancing spatial understanding and visual effects. The analysis of environmental scanning data generates accurate internal spatial structure data of the library, providing a reliable foundation for the subsequent construction of a virtual reality environment. Accurately identify the geometric contour feature data inside the library to ensure the realism and detail presentation of the virtual three-dimensional library. The generated virtual three-dimensional library provides a realistic virtual reality environment, improves the user experience, and allows users to explore and navigate the library in a virtual environment. The virtual three-dimensional library is not only used for user experience, but can also be used for library management and planning, optimizing spatial layout and resource allocation.

[0016] Preferably, step S14 includes the following steps:

[0017] Step S141: performing library space corner point analysis based on the library internal space structure data and the library internal geometric contour feature data to generate library space corner point data;

[0018] Step S142: performing point cloud conversion on the library space corner point data to obtain the library space corner point cloud data;

[0019] Step S143: performing point-line-surface pattern three-dimensional grid modeling according to the library space corner point cloud data to generate the library three-dimensional grid data;

[0020] Step S144: texture mapping the library three-dimensional mesh data to generate library three-dimensional texture mapping data; texture mapping the library three-dimensional texture mapping data and the library three-dimensional mesh data to generate a virtual three-dimensional library.

[0021] The present invention performs library space corner point analysis through library internal space structure data and geometric contour feature data to generate library space corner point data. This step ensures that the key points of the library internal structure are captured, providing a basis for subsequent modeling. The library space corner point data is converted into point cloud data to obtain the library space corner point cloud data. The point cloud data provides three-dimensional coordinate information of the space corner points, making the three-dimensional representation of the library internal structure more accurate. According to the library space corner point cloud data, three-dimensional grid modeling of point, line and surface modes is performed to generate library three-dimensional grid data. This step converts the point cloud data into grid data with a geometric structure to construct a three-dimensional framework inside the library. Texture mapping is performed on the library three-dimensional grid data to generate library three-dimensional texture mapping data. Texture mapping increases the realism of the three-dimensional model by attaching image information to the three-dimensional grid. The library three-dimensional texture mapping data and the three-dimensional grid data are texture mapped to generate a virtual three-dimensional library. This step ensures that the three-dimensional model has a realistic appearance, making the virtual three-dimensional library more immersive. Through the library space corner point analysis, the key points of the library internal structure are accurately captured to ensure the high precision of subsequent modeling. Point cloud conversion provides detailed 3D coordinate information, making the representation of the library's internal structure more accurate and facilitating high-precision 3D modeling. Through 3D mesh modeling in point, line, and surface modes, point cloud data is converted into mesh data with geometric structure to construct a 3D framework inside the library. Texture mapping and mapping give the 3D model a realistic appearance, enhancing the realism and immersion of the virtual 3D library. The high-precision and high-realism virtual 3D library improves the user experience, allowing users to better explore and navigate the interior of the library in a virtual environment.

[0022] Preferably, step S2 comprises the following steps:

[0023] Step S21: obtaining library book data, including library book text type data and library book image type data;

[0024] Step S22: preprocessing the library book text type data to generate standard library book text type data, wherein the data preprocessing includes data cleaning, data denoising, data missing value filling and data standardization;

[0025] Step S23: extracting book cover text from the standard library book text type data to obtain book cover text information data; classifying the library book data into book types according to the book cover text information data to generate library book type data; extracting cover image features from the library book image type data based on the library book type data to obtain book cover image feature data;

[0026] Step S24: importing the book cover text information data and the book cover image feature data into the virtual three-dimensional library to generate a virtual reality enhanced interface, thereby obtaining virtual reality enhanced interface data.

[0027] The present invention ensures the accuracy and completeness of the text type data of library books through preprocessing steps, and provides a reliable basis for subsequent data analysis and processing. Through book cover text extraction and book type classification, automatic classification of book information is realized, and the efficiency and accuracy of book management are improved. Cover image feature extraction allows the image data of library books to be effectively utilized, enhancing the diversity and richness of book information. Text information and image feature data are imported into a virtual three-dimensional library to generate virtual reality enhanced interface data, so that users can experience enhanced book information display in a virtual environment, improving the user's interactive experience. The virtual reality enhanced interface provides users with a more intuitive and immersive way to browse books, improving the library's service quality and user satisfaction. Through the comprehensive processing and application of book text and image data, the utilization rate of data is improved, and the value of library book data is fully utilized.

[0028] Preferably, step S24 includes the following steps:

[0029] Step S241: parsing the book cover text information data for book key text information to obtain book cover key information data, wherein the book cover key information data includes the book title, author and ISBN;

[0030] Step S242: extracting key points and descriptors from the book image feature data to obtain book image key points and book image descriptors; performing principal component analysis based on the book image key points and book image descriptors to generate a book image feature vector;

[0031] Step S243: importing the book title, author and ISBN into the database in the virtual three-dimensional library to perform field query to obtain preliminary text matching data; importing the book image feature vector into the virtual three-dimensional library to perform image similarity calculation to obtain book image feature similarity data;

[0032] Step S244: performing comprehensive book matching analysis based on the preliminary text matching data and the book image feature similarity data to generate comprehensive book matching data; using the comprehensive book matching data to screen candidate matching books for the virtual three-dimensional library to generate candidate matching book data;

[0033] Step S245: Based on the candidate matching book data, the virtual scene position of the virtual three-dimensional library is mapped to generate book positioning data; the book scene modeling of the candidate matching book data is performed through the book positioning data to generate virtual scene book model data; the virtual three-dimensional library is integrated with a virtual reality enhanced interface through the virtual scene book model data to obtain virtual reality enhanced interface data.

[0034] The present invention improves the efficiency and accuracy of data processing by extracting and analyzing text and image features. Accurate book matching is achieved through comprehensive text matching and image similarity calculation, which improves the matching degree and user satisfaction of the virtual three-dimensional library. The realism and user experience of the virtual three-dimensional library are improved through book scene modeling and location mapping. The integration of the virtual reality enhanced interface provides users with a richer and more intuitive interaction method, which improves the user's immersion and participation. Combining the multi-dimensional features of book text and image data, the library's data resources are fully utilized to provide users with a more comprehensive display of book information. Through the data integration and management of the virtual three-dimensional library, the unified processing and display of book information is achieved, simplifying the library management process.

[0035] Preferably, step S3 comprises the following steps:

[0036] Step S31: deploying UWB signal base stations using a virtual three-dimensional library;

[0037] Step S32: Based on the UWB signal base station, a UWB tag is added to the book according to the virtual reality enhanced interface data to generate book tag data;

[0038] Step S33: performing virtual edge computing node site selection for the virtual three-dimensional library through a preset edge computing node range to generate edge node site selection data; performing edge computing node configuration for the book tag data according to the edge node site selection data to generate edge computing node configuration data; performing node connection between the edge computing node configuration data and the UWB signal base station to generate a UWB book positioning network;

[0039] Step S34: dynamically updating the book position of the virtual reality enhanced interface data according to the UWB book positioning network to generate real-time book position data.

[0040] The present invention realizes high-precision positioning of books through the deployment of UWB signal base stations and UWB tags, ensuring that the location of books in the virtual three-dimensional library can be updated and tracked in real time. The UWB book positioning network is used to ensure that the book location data in the virtual reality enhanced interface is updated in real time, providing users with the latest book location information. The configuration and deployment of edge computing nodes improves the efficiency of data processing and transmission, reduces latency, and improves the response speed and user experience of the virtual three-dimensional library. Through the intelligent book location update and management system, the library can manage the location of books more efficiently, reduce search time, and improve operational efficiency. Real-time, accurate book positioning and dynamic updating enhance the user experience in the virtual three-dimensional library, allowing users to find the required books more easily and improve satisfaction. The flexible deployment of UWB signal base stations and edge computing nodes ensures the comprehensive coverage of the virtual three-dimensional library, and also has good scalability, which can be adjusted and optimized according to needs.

[0041] Preferably, step S34 includes the following steps:

[0042] Step S341: Based on the UWB signal base station, the pulse arrival time of the UWB book positioning network and the book tag data is measured to generate preliminary distance data;

[0043] Step S342: Calculate the book arrival time difference on the preliminary distance data by using the arrival time difference algorithm to generate the book arrival time difference position data; perform Kalman filter data fusion on the book arrival time difference position data to generate the book optimized position data;

[0044] Step S343: The optimized book location data is transmitted and stored in the central local area network to generate book location storage data; the edge computing node is used to obtain the real-time location calculation result of the book location storage data to generate book location update data;

[0045] Step S344: dynamically refreshing the virtual reality augmented interface data based on the book position using the book position update data, thereby generating real-time book position data.

[0046] The present invention realizes high-precision real-time positioning of books through the pulse arrival time measurement and arrival time difference algorithm of the UWB signal base station, combined with Kalman filter data fusion. The book location data is smoothed by Kalman filtering, which reduces noise interference and improves the stability and accuracy of the data. The combination of central LAN transmission and edge computing nodes ensures the real-time update of book location data, so that the book location in the virtual three-dimensional library can be refreshed instantly. Real-time and accurate book location updates enhance the user experience in the virtual three-dimensional library, allowing users to quickly find the required books, improving the library's operating efficiency and user satisfaction. The dynamic refresh and high-precision positioning of real-time book location data help the library to achieve intelligent management and reduce the time and labor cost of finding books. Through the flexible deployment of UWB book positioning network and edge computing nodes, the system has good scalability and flexibility, and can be adjusted and optimized according to the needs of the library.

[0047] Preferably, step S4 comprises the following steps:

[0048] Step S41: obtaining the user's current location information data; performing book retrieval path planning based on the real-time book location data and the virtual three-dimensional library, and generating initial book retrieval path planning data;

[0049] Step S42: Calculate the shortest obstacle-avoiding book-picking path for the initial book-picking path planning data according to the user's current location information data, and generate optimized book-picking path data;

[0050] Step S43: Mapping the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, generating a dynamic path display interface; generating robot grabbing path navigation instructions according to the dynamic path display interface, obtaining robot path navigation instructions, and executing intelligent book positioning and sorting operations.

[0051] The present invention obtains the user's current location information and performs path planning and optimization, so that the user can easily find and get the required books in the virtual three-dimensional library, thereby improving the user experience. The shortest path and obstacles are considered to ensure that the user and the robot can find the target book smoothly, reducing time waste and potential collisions. The book retrieval path is dynamically displayed in the virtual reality enhanced interface, so that the user can clearly understand and follow the path, improving the intuitiveness and accuracy of the operation. By generating robot path navigation instructions, intelligent book positioning and sorting operations are realized, reducing manual operations and improving the automation level and work efficiency of the library. By combining user location information and real-time book location data, efficient book retrieval path planning and optimization are achieved, which helps the library to achieve intelligent management. Through obstacle avoidance calculation, the risk of collision between users and robots in the library is reduced, and the safety of operation is improved. Through the UWB book positioning network and path planning technology, the accurate positioning and tracking of books and user positions are ensured, and the reliability of the system is improved.

[0052] Preferably, step S42 includes the following steps:

[0053] Step S421: performing static obstacle recognition on the multi-view fusion image to generate static obstacle distribution data;

[0054] Step S422: performing time series position analysis on the user's current location information data to generate user movement path data;

[0055] Step S423: Divide the user movement path data into data sets to generate a model training set and a model test set; perform model training on the model training set using a random forest algorithm to generate a user dynamic movement training model; perform model testing on the user dynamic movement training model using a model test set to generate a user dynamic movement prediction model;

[0056] Step S424: Use the user dynamic movement prediction model to predict the user movement path data and generate dynamic user movement prediction data; calculate the shortest obstacle avoidance book picking path for the initial book picking path planning data based on the dynamic user movement prediction data and the static obstacle distribution data to generate optimized book picking path data.

[0057] The static obstacle data obtained by the laser radar and the user dynamic movement prediction model can accurately plan the book retrieval path, avoid static and dynamic obstacles, and provide the optimal path. The user movement prediction model can predict the user's future movement path, making the path planning more forward-looking and intelligent, and avoiding potential collisions and conflicts. Through the optimized book retrieval path, users can find the required books more quickly, reduce the movement time in the library, and improve the user experience. The random forest algorithm provides an efficient user movement prediction model that can quickly respond and adjust the path planning to ensure the real-time and accuracy of the path. Accurate path planning and dynamic prediction enable the library to better manage and control the internal book retrieval process and improve overall operational efficiency. Obstacle avoidance path calculation can effectively avoid collisions between users and robots in the library and improve the safety of users and equipment. Through time series analysis and machine learning algorithms, data is used to make path optimization decisions to improve the scientificity and reliability of decisions.

[0058] In this specification, a smart book positioning and sorting system based on virtual reality enhancement technology is provided, which is used to execute the above-mentioned smart book positioning and sorting method based on virtual reality enhancement technology. The smart book positioning and sorting system based on virtual reality enhancement technology includes:

[0059] A virtual reality environment construction module is used to obtain environment scanning data and environment perception images; perform internal space contour feature recognition on the environment scanning data to obtain the internal geometric contour feature data of the library; perform library geometric contour feature recognition on the environment perception image to obtain the internal geometric contour feature data of the library; construct a library virtual reality environment through the library internal space structure data and the library internal geometric contour feature data to generate a virtual three-dimensional library;

[0060] The virtual book generation module is used to obtain library book data, including library book text type data and library book image type data; classify the book types according to the library book text type data to generate the library book type data; extract the cover image features of the library book image type data based on the library book type data to obtain the book cover image feature data; import the book cover text information data and the book cover image feature data into the virtual three-dimensional library to generate a virtual reality enhanced interface to obtain the virtual reality enhanced interface data;

[0061] The book tag module is used to deploy UWB signal base stations using a virtual three-dimensional library; based on the UWB signal base station, UWB tags are added to books according to the virtual reality enhanced interface data to generate book tag data; nodes are connected through the UWB signal base station and the book tag data to generate a UWB book positioning network; the virtual reality enhanced interface data is dynamically updated according to the UWB book positioning network to generate real-time book location data;

[0062] The path planning module is used to obtain the user's current location information data; calculate the shortest obstacle-avoiding book-picking path based on the real-time book location data and the virtual three-dimensional library, and generate optimized book-picking path data; map the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, and generate a dynamic path display interface; generate robot grasping path navigation instructions based on the dynamic path display interface, and obtain robot path navigation instructions to perform intelligent book positioning and sorting operations.

[0063] The beneficial effect of the present invention is that through environmental scanning data and image recognition technology, the system can build a high-precision virtual three-dimensional library environment, and this high-quality virtual environment can provide users with a realistic virtual reality experience. By processing the text and image data of library books, the system can automatically classify and extract features of books, which makes book management more systematic and improves the operational efficiency of the library. Using UWB signal base stations for book labeling and positioning, the system can update the location of books in real time and generate an accurate book positioning network. This technology supports efficient book search and management, and reduces the time and error of manual positioning. Based on the user's current location and real-time book location data, the system can calculate the shortest obstacle avoidance book retrieval path. This function enables users to find and get the required books faster and more conveniently. The optimized book retrieval path is mapped to the virtual reality enhanced interface, and users can view the book retrieval path in real time in the virtual environment, enhancing the user's interactive experience. By generating robot path navigation instructions, the system can realize intelligent book positioning and sorting operations. This function reduces the need for manual operation and improves the work efficiency and accuracy of the library. Therefore, the present invention improves the accuracy, real-time updating, environmental modeling and operational efficiency of traditional book positioning and sorting by integrating virtual reality enhancement technology, UWB positioning, intelligent path planning and automatic control. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of the steps of an intelligent book positioning and sorting method based on virtual reality augmented technology;

[0065] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0066] Figure 3 for Figure 1 Detailed implementation steps of step S3 in FIG.

[0067] Figure 4 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0068] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0069] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0070] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0071] It should be understood that although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, and the term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0072] To achieve this, please refer to Figures 1 to 4 , an intelligent book positioning and sorting method based on virtual reality augmented technology, the method comprising the following steps:

[0073] Step S1: Acquire environmental scanning data and environmental perception images; perform internal space contour feature recognition on the environmental scanning data to obtain internal geometric contour feature data of the library; perform library geometric contour feature recognition on the environmental perception image to obtain internal geometric contour feature data of the library; construct a library virtual reality environment through the internal space structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library;

[0074] Step S2: obtaining library book data, including library book text type data and library book image type data; classifying book types according to the library book text type data to generate library book type data; extracting cover image features of the library book image type data based on the library book type data to obtain book cover image feature data; importing the book cover text information data and the book cover image feature data into a virtual three-dimensional library to generate a virtual reality enhanced interface to obtain virtual reality enhanced interface data;

[0075] Step S3: Deploy UWB signal base stations using the virtual three-dimensional library; attach UWB tags to books based on the UWB signal base stations according to the virtual reality enhanced interface data to generate book tag data; connect nodes through the UWB signal base stations and the book tag data to generate a UWB book positioning network; dynamically update the virtual reality enhanced interface data based on the UWB book positioning network to generate real-time book location data;

[0076] Step S4: obtaining the user's current location information data; calculating the shortest obstacle-avoiding book-picking path based on the real-time book location data and the virtual three-dimensional library, and generating optimized book-picking path data; mapping the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, and generating a dynamic path display interface; generating robot grasping path navigation instructions according to the dynamic path display interface, and obtaining robot path navigation instructions to perform intelligent book positioning and sorting operations.

[0077] The present invention can accurately identify the geometric contour features of the library by acquiring environmental scanning data and environmental perception images, ensuring that the construction of the virtual three-dimensional library is real and detailed. The generated virtual three-dimensional library provides a visual environment for subsequent operations, helping users to understand and manage the internal structure of the library more intuitively. By classifying and extracting features from the text and image data of library books, the information of each book can be accurately displayed in the virtual three-dimensional library. The generation of a virtual reality enhanced interface enables users to browse and locate books intuitively in a virtual environment, improving the operating efficiency and user experience of the library. By using UWB signal base stations and tags, high-precision positioning of books is achieved, and the real-time location of books can be accurately tracked. The dynamic update of real-time book location data ensures the immediacy of the location of books in the library and improves the accuracy and reliability of book positioning. By calculating the shortest obstacle avoidance book picking path and generating optimized book picking path data, the efficiency of book picking is improved, and the operation time and error are reduced. The dynamic display of the path and the generation of robot path navigation instructions realize intelligent operation, automatically complete the book positioning and sorting tasks, and improve the overall work efficiency. Therefore, the present invention improves the accuracy, real-time updating, environmental modeling and operational efficiency of traditional book positioning and sorting by integrating virtual reality enhancement technology, UWB positioning, intelligent path planning and automatic control.

[0078] In the embodiment of the present invention, reference Figure 1 The above is a schematic diagram of the steps of an intelligent book positioning and sorting method based on virtual reality augmented technology of the present invention. In this example, the intelligent book positioning and sorting method based on virtual reality augmented technology includes the following steps:

[0079] Step S1: Acquire environmental scanning data and environmental perception images; perform internal space contour feature recognition on the environmental scanning data to obtain internal geometric contour feature data of the library; perform library geometric contour feature recognition on the environmental perception image to obtain internal geometric contour feature data of the library; construct a library virtual reality environment through the internal space structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library;

[0080] In an embodiment of the present invention, environmental scanning data inside the library is obtained by using a laser scanner, a structured light scanner, or a LIDAR device. A high-resolution camera or a panoramic camera is used to obtain an environmental perception image inside the library. Scanning and shooting are performed at multiple locations inside the library to ensure that all areas of the library are covered, including bookshelves, reading areas, passages, etc. The acquired environmental scanning data is preprocessed to remove noise and redundant data and perform data cleaning. Three-dimensional point cloud processing software (such as PCL, Meshlab, etc.) is used to identify the contour features of the internal space. The geometric contour features inside the library, such as the shape and position of the wall, ceiling, floor, and bookshelf, are extracted. The extracted geometric contour feature data is formatted into a data format that can be used for modeling, such as OBJ, PLY, etc. The environmental perception image is preprocessed to remove noise, perform color correction, etc. Image processing technology (such as OpenCV) and deep learning algorithms (such as convolutional neural networks) are used to identify geometric contour features. The geometric contour features inside the library, such as the shape of the bookshelf and the texture of the wall, etc., are extracted. The extracted geometric contour feature data is matched and fused with the environmental scanning data to ensure the consistency and integrity of the data. Integrate environmental scan data and perception image data into a unified coordinate system to ensure accurate positioning of geometric contour features. Use 3D modeling software (such as Blender, 3ds Max, Maya, etc.) to perform 3D modeling based on the integrated data. Generate a 3D model of the library interior, including walls, floors, ceilings, bookshelves, tables and chairs, etc. Use environmental perception images to add textures to the 3D model to make the virtual library look more realistic. Import the 3D model into a virtual reality development platform (such as Unity, UnrealEngine). Configure the lighting, materials, interactive functions, etc. of the virtual reality environment. Generate the final virtual 3D library. A complete virtual reality environment, including precise geometric contours and realistic textures. Users can use virtual reality devices (such as VR headsets) for an immersive experience and browse various areas inside the library.

[0081] Step S2: obtaining library book data, including library book text type data and library book image type data; classifying book types according to the library book text type data to generate library book type data; extracting cover image features of the library book image type data based on the library book type data to obtain book cover image feature data; importing the book cover text information data and the book cover image feature data into a virtual three-dimensional library to generate a virtual reality enhanced interface to obtain virtual reality enhanced interface data;

[0082] In an embodiment of the present invention, the text data of the book, including the title, author, ISBN, category, publication date, etc., is obtained through the library's management system (such as ILS or OPAC). The cover image of the book can be obtained by: directly extracting from the library's management system; scanning or photographing the actual book cover; downloading from an online database (such as Google Books, Open Library). The obtained text data is preprocessed, including removing duplicates, correcting erroneous data, standardizing the format, etc. The image data is preprocessed, including adjusting the resolution, removing noise, cropping, etc. Based on the text data of the book, a suitable classification method is selected, which can be based on a predefined classification system (such as Dewey Decimal Classification, Library Classification) or automatic classification using a machine learning method. The text data of the book is analyzed and classified using natural language processing (NLP) technology. Commonly used NLP technologies include TF-IDF, word embedding (Word2Vec, GloVe), and classification algorithms (SVM, Naive Bayes, Neural Network, etc.). The library book type data is generated according to the classification results, and the data format is JSON or CSV. Use computer vision tools (such as OpenCV) and deep learning frameworks (such as TensorFlow, PyTorch) to extract image features. Use pre-trained convolutional neural network (CNN) models (such as VGG, ResNet, Inception) to extract features from cover images. Perform feature extraction on cover images to obtain feature vectors of images. Format the extracted cover image feature data into JSON or CSV format. Integrate text information data and cover image feature data into the virtual 3D library. Ensure data consistency and integrity. Design a book display interface in the virtual 3D library, including the layout of bookshelves, the placement of books, and the display of cover images. Add interactive features so that users can click on books to view detailed information. Use virtual reality development platforms (such as Unity, Unreal Engine) to import the integrated data and generate an enhanced interface. Configure the visual effects and interactive functions of the interface.

[0083] Step S3: Deploy UWB signal base stations using the virtual three-dimensional library; attach UWB tags to books based on the UWB signal base stations according to the virtual reality enhanced interface data to generate book tag data; connect nodes through the UWB signal base stations and the book tag data to generate a UWB book positioning network; dynamically update the virtual reality enhanced interface data based on the UWB book positioning network to generate real-time book location data;

[0084] In the embodiment of the present invention, by selecting a suitable UWB signal base station, it is ensured that its coverage can cover the entire library. Common UWB base station brands include Decawave, Zebra, etc. Select several suitable locations in the library to install UWB signal base stations to ensure uniform signal coverage. The installation locations of the base stations should include various major areas of the library, such as bookshelves, reading areas, passages, etc. During the installation process, it is necessary to ensure that the distance and height between the base stations are appropriate to avoid signal interference and coverage blind spots. After the installation is completed, the base station is calibrated to ensure that the positioning accuracy of each base station meets the requirements. Professional UWB calibration tools or software can be used for calibration. Select a suitable UWB tag to ensure that the tag is small and light and will not affect the use and storage of books. The tag should have good signal transmission performance and a long battery life. Attach the UWB tag to the book, and you can choose to stick it on the back cover or inside of the book without affecting the appearance and use of the book. Generate a unique tag ID for each book, and record the correspondence between the ID and the book information. Generate corresponding tag data for each book, including book ID, tag ID, book title, author, classification and other information. The tag data is stored in the database for subsequent query and update. A connection is established between the UWB signal base station and the UWB tag on the book to form a UWB book positioning network. Each base station periodically communicates with the tag to obtain the real-time location information of the tag. The real-time location of each book is calculated using triangulation or other positioning algorithms. Common positioning algorithms include TDOA (time difference of arrival), AOA (angle of arrival), etc. The acquired book location data is processed to filter out abnormal data to ensure positioning accuracy. Dynamic book location data is generated based on the real-time location information of the book. The real-time acquired book location data is integrated with the book information in the virtual 3D library. Ensure the real-time and accuracy of the book location data. The location of the book is updated in real time in the enhanced interface of the virtual 3D library. A dynamic display function of the book location is provided so that users can intuitively view the current location of the book.

[0085] Step S4: obtaining the user's current location information data; calculating the shortest obstacle-avoiding book-picking path based on the real-time book location data and the virtual three-dimensional library, and generating optimized book-picking path data; mapping the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, and generating a dynamic path display interface; generating robot grasping path navigation instructions according to the dynamic path display interface, and obtaining robot path navigation instructions to perform intelligent book positioning and sorting operations.

[0086] In an embodiment of the present invention, the current position of the user is obtained by using a UWB positioning system, a Wi-Fi positioning system, a Bluetooth positioning system or a combined positioning system. The coordinates of the current position of the user are obtained by a positioning device or a mobile device. The internal structure of the library is modeled in a virtual three-dimensional library, including bookshelves, passages, obstacles, etc. Ensure that the environmental model is consistent with reality and facilitate path planning. Use a path planning algorithm such as the Dijkstra algorithm or RRT (rapid random tree) to calculate the shortest path. Consider obstacle avoidance factors to ensure that the path is safe and feasible. Integrate the calculated path data with the environmental data in the virtual three-dimensional library. Ensure the dynamic and real-time nature of the path data. Dynamically display the path in the enhanced interface of the virtual three-dimensional library to help users and robots understand the best path for taking books. Provide path guidance and real-time update functions. Generate robot navigation instructions based on the calculated shortest path. The instructions include information such as moving direction, speed, and turning angle. The robot receives the navigation instructions, performs path navigation according to the instructions, and grabs the target book. Adjust the path through sensors and feedback systems to ensure accurate positioning and grabbing.

[0087] Preferably, step S1 comprises the following steps:

[0088] Step S11: Obtaining environment scanning data and environment perception images through a laser radar sensor and a depth camera;

[0089] Step S12: performing image preprocessing on the environment perception image to generate a standard environment perception image, wherein the image preprocessing includes image filtering, image brightness enhancement and image grayscale value transformation; performing multi-view image fusion on the standard environment perception image to generate a multi-view fusion image;

[0090] Step S13: Performing library internal space structure analysis on the environmental scanning data to generate library internal space structure data; performing library geometric contour feature recognition on the multi-view fusion image to obtain library internal geometric contour feature data;

[0091] Step S14: constructing a virtual reality environment of the library through the internal spatial structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library.

[0092] In the embodiment of the present invention, by installing a laser radar sensor and a depth camera in the library, the entire interior space of the library is ensured to be covered. The laser radar is used to obtain high-precision spatial distance data, and the depth camera is used to capture the depth information of the image. The laser radar scans the interior of the library, obtains environmental scanning data, and records the three-dimensional coordinates of each point. The depth camera captures the environmental perception image inside the library, including the depth image and the RGB image. The image is denoised using a Gaussian filter or a median filter to reduce noise interference. The image brightness is enhanced using histogram equalization or adaptive histogram equalization (CLAHE), and the RGB image is converted into a grayscale image to simplify subsequent processing. The environmental perception image is filtered, brightness enhanced, and grayscale value transformed in sequence to generate a standard environmental perception image. The images obtained from different perspectives are fused to generate a multi-perspective fusion image to enhance the integrity and details of the image. The environmental scanning data is analyzed to extract the internal spatial structure data of the library, such as walls, ceilings, and floors. The multi-perspective fusion image is subjected to geometric contour feature recognition to extract the geometric features inside the library, such as bookshelves, tables and chairs. Combine the library's internal spatial structure data and geometric contour feature data to build a virtual reality environment for the library using 3D modeling software (such as Unity or Unreal Engine). Import the extracted spatial structure data and geometric contour feature data into the virtual reality environment for scene rendering. Ensure that the structure and layout of the virtual 3D library are consistent with the actual library, providing realism and interactivity.

[0093] Preferably, step S14 includes the following steps:

[0094] Step S141: performing library space corner point analysis based on the library internal space structure data and the library internal geometric contour feature data to generate library space corner point data;

[0095] Step S142: performing point cloud conversion on the library space corner point data to obtain the library space corner point cloud data;

[0096] Step S143: performing point-line-surface pattern three-dimensional grid modeling according to the library space corner point cloud data to generate the library three-dimensional grid data;

[0097] Step S144: texture mapping the library three-dimensional mesh data to generate library three-dimensional texture mapping data; texture mapping the library three-dimensional texture mapping data and the library three-dimensional mesh data to generate a virtual three-dimensional library.

[0098] In an embodiment of the present invention, corner points are detected in the internal spatial structure data and geometric contour feature data of the library by using a corner detection algorithm (such as Harris corner detection and Shi-Tomasi corner detection), and the detected corner point coordinates are stored as the library space corner point data. The library space corner point data is converted into a point cloud data format (such as PCL point cloud format). The point cloud data is used to perform three-dimensional mesh modeling to generate the three-dimensional mesh data of the library. The Delaunay triangulation or Poisson surface reconstruction algorithm can be used to store the generated three-dimensional mesh data as the three-dimensional mesh data of the library. Texture mapping is performed on the three-dimensional mesh data, and the texture image is mapped onto the three-dimensional mesh to generate the three-dimensional texture mapping data of the library. The texture mapping data is combined with the three-dimensional mesh data to generate a virtual three-dimensional library.

[0099] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0100] Step S21: obtaining library book data, including library book text type data and library book image type data;

[0101] Step S22: preprocessing the library book text type data to generate standard library book text type data, wherein the data preprocessing includes data cleaning, data denoising, data missing value filling and data standardization;

[0102] Step S23: extracting book cover text from the standard library book text type data to obtain book cover text information data; classifying the library book data into book types according to the book cover text information data to generate library book type data; extracting cover image features from the library book image type data based on the library book type data to obtain book cover image feature data;

[0103] Step S24: importing the book cover text information data and the book cover image feature data into the virtual three-dimensional library to generate a virtual reality enhanced interface, thereby obtaining virtual reality enhanced interface data.

[0104] In an embodiment of the present invention, all book data including text type data and image type data of books are obtained from a library database. The text type data includes text information such as the title, author, and introduction of the book. The image type data includes the cover image and related images of the book. Redundant information and erroneous data in the book text type data are cleaned. Extra spaces, symbols, and format errors are removed. Noise in the text data, such as erroneous characters in the OCR (optical character recognition) process, is removed by an algorithm. For missing book text information, a suitable method is used to fill it, such as supplementing the missing information by searching other databases or using statistical methods to fill it. The book text type data is standardized and the data format is unified, such as unified character encoding, date format, etc. After the above processing, standard library book text type data is obtained. The text information on the book cover is extracted from the standard library book text type data using OCR technology to obtain book cover text information data. According to the book cover text information data, the books are classified into different types (such as novels, non-fiction, science and technology, art, etc.) to generate library book type data. Image processing technology is used to extract image features of the book cover from the library book image type data. Feature extraction includes color features, texture features, and shape features, etc., to obtain book cover image feature data. Integrate book cover text information data and book cover image feature data. Based on the integrated data, create a virtual three-dimensional library environment, and layout bookshelves, book display areas, etc. in the virtual environment. Import the integrated book cover text information and image feature data into the virtual three-dimensional library to generate virtual reality enhanced interface data, including the virtual cover of the book, book information display, etc. Design the user's interaction method with the virtual three-dimensional library, such as browsing, borrowing, and querying book information through gestures, voice, or controllers, and generate a complete virtual reality enhanced interface so that users can access and interact through virtual reality devices.

[0105] Preferably, step S24 includes the following steps:

[0106] Step S241: parsing the book cover text information data for book key text information to obtain book cover key information data, wherein the book cover key information data includes the book title, author and ISBN;

[0107] Step S242: extracting key points and descriptors from the book image feature data to obtain book image key points and book image descriptors; performing principal component analysis based on the book image key points and book image descriptors to generate a book image feature vector;

[0108] Step S243: importing the book title, author and ISBN into the database in the virtual three-dimensional library to perform field query and obtain preliminary text matching data; importing the book image feature vector into the virtual three-dimensional library to perform image similarity calculation and obtain book image feature similarity data;

[0109] Step S244: performing comprehensive book matching analysis based on the preliminary text matching data and the book image feature similarity data to generate comprehensive book matching data; using the comprehensive book matching data to screen candidate matching books for the virtual three-dimensional library to generate candidate matching book data;

[0110] Step S245: Based on the candidate matching book data, the virtual scene position of the virtual three-dimensional library is mapped to generate book positioning data; the book scene modeling of the candidate matching book data is performed through the book positioning data to generate virtual scene book model data; the virtual three-dimensional library is integrated with a virtual reality enhanced interface through the virtual scene book model data to obtain virtual reality enhanced interface data.

[0111] In an embodiment of the present invention, by parsing the book cover text information data, the key text information of the book, including the book title, author and ISBN, is extracted. In the parsing process, the natural language processing (NLP) technology is used to segment and recognize the text information to generate the book cover key information data. The key points and descriptors of the book cover image are extracted using an image processing algorithm (such as SIFT, SURF, etc.) to generate the book image key points and book image descriptors. The extracted book image key points and descriptors are subjected to principal component analysis (PCA) to reduce the dimension and highlight the important features to generate the book image feature vector. The book title, author and ISBN are imported into the database in the virtual three-dimensional library for field query. Preliminary text matching data is obtained through database query. The book image feature vector is imported into the image database in the virtual three-dimensional library to perform image similarity calculation to obtain the book image feature similarity data. The preliminary text matching data and the book image feature similarity data are integrated. The comprehensive matching degree analysis of the books is performed by weighted calculation or other algorithms to generate the book comprehensive matching degree data. According to the book comprehensive matching degree data, the books in the virtual three-dimensional library are screened to generate candidate matching book data. According to the candidate matching book data, the virtual scene position of the book is determined in the virtual three-dimensional library to generate book positioning data. Using the book positioning data, the candidate matching book is modeled in the virtual scene to generate virtual scene book model data. The virtual scene book model data is integrated into the virtual three-dimensional library to generate virtual reality enhanced interface data.

[0112] As an example of the present invention, refer to Figure 3 As shown, in this example, step S3 includes:

[0113] Step S31: deploying UWB signal base stations using a virtual three-dimensional library;

[0114] Step S32: Based on the UWB signal base station, a UWB tag is added to the book according to the virtual reality enhanced interface data to generate book tag data;

[0115] Step S33: performing virtual edge computing node site selection for the virtual three-dimensional library through a preset edge computing node range to generate edge node site selection data; performing edge computing node configuration for the book tag data according to the edge node site selection data to generate edge computing node configuration data; performing node connection between the edge computing node configuration data and the UWB signal base station to generate a UWB book positioning network;

[0116] Step S34: dynamically updating the book position of the virtual reality enhanced interface data according to the UWB book positioning network to generate real-time book position data.

[0117] In an embodiment of the present invention, an ultra-wideband (UWB) signal base station is deployed at each key location of a virtual three-dimensional library. The deployment of the signal base station needs to consider the coverage and signal strength of the library to ensure that the books in the entire library can be effectively located. Based on the deployed UWB signal base station, a UWB tag is attached to each book. The UWB tag will communicate with the base station through wireless signals to generate book tag data. The range of edge computing nodes is preset in the virtual three-dimensional library, and a suitable location is selected for node site selection to generate edge node site selection data. According to the selected edge node location, the book tag data is configured to the corresponding edge computing node to generate edge computing node configuration data. The edge computing node configuration data is connected to the UWB signal base station to form a complete UWB book positioning network. Using the UWB book positioning network, the book location in the virtual reality augmented interface is dynamically updated according to the UWB tag signal of the book to generate real-time book location data. Multiple UWB signal base stations are deployed on each floor and main area of ​​the library to ensure that there is no dead angle in the signal coverage. Each book is attached with a UWB tag, and the book tag data is generated through the signal receiving and sending functions of the base station. According to the layout of the library and the signal coverage, select multiple edge computing node locations and generate edge node site selection data. Configure the edge computing node to enable it to receive and process book tag data and generate edge computing node configuration data. Connect the edge computing node to the UWB signal base station to form a UWB book positioning network. According to the UWB tag signal of the book, update the location of the book in the virtual 3D library in real time. Combine the real-time book location data with the virtual reality enhanced interface data to provide the accurate location of the book.

[0118] Preferably, step S34 includes the following steps:

[0119] Step S341: Based on the UWB signal base station, the pulse arrival time of the UWB book positioning network and the book tag data is measured to generate preliminary distance data;

[0120] Step S342: Calculate the book arrival time difference on the preliminary distance data by using the arrival time difference algorithm to generate the book arrival time difference position data; perform Kalman filter data fusion on the book arrival time difference position data to generate the book optimized position data;

[0121] Step S343: The optimized book location data is transmitted and stored in the central local area network to generate book location storage data; the edge computing node is used to obtain the real-time location calculation result of the book location storage data to generate book location update data;

[0122] Step S344: dynamically refreshing the virtual reality augmented interface data based on the book position using the book position update data, thereby generating real-time book position data.

[0123] In an embodiment of the present invention, the pulse arrival time of the UWB signal from the base station to the book tag is measured by using the deployed UWB signal base station. The collected pulse arrival time data is used to calculate preliminary distance data. The measured pulse arrival time is converted into distance data to preliminarily estimate the location of the book. The preliminary distance data is analyzed by applying the arrival time difference algorithm to calculate the relative position of the book. The calculated time difference location data is used to accurately locate the book. The calculated book arrival time difference location data is input into the Kalman filter. The Kalman filter fuses and optimizes the data to generate optimized location data of the book to improve the positioning accuracy. The generated optimized location data of the book is transmitted to the data storage system through the central local area network. The storage system saves the data as book location storage data for further analysis and processing. The edge computing node is used to perform real-time calculation on the book location storage data to obtain the latest book location data. Book location update data is generated for dynamically updating the location of the book. According to the generated book location update data, the book location in the virtual reality enhanced interface is dynamically refreshed. The updated virtual reality interface displays the real-time location of the book, providing users with accurate book location information.

[0124] As an example of the present invention, refer to Figure 4 As shown, in this example, step S4 includes:

[0125] Step S41: obtaining the user's current location information data; planning the book retrieval path based on the real-time book location data and the virtual three-dimensional library, and generating initial book retrieval path planning data;

[0126] Step S42: Calculate the shortest obstacle-avoiding book-picking path for the initial book-picking path planning data according to the user's current location information data, and generate optimized book-picking path data;

[0127] Step S43: Mapping the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, generating a dynamic path display interface; generating robot grabbing path navigation instructions according to the dynamic path display interface, obtaining robot path navigation instructions, and executing intelligent book positioning and sorting operations.

[0128] In an embodiment of the present invention, the user's real-time location information data is obtained by using the user's mobile device or positioning sensor. Ensure that the acquired data includes the user's accurate location coordinates and positioning time. Based on the real-time book location data and the virtual three-dimensional library layout, book retrieval path planning is performed. The initial path from the user's current location to the target book location is calculated. Generate initial book retrieval path planning data, including path points, path length and estimated time. According to the user's current location and the initial book retrieval path planning data, the path calculation is performed using the shortest path algorithm (such as A* algorithm). Consider obstacles in the library (such as bookshelves, walls, etc.) and perform obstacle avoidance calculation. Generate the shortest path after obstacle avoidance, and optimize the book retrieval path to avoid obstacles. Generate optimized book retrieval path data based on the shortest obstacle avoidance path calculation result. Including optimized path points, total path length and estimated time. Map the optimized book retrieval path data to the virtual reality enhanced interface. Realize the dynamic display of the path, including path lines, path points and real-time positioning marks. Display the optimized path from the user to the book in the virtual reality interface to provide the user with real-time navigation information. Ensure that the path dynamic display interface is interactive, allowing the user to view path details and adjust the view. According to the path data generated by the dynamic path display interface, the robot grasping path navigation instructions are formulated. The instructions include the robot's route, turning points, speed control and path tracking information. The robot receives the path navigation instructions and performs intelligent book positioning and sorting operations. Ensure that the robot can accurately reach the book location according to the optimized path and complete the book retrieval and sorting.

[0129] Preferably, step S42 includes the following steps:

[0130] Step S421: performing static obstacle recognition on the multi-view fusion image to generate static obstacle distribution data;

[0131] Step S422: performing time series position analysis on the user's current location information data to generate user movement path data;

[0132] Step S423: Divide the user movement path data into data sets to generate a model training set and a model test set; perform model training on the model training set using a random forest algorithm to generate a user dynamic movement training model; perform model testing on the user dynamic movement training model using a model test set to generate a user dynamic movement prediction model;

[0133] Step S424: Use the user dynamic movement prediction model to predict the user movement path data and generate dynamic user movement prediction data; calculate the shortest obstacle avoidance book picking path for the initial book picking path planning data based on the dynamic user movement prediction data and the static obstacle distribution data to generate optimized book picking path data.

[0134] In an embodiment of the present invention, multi-view fusion image data of a virtual three-dimensional library is collected, including view images of static obstacles (such as bookshelves, walls, etc.). Image processing algorithms (such as edge detection and segmentation algorithms) are used to identify static obstacles in the image. Static obstacle distribution data is generated, including the location, size and type of the obstacle. The spatial distribution information of the identified static obstacles is recorded, and a static obstacle map is generated for obstacle avoidance calculation in path planning. The user's current location information data is obtained to ensure that accurate coordinates and timestamps are included. The user's real-time location data is analyzed, the user's mobile path data is generated, the user's mobile trend and trajectory changes are identified, and the user's mobile path is recorded, including historical location points, moving direction and speed information. The user's mobile path data is divided into a model training set and a model test set for model training and testing. The model training set is trained using a random forest algorithm. The random forest constructs multiple decision trees to learn the mobile mode and obtains a user dynamic mobile training model for predicting the user's future location and path. The trained user dynamic mobile model is tested using a model test set to evaluate the prediction accuracy of the model and optimize the model parameters. The optimized user dynamic mobile prediction model is generated through the model test results. Use the user dynamic movement prediction model to predict the user's movement path and generate dynamic user movement prediction data, including future movement locations and path trends. Combine the dynamic user movement prediction data with the static obstacle distribution data to update the initial book collection path planning data. Use the shortest path algorithm to perform obstacle avoidance calculations to ensure that the path bypasses static obstacles and meets the user's dynamic movement prediction, and generate optimized book collection path data, including path points, path length, obstacle avoidance information, and estimated time.

[0135] In this specification, a smart book positioning and sorting system based on virtual reality enhancement technology is provided, which is used to execute the above-mentioned smart book positioning and sorting method based on virtual reality enhancement technology. The smart book positioning and sorting system based on virtual reality enhancement technology includes:

[0136] A virtual reality environment construction module is used to obtain environment scanning data and environment perception images; perform internal space contour feature recognition on the environment scanning data to obtain the internal geometric contour feature data of the library; perform library geometric contour feature recognition on the environment perception image to obtain the internal geometric contour feature data of the library; construct a library virtual reality environment through the library internal space structure data and the library internal geometric contour feature data to generate a virtual three-dimensional library;

[0137] The virtual book generation module is used to obtain library book data, including library book text type data and library book image type data; classify the book types according to the library book text type data to generate the library book type data; extract the cover image features of the library book image type data based on the library book type data to obtain the book cover image feature data; import the book cover text information data and the book cover image feature data into the virtual three-dimensional library to generate a virtual reality enhanced interface to obtain the virtual reality enhanced interface data;

[0138] The book tag module is used to deploy UWB signal base stations using a virtual three-dimensional library; based on the UWB signal base station, UWB tags are added to books according to the virtual reality enhanced interface data to generate book tag data; nodes are connected through the UWB signal base station and the book tag data to generate a UWB book positioning network; the virtual reality enhanced interface data is dynamically updated according to the UWB book positioning network to generate real-time book location data;

[0139] The path planning module is used to obtain the user's current location information data; calculate the shortest obstacle-avoiding book-picking path based on the real-time book location data and the virtual three-dimensional library, and generate optimized book-picking path data; map the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, and generate a dynamic path display interface; generate robot grasping path navigation instructions based on the dynamic path display interface, and obtain robot path navigation instructions to perform intelligent book positioning and sorting operations.

[0140] The beneficial effect of the present invention is that through environmental scanning data and image recognition technology, the system can build a high-precision virtual three-dimensional library environment, and this high-quality virtual environment can provide users with a realistic virtual reality experience. By processing the text and image data of library books, the system can automatically classify and extract features of books, which makes book management more systematic and improves the operational efficiency of the library. Using UWB signal base stations for book labeling and positioning, the system can update the location of books in real time and generate an accurate book positioning network. This technology supports efficient book search and management, and reduces the time and error of manual positioning. Based on the user's current location and real-time book location data, the system can calculate the shortest obstacle avoidance book retrieval path. This function enables users to find and get the required books faster and more conveniently. The optimized book retrieval path is mapped to the virtual reality enhanced interface, and users can view the book retrieval path in real time in the virtual environment, enhancing the user's interactive experience. By generating robot path navigation instructions, the system can realize intelligent book positioning and sorting operations. This function reduces the need for manual operation and improves the work efficiency and accuracy of the library. Therefore, the present invention improves the accuracy, real-time updating, environmental modeling and operational efficiency of traditional book positioning and sorting by integrating virtual reality enhancement technology, UWB positioning, intelligent path planning and automatic control.

[0141] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0142] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. An intelligent book positioning and sorting method based on virtual reality augmented technology, characterized in that: The following steps are involved: Step S1: Acquire environmental scanning data and environmental perception images; perform internal space contour feature recognition on the environmental scanning data to obtain internal geometric contour feature data of the library; The library geometric contour feature recognition is performed on the environment perception image to obtain the internal geometric contour feature data of the library; the library virtual reality environment is constructed by using the internal spatial structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library; step S1 includes the following steps: Step S11: Obtaining environment scanning data and environment perception images through a laser radar sensor and a depth camera; Step S12: performing image preprocessing on the environment perception image to generate a standard environment perception image, wherein the image preprocessing includes image filtering, image brightness enhancement and image grayscale value transformation; performing multi-view image fusion on the standard environment perception image to generate a multi-view fusion image; Step S13: Performing library internal space structure analysis on the environmental scanning data to generate library internal space structure data; performing library geometric contour feature recognition on the multi-view fusion image to obtain library internal geometric contour feature data; Step S14: constructing a virtual reality environment of the library through the internal spatial structure data of the library and the internal geometric contour feature data of the library to generate a virtual three-dimensional library; Step S14 includes the following steps: Step S141: performing library space corner point analysis based on the library internal space structure data and the library internal geometric contour feature data to generate library space corner point data; Step S142: performing point cloud conversion on the library space corner point data to obtain the library space corner point cloud data; Step S143: performing point-line-surface pattern three-dimensional grid modeling according to the library space corner point cloud data to generate the library three-dimensional grid data; Step S144: texture mapping the library 3D mesh data to generate library 3D texture mapping data; texture mapping the library 3D texture mapping data and the library 3D mesh data to generate a virtual 3D library; Step S2: obtaining library book data, including library book text type data and library book image type data; classifying book types according to the library book text type data to generate library book type data; extracting cover image features of the library book image type data based on the library book type data to obtain book cover image feature data; importing the book cover text information data and the book cover image feature data into a virtual three-dimensional library to generate a virtual reality enhanced interface to obtain virtual reality enhanced interface data; Step S2 includes the following steps: Step S21: obtaining library book data, including library book text type data and library book image type data; Step S22: preprocessing the library book text type data to generate standard library book text type data, wherein the data preprocessing includes data cleaning, data denoising, data missing value filling and data standardization; Step S23: extracting book cover text from the standard library book text type data to obtain book cover text information data; classifying the library book data into book types according to the book cover text information data to generate library book type data; extracting cover image features from the library book image type data based on the library book type data to obtain book cover image feature data; Step S24: importing the book cover text information data and the book cover image feature data into the virtual three-dimensional library to generate a virtual reality enhanced interface, thereby obtaining virtual reality enhanced interface data; Step S24 includes the following steps: Step S241: parsing the book cover text information data for book key text information to obtain book cover key information data, wherein the book cover key information data includes the book title, author and ISBN; Step S242: extracting key points and descriptors from the book image feature data to obtain book image key points and book image descriptors; performing principal component analysis based on the book image key points and book image descriptors to generate a book image feature vector; Step S243: importing the book title, author and ISBN into the database in the virtual three-dimensional library to perform field query to obtain preliminary text matching data; importing the book image feature vector into the virtual three-dimensional library to perform image similarity calculation to obtain book image feature similarity data; Step S244: performing comprehensive book matching analysis based on the preliminary text matching data and the book image feature similarity data to generate comprehensive book matching data; using the comprehensive book matching data to screen candidate matching books for the virtual three-dimensional library to generate candidate matching book data; Step S245: mapping the virtual scene position of the virtual three-dimensional library based on the candidate matching book data to generate book positioning data; performing book scene modeling on the candidate matching book data through the book positioning data to generate virtual scene book model data; integrating the virtual three-dimensional library with a virtual reality enhanced interface through the virtual scene book model data to obtain virtual reality enhanced interface data; Step S3: Deploy UWB signal base stations using the virtual three-dimensional library; attach UWB tags to books based on the UWB signal base stations according to the virtual reality enhanced interface data to generate book tag data; connect nodes through the UWB signal base stations and the book tag data to generate a UWB book positioning network; dynamically update the virtual reality enhanced interface data based on the UWB book positioning network to generate real-time book location data; Step S4: obtaining the user's current location information data; calculating the shortest obstacle-avoiding book-picking path based on the real-time book location data and the virtual three-dimensional library, and generating optimized book-picking path data; mapping the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, and generating a dynamic path display interface; generating robot grasping path navigation instructions according to the dynamic path display interface, and obtaining robot path navigation instructions to perform intelligent book positioning and sorting operations.

2. The intelligent book positioning and sorting method based on virtual reality augmented technology according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: deploying UWB signal base stations using a virtual three-dimensional library; Step S32: Based on the UWB signal base station, a UWB tag is added to the book according to the virtual reality enhanced interface data to generate book tag data; Step S33: performing virtual edge computing node site selection for the virtual three-dimensional library through a preset edge computing node range to generate edge node site selection data; performing edge computing node configuration for the book tag data according to the edge node site selection data to generate edge computing node configuration data; performing node connection between the edge computing node configuration data and the UWB signal base station to generate a UWB book positioning network; Step S34: dynamically updating the book position of the virtual reality enhanced interface data according to the UWB book positioning network to generate real-time book position data.

3. The intelligent book positioning and sorting method based on virtual reality augmented technology according to claim 2 is characterized in that: Step S34 includes the following steps: Step S341: Based on the UWB signal base station, the pulse arrival time of the UWB book positioning network and the book tag data is measured to generate preliminary distance data; Step S342: Calculate the book arrival time difference on the preliminary distance data by using the arrival time difference algorithm to generate the book arrival time difference position data; perform Kalman filter data fusion on the book arrival time difference position data to generate the book optimized position data; Step S343: The optimized book location data is transmitted and stored in the central local area network to generate book location storage data; the edge computing node is used to obtain the real-time location calculation result of the book location storage data to generate book location update data; Step S344: dynamically refreshing the virtual reality augmented interface data based on the book position using the book position update data, thereby generating real-time book position data.

4. The intelligent book positioning and sorting method based on virtual reality augmented technology according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: obtaining the user's current location information data; planning the book retrieval path based on the real-time book location data and the virtual three-dimensional library, and generating initial book retrieval path planning data; Step S42: Calculate the shortest obstacle-avoiding book-picking path for the initial book-picking path planning data according to the user's current location information data, and generate optimized book-picking path data; Step S43: Mapping the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, generating a dynamic path display interface; generating robot grabbing path navigation instructions according to the dynamic path display interface, obtaining robot path navigation instructions, and executing intelligent book positioning and sorting operations.

5. The intelligent book positioning and sorting method based on virtual reality augmented technology according to claim 4 is characterized in that: Step S42 includes the following steps: Step S421: performing static obstacle recognition on the multi-view fusion image to generate static obstacle distribution data; Step S422: performing time series position analysis on the user's current location information data to generate user movement path data; Step S423: Divide the user movement path data into data sets to generate a model training set and a model test set; perform model training on the model training set using a random forest algorithm to generate a user dynamic movement training model; perform model testing on the user dynamic movement training model using a model test set to generate a user dynamic movement prediction model; Step S424: Use the user dynamic movement prediction model to predict the user movement path data and generate dynamic user movement prediction data; calculate the shortest obstacle avoidance book picking path for the initial book picking path planning data based on the dynamic user movement prediction data and the static obstacle distribution data to generate optimized book picking path data.

6. An intelligent book positioning and sorting system based on virtual reality augmented technology, characterized in that: Used to execute the intelligent book positioning and sorting method based on virtual reality enhancement technology as claimed in claim 1, the intelligent book positioning and sorting system based on virtual reality enhancement technology comprises: A virtual reality environment construction module is used to obtain environment scanning data and environment perception images; perform internal space contour feature recognition on the environment scanning data to obtain the internal geometric contour feature data of the library; perform library geometric contour feature recognition on the environment perception image to obtain the internal geometric contour feature data of the library; construct a library virtual reality environment through the library internal space structure data and the library internal geometric contour feature data to generate a virtual three-dimensional library; The virtual book generation module is used to obtain library book data, including library book text type data and library book image type data; classify the book types according to the library book text type data to generate the library book type data; extract the cover image features of the library book image type data based on the library book type data to obtain the book cover image feature data; import the book cover text information data and the book cover image feature data into the virtual three-dimensional library to generate a virtual reality enhanced interface to obtain the virtual reality enhanced interface data; The book tag module is used to deploy UWB signal base stations using a virtual three-dimensional library; based on the UWB signal base station, UWB tags are added to books according to the virtual reality enhanced interface data to generate book tag data; nodes are connected through the UWB signal base station and the book tag data to generate a UWB book positioning network; the virtual reality enhanced interface data is dynamically updated according to the UWB book positioning network to generate real-time book location data; The path planning module is used to obtain the user's current location information data; calculate the shortest obstacle-avoiding book-picking path based on the real-time book location data and the virtual three-dimensional library, and generate optimized book-picking path data; map the optimized book-picking path data to the virtual reality enhanced interface data for dynamic path display, and generate a dynamic path display interface; generate robot grasping path navigation instructions based on the dynamic path display interface, and obtain robot path navigation instructions to perform intelligent book positioning and sorting operations.

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