AI digital human mobile navigation method and system based on transparent display screen

Abstract

The invention relates to an AI digital human mobile navigation method based on a transparent display screen. The method comprises the following steps: starting a system to carry out hardware and software self-inspection; the camera identifies a user identity and performs user login according to the user identity; the transparent display screen generates a digital person according to the AI large model, and performs adjustment on the digital person according to the input information and the interaction situation of the target user; the sensor obtains current environment information, obtains initial position information of the navigation equipment, analyzes surrounding environment information, converts the surrounding environment information into laser information and generates a mobile navigation map. According to the invention, through cooperation of all the modules, digital content and visual perception of the real world are perfectly fused through the transparent display screen, a visual and immersive interaction space is created, and a user can directly perform visual interaction with a digital person to obtain smooth and vivid user experience.

Description

Technical Field

[0001] The present invention belongs to the technical field of interactive navigation, and in particular relates to an AI digital human mobile navigation method and system based on a transparent display screen. Background Art

[0002] Mobile guide system has always been an important auxiliary tool for tourists and visitors when exploring various places such as museums, exhibition halls, theme parks, etc. This system mainly relies on two core functions: voice explanation and map navigation. The voice explanation provides tourists with detailed introductions about exhibits or attractions through pre-recorded audio information, while the map navigation helps tourists quickly locate their position in a vast area and plan the best route to their destination.

[0003] However, the above-mentioned traditional mobile guide systems often adopt a "one-size-fits-all" explanation method and are unable to provide customized information based on individual differences of tourists such as age, interests, and knowledge level. The interaction between tourists and the system is also limited to simple query and navigation operations, lacking a deeper interactive experience. This one-way information transmission mode greatly limits tourists' sense of participation and immersion.

[0004] Nowadays, with the rapid development and popularization of artificial intelligence (AI) technology, AI digital humans, as highly intelligent virtual images, can simulate real human expressions, movements and voices, and achieve natural dialogue and interaction with users; the interaction between AI digital humans and transparent displays has gradually become a new technological trend and a hot spot for user experience.

[0005] Therefore, a method and system for mobile tour guide using AI digital humans based on a transparent display screen is designed, which can not only realize the intelligent upgrade of voice explanation and map navigation, such as analyzing tourists' preferences and behavior patterns through AI algorithms to provide personalized explanation content and route planning; it can also use the interactive capabilities of AI digital humans to realize interactive functions such as real-time question and answer, virtual tour guide, situational simulation, etc. with tourists, thereby greatly improving tourists' participation and experience. Summary of the invention

[0006] The purpose of the present invention is to provide an AI digital human mobile navigation method and system based on a transparent display screen to solve the problems raised in the above background technology.

[0007] To achieve the above-mentioned purpose, the first aspect of the present invention provides an AI digital human mobile navigation method based on a transparent display screen, comprising:

[0008] S01 starts the system to perform hardware and software self-test;

[0009] S02 The camera identifies the user identity and logs in the user according to the user identity;

[0010] S03 transparent display screen generates digital human based on AI big model and makes execution adjustments to the digital human based on input information and interaction scenario of target user;

[0011] S04 sensor acquires current surrounding environment information, obtains initial position information of the navigation device, analyzes the surrounding environment information, converts the surrounding environment information into laser information, and generates a mobile navigation map;

[0012] S05 starts the guide device;

[0013] S06: The digital human interacts with the user through the transparent display screen, obtains user feedback using the language model, the system analyzes the user feedback to obtain target location information, and the navigation device moves to the target location.

[0014] Preferably, the camera identifies the user identity and performs user login based on the user identity, mainly relying on facial recognition and contactless radio frequency identification functions.

[0015] Preferably, the transparent display screen generates a digital human according to the AI ​​big model, and performs execution adjustments on the digital human according to the input information and interaction context of the target user, including:

[0016] The AI ​​big model accurately customizes the appearance features and behavior patterns of the digital human based on the user's input information;

[0017] Among them, the appearance features of digital humans include facial contours, hairstyle color and clothing style, and the behavioral patterns of digital humans include walking posture, communication methods and interactive reactions.

[0018] Preferably, the sensor acquires current surrounding environment information, obtains initial position information of the navigation device, analyzes the surrounding environment information, converts the surrounding environment information into laser information, and generates a mobile navigation map, including:

[0019] The S401 depth camera obtains depth images and RGB images of the surrounding environment;

[0020] S402 converts the depth information in the depth image into laser information to create a two-dimensional occupancy grid map;

[0021] S403, during the navigation process of the mobile navigation device, continuously acquiring new depth images and updating the grid state of the two-dimensional occupancy grid map in real time to reflect environmental changes;

[0022] S404 performs target detection on the RGB image acquired by the depth camera using a target detection network to generate an object information list including object names and pixel position information;

[0023] S405 integrates the generated two-dimensional occupancy grid map and the object position information marked thereon to form a mobile navigation map.

[0024] Preferably, the digital human interacts with the user through the transparent display screen, obtains user feedback using a language model, the system analyzes the user feedback to obtain target location information, and the navigation device moves to the target location, including:

[0025] Extracting the user's target location information;

[0026] The system dynamically forms a multi-path selection strategy based on current environmental data and provides the optimal movement path;

[0027] Obtain the user's desired movement path and start the mobile navigation device.

[0028] Preferably, the step of obtaining the user's desired moving path and activating the mobile navigation device further includes:

[0029] During the navigation process of the mobile guide device, a real-time obstacle avoidance algorithm is integrated to update the mobile guide map and generate a moving path in real time.

[0030] Preferably, it also includes:

[0031] Analyze the user's historical behavior and preferences based on the user's target location information and historical search information, and provide personalized recommendations through the transparent display screen;

[0032] According to the relevant information retrieved by the user, multimedia information display is provided through the transparent display screen and sound system;

[0033] Among them, relevant information includes exhibit information, historical background, etc.

[0034] Preferably, it also includes:

[0035] After the tour, user feedback is collected through the transparent display screen, user feedback and interaction data are analyzed, and the interaction algorithm and content recommendation mechanism are optimized.

[0036] The second aspect of the present invention provides an AI digital human mobile navigation system based on a transparent display screen, comprising the following modules:

[0037] Self-check module, used for system startup and hardware and software self-check to ensure that all modules are operating normally;

[0038] Identification module, which identifies the user or logs in the user through a camera or near-field communication device;

[0039] The environmental perception module uses sensors such as cameras and lidar to obtain current environmental information, perform environmental analysis, generate maps, and identify paths, obstacles, and key areas;

[0040] The AI ​​digital human generation module uses the AI ​​large model to generate a digital human image for display on a transparent display screen, and adjusts the digital human's facial expressions and body movements;

[0041] The fusion module is used to build, update and maintain the environment map in real time after integrating the interaction with the user, focusing on accuracy and details;

[0042] The interactive module realizes the recognition of user voice commands and the voice response of the digital human, and supports gesture and touch input;

[0043] Path planning module, which dynamically generates movement paths based on environmental data to avoid obstacles and ensure safety;

[0044] The navigation execution module controls the mobile chassis to move along the planned path to maintain stability and safety;

[0045] The navigation information module retrieves relevant information based on the user's location and interests, and provides multimedia information display through a transparent display screen and sound system;

[0046] The optimization module is used to collect user feedback, evaluate satisfaction and experience, and continuously optimize the interaction algorithm and content recommendation mechanism based on user feedback and interaction data.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] Through the collaborative cooperation of various modules, the present invention perfectly integrates digital content with the visual perception of the real world through a transparent display screen, creating an intuitive and immersive interactive space where users can directly interact visually with the digital human and obtain a smooth and vivid user experience;

[0049] The present invention ensures that all modules are in the best working state through hardware and software self-checking of the self-checking module when the system is started, improves the reliability and stability of the entire system, provides users with a seamless and uninterrupted navigation experience, and reduces the inconvenience caused by system failures;

[0050] The present invention recognizes the user's identity through the identification module, completes the user login on the transparent display screen, and combines the AI ​​digital human generation module and the guide information module. The system can provide personalized guide content and recommendations based on the user's personal preferences and historical behaviors. At the same time, the facial expressions and body movements of the AI ​​digital human are adjusted to make the interaction more natural and friendly, enhancing the user's immersion and satisfaction.

[0051] The present invention obtains current environmental information through sensors in the environmental perception module, generates an accurate environmental map, and updates and maintains it in real time. Combined with the moving path dynamically generated by the path planning module based on environmental data, it can achieve effective obstacle avoidance, ensure that the AI ​​digital human can move to the designated location safely and efficiently, and provide a more accurate, safe and comfortable navigation environment.

[0052] The interactive module in the present invention supports multiple interactive modes such as voice command recognition, digital human voice response, gesture and touch input, etc. Users can choose the interactive mode according to their preferences and habits, thereby improving the flexibility and fun of the guided tour process;

[0053] The present invention collects user feedback and interaction data through an optimization module, and continuously evaluates the system's satisfaction and experience. Based on these data, the system can continuously optimize the interaction algorithm and content recommendation mechanism, thereby continuously adapting to user needs and changes, and improving the accuracy and personalization of navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of an AI digital human mobile navigation method based on a transparent display screen in an embodiment of the present invention;

[0055] Figure 2 The structure block diagram of an AI digital human mobile guide system based on a transparent display screen in an embodiment of the present invention.

[0056] Numbers in the figure: 701-self-check module, 702-recognition module, 703-environmental perception module, 704-AI digital human generation module, 705-fusion module, 706-interaction module, 707-path planning module, 708-navigation execution module, 709-guide information module, 710-optimization module. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Embodiment 1

[0059] like Figure 1 The AI ​​digital human mobile navigation method based on a transparent display screen is shown, and the steps are as follows:

[0060] S01 starts the system to perform hardware and software self-test;

[0061] The S02 camera identifies the user's identity and logs in the user based on the user's identity;

[0062] The S03 transparent display screen generates a digital human based on the AI ​​big model and makes execution adjustments to the digital human based on the input information and interaction scenarios of the target user;

[0063] The S04 sensor acquires the current environment information, obtains the initial position information of the navigation device, analyzes the surrounding environment information, converts the surrounding environment information into laser information, and generates a mobile navigation map;

[0064] S05 starts the guide device;

[0065] S06 The digital human interacts with the user through the transparent display screen and obtains user feedback using the language model. The system analyzes the user feedback to obtain target location information, and the navigation device moves to the target location.

[0066] In one embodiment, the above step S01: starting the system to perform hardware and software self-tests; specifically includes:

[0067] During the system startup phase, the self-check module 701 is usually used to perform self-checks on the hardware and software in each module. The software includes the integrity and version verification of the operating system, driver, application, etc., to ensure the stability and security of the software environment; while the hardware self-check is designed to check the status of key hardware components such as the processor, memory, storage device, input and output interface, to ensure that they are working properly and support the stable movement of the guide device.

[0068] In one embodiment, the above step S02: the camera identifies the user identity and logs in the user according to the user identity; specifically includes:

[0069] The camera identifies the user's identity and logs in the user based on the user's identity, mainly relying on facial recognition and contactless radio frequency identification functions.

[0070] The guide device in the embodiment of the present invention is equipped with an identification module 702 for identifying the user's identity or logging in the user. The user can be a tourist or a staff member. The identification module is specifically a camera or a near-field communication device. The camera in the identification module uses computer vision technology to capture the user's facial features, and compares the facial information of the user stored in the database through a facial recognition algorithm to identify the user's identity. Near-field communication devices (NFC for short) are short-range high-frequency wireless communication technologies, mainly based on the integration of contactless radio frequency identification (RFID) and interconnection technology, using mobile terminals to achieve point-to-point communication applications, and sharing user information (photos, videos, contacts, etc.) to confirm the user's identity. Among them, when entering the guide device, the staff needs to complete the dual authentication of the identity card and the face; and considering that when the user logs in after passing the facial recognition, it may involve biometric technology such as fingerprint or iris scanning and other highly secure information, so after identifying a non-staff member, two options will be given on the transparent display screen as follows:

[0071] 1. After facial recognition is passed, the transparent display screen displays "Identity Confirmation" and displays the security protocol for user login;

[0072] 2. Touch the mobile device with NFC to share information with it. The transparent display will show part of the user's identity information. After confirmation, log in.

[0073] In one embodiment, the above step S03, the transparent display screen generates a digital human according to the AI ​​big model, and performs execution adjustments on the digital human according to the input information and interaction context of the target user; specifically, it includes:

[0074] The AI ​​big model accurately customizes the appearance features and behavior patterns of the digital human based on the user's input information; among them, the appearance features include facial contours, hairstyle color and clothing style; the behavior patterns include walking posture, communication methods and interactive reactions.

[0075] Transparent display technology allows images to be displayed while maintaining the perspective of the background, providing a more intuitive and natural human-computer interaction. The AI ​​big model can generate the image and behavior of the digital human after deep learning. The deep learning network can be any training architecture such as the Transformer architecture. The Transformer architecture has powerful multimodal data processing capabilities and can simultaneously process multiple types of data such as text, images, and audio. Through the Transformer architecture and a large amount of parameters and data training, the AI ​​big model can convert the user's input into an accurate description of the digital human image, and accurately adjust the digital human's facial contours, hairstyle details, clothing accessories, etc., thereby generating a highly personalized virtual image.

[0076] The AI ​​large model based on the Transformer architecture can learn and understand users' commands, emotions, and interactive situations, and use natural language processing to generate logical and creative interactive responses. This enables digital humans to make appropriate responses and actions in different scenarios based on users' actual needs and behaviors, enhancing their intelligence and interactivity.

[0077] In one embodiment, the above step S04, the sensor acquires the current environment information, obtains the initial position information of the navigation device, analyzes the surrounding environment information, converts the surrounding environment information into laser information, and generates a mobile navigation map; specifically includes:

[0078] The S401 depth camera obtains depth images and RGB images of the surrounding environment;

[0079] S402 converts the depth information in the depth image into laser information to create a two-dimensional occupancy grid map;

[0080] S403, during the navigation process of the mobile navigation device, continuously acquiring new depth images and updating the grid state of the two-dimensional occupancy grid map in real time to reflect environmental changes;

[0081] S404 performs target detection on the RGB image acquired by the depth camera using a target detection network to generate an object information list including object names and pixel position information;

[0082] S405 integrates the generated two-dimensional occupancy grid map and the object position information marked thereon to form a mobile navigation map.

[0083] Among them, the sensor is specifically a depth camera, which can capture ordinary RGB color images of the surrounding environment, providing rich color and texture information, and helping to identify specific objects in the environment, such as trees, grass, doors and windows, etc.; at the same time, the depth camera can also generate a depth image containing the distance information of each pixel through its special ranging principle, obtain depth information (that is, the three-dimensional shape and position relationship of the object), and provide basic data for subsequent map construction.

[0084] After being processed by the algorithm, the above depth information is converted into point cloud data similar to that scanned by LiDAR. These point cloud data are used to create a two-dimensional occupancy grid map. This map can divide the surrounding environment into a series of small grids (grids) and mark the map according to whether the grid is occupied by an object. The state of each grid (free, occupied or unknown) is determined according to the density and distribution of the point cloud data, thereby constructing a two-dimensional map reflecting the actual environment layout. Then the RGB image obtained by the depth camera is sent to the pre-trained target detection network, and a list containing the object name and its pixel position information in the image is generated for the objects in the image, such as trees, grass, doors and windows. Finally, the generated two-dimensional occupancy grid map is combined with the object position information obtained through target detection to form a mobile navigation map that contains both spatial layout and specific object information. On this map, different object information will be mapped to the corresponding grid of the grid map, or the object position and name will be directly displayed on the map through annotation, helping users to understand the surrounding environment more intuitively.

[0085] Furthermore, based on the generation of the above-mentioned two-dimensional occupancy grid map, in the subsequent navigation of the guide device, very specific guide clues such as "turn left and go straight to the third door" can be provided to help users understand the environmental content more quickly and enhance the guide experience.

[0086] Moreover, in the acquisition, analysis and generation of guide maps of the surrounding environment, a combination of LiDAR or INS and GPS can also be used. LiDAR mainly measures the distance by emitting laser beams and measuring the reflection time to generate high-precision point cloud data. These data can be directly used to create three-dimensional maps and can also provide rich environmental information when further converted into two-dimensional maps. The combination of INS and GPS can provide precise location information of the guide equipment and, combined with visual or laser sensor data, build an environmental map with more details.

[0087] In one embodiment, the above step S05 of starting the navigation device specifically includes:

[0088] In step S04, the depth camera can generate a depth image containing the distance information of each pixel after shooting, and obtain the depth information (ie, the three-dimensional shape and position relationship of the object).

[0089] After being processed by an algorithm, the depth information is converted into point cloud data similar to lidar scanning. These point cloud data are used to create a two-dimensional occupancy grid map. After eliminating the point cloud data of the surrounding environment, the initial position of the mobile guide device can be located. In addition, the mobile guide device can also determine its precise position on the map again based on the installed GPS positioning technology, and combine GIS (geographic information system) technology to manage and analyze geographic data to provide support for navigation.

[0090] In one embodiment, the above step S06, in which the digital human interacts with the user through the transparent display screen, obtains user feedback using the language model, the system analyzes the user feedback to obtain target location information, and the navigation device moves to the target location, specifically includes:

[0091] Extracting the user's target location information;

[0092] The system dynamically forms a multi-path selection strategy based on current environmental data and provides the optimal movement path;

[0093] Obtain the user's desired movement path and start the mobile navigation device.

[0094] First, the mobile guide device is in an indoor or outdoor environment with a pre-given surrounding environment map, such as in an exhibition venue. The digital human interacts with the user through a transparent display screen, and can obtain user feedback through direct touch or by using a language model. The user can issue voice commands, such as "Please move to the first exhibition hall" or "Please move to the ** booth". The digital human uses a large language model to parse the commands and obtain the navigation target location: the first exhibition hall. The user can also interact with the digital human through gestures, and the transparent display screen interactively identifies and tracks the user, obtains the user's motion data, and extracts and analyzes user feedback.

[0095] To further illustrate the feasibility of this embodiment, reference may also be made to the intelligent mobile AI digital human interaction method and system based on a transparent display device in announcement number CN117908683A, in which the voice signal of the target user is collected through the audio sensor in the transparent display device to obtain a voice signal, and the voice signal is subjected to short-time Fourier transform to obtain voice data; feature extraction is performed on the voice data to obtain a voice feature set, user intent analysis is performed on the voice feature set through a natural language processing model to obtain user intent information, and digital human adaptive dialogue response analysis is performed through the user intent information to generate digital human dialogue response parameters, etc.; finally, a multi-dimensional digital human execution strategy adjustment is performed on the digital human to obtain adjustments including but not limited to voice response execution strategy and action response execution strategy.

[0096] Then the digital human extracts the target location information required for navigation, such as "the first exhibition hall", and after obtaining the initial location of the mobile guide device, dynamically forms a multi-path selection strategy based on the current environmental data and provides the optimal movement path. Among them, the multi-path selection strategy will refer to the following factors, including but not limited to:

[0097] The depth camera perceives the distribution of obstacles in the environment in real time, such as walls, pillars, exhibits, etc., to ensure that the planned path will not collide with these obstacles;

[0098] The depth camera senses the density of people in the environment in real time, and the digital human will try to choose a path that avoids peak traffic to improve the user's navigation efficiency;

[0099] Based on the above factors, the digital human calculates the length of each path through a path planning algorithm, giving priority to the path with the shortest distance and lowest time cost.

[0100] It should be noted that the digital human displays at least three different paths through a transparent display screen. All three paths are connected between the initial position and the target position of the mobile guide device. At the same time, the digital human will mark the "optimal moving path" for the user's reference and selection. The final moving path of the mobile guide device will execute navigation based on the user's choice.

[0101] During the navigation process of the mobile guide device, the depth camera continuously captures new depth images, which are processed in real time and used to update the occupied grid map. Whenever the device moves or the surrounding environment changes, the grid status on the map will be adjusted accordingly to ensure that the map always reflects the latest environmental conditions, achieving the effect of real-time obstacle avoidance and planning the optimal path.

[0102] In one embodiment, it further includes:

[0103] Analyze the user's historical behavior and preferences based on the user's target location information and historical search information, and provide personalized recommendations through the transparent display screen;

[0104] According to the relevant information retrieved by the user, multimedia information display is provided through the transparent display screen and the sound system; specifically including:

[0105] In the interaction between the digital human, the transparent display screen and the user, the system will actively perform intelligent analysis on the user's input data, accurately capture the user's potential interests, and push relevant information. For example, during navigation, the user frequently searches for exhibition information about the "Second Exhibition Hall" of a specific historical period. The system identifies the user's interest and displays personalized recommended content closely related to the historical period through the transparent display screen when the user approaches the second exhibition hall, such as special exhibit introductions, in-depth interpretation articles or related event announcements. The user can click to view or interrupt the original navigation and add the "Second Exhibition Hall" to the planned path. The digital human will calculate again and calculate the optimal path that includes the second exhibition hall and the first exhibition hall, and perform navigation based on the user's choice.

[0106] Among them, relevant information includes exhibit information, historical background, creation story, artist's life and connection with other cultural elements. The transparent display screen works together with the sound system to present the above information through the transparent display screen in the form of pictures, texts and dynamic demonstrations. At the same time, the speakers play background music related to the exhibits, sound effects of historical scenes or narration of professional commentators, allowing users to achieve dual visual and auditory enjoyment.

[0107] In one embodiment, it further includes:

[0108] After the tour, user feedback is collected through the transparent display screen, and user feedback and interaction data are analyzed to optimize the interaction algorithm and content recommendation mechanism.

[0109] After the tour, this embodiment uses the two-way interactive characteristics of the transparent display screen to design a user feedback collection interface, which incorporates more interactive elements, such as a slider on the touch screen, star rating, emoticon selection, or a short text comment input box, allowing users to easily express their satisfaction, opinions, and suggestions. Through the intuitive display and instant feedback mechanism of the transparent display screen, users are encouraged to share their feelings immediately after the tour, ensuring that the collected feedback data is closer to the user's immediate experience and reducing the memory bias caused by the time interval.

[0110] The user feedback data collected includes but is not limited to the interest in the guided tour content, the clarity of information, the effect of multimedia display, the friendliness of the interactive interface, and the evaluation of the overall experience. The feedback data is combined with the user's interactive behavior data during the mobile guided tour, and the individual data is analyzed to continuously optimize the interactive algorithm, including but not limited to: adjusting the user interface design to make it more in line with the user's behavioral habits and aesthetic preferences; optimizing the content recommendation mechanism, analyzing the user's feedback and interaction patterns through machine learning algorithms, and automatically adjusting the order and type of recommended content; adjusting the presentation of multimedia content, such as adjusting the audio volume and speech speed, optimizing the video resolution and playback smoothness, etc.; and ultimately building an intelligent guided tour system that can continuously learn and adapt to the needs of different individual users.

[0111] Embodiment 2

[0112] like Figure 2 As shown, this embodiment provides an AI digital human mobile navigation system based on a transparent display screen, including the following modules:

[0113] Self-check module 701, used for system startup and hardware and software self-check to ensure that all modules are operating normally;

[0114] Identification module 702, identifying the user identity or performing user login through a camera or near field communication device;

[0115] The environment perception module 703 uses sensors such as cameras and lidar to obtain current environment information, perform environmental analysis, generate maps, and identify paths, obstacles, and key areas;

[0116] The AI ​​digital human generation module 704 generates a digital human image using the AI ​​large model and displays it on the transparent display screen, and adjusts the digital human's facial expressions and body movements;

[0117] Fusion module 705, for real-time map construction, updating and maintaining the environment map after fusing the interaction with the user, focusing on accuracy and details;

[0118] Interaction module 706, which realizes the recognition of user voice commands and the voice response of the digital human, and supports gesture and touch input;

[0119] Path planning module 707, dynamically generates a moving path based on environmental data to avoid obstacles and ensure safety;

[0120] The navigation execution module 708 controls the mobile chassis to move along the planned path to maintain stability and safety;

[0121] The navigation information module 709 retrieves relevant information according to the user's location and interests, and provides multimedia information display through the transparent display screen and sound system;

[0122] The optimization module 710 is used to collect user feedback, evaluate satisfaction and experience, and continuously optimize the interaction algorithm and content recommendation mechanism based on user feedback and interaction data.

[0123] Through the cooperation of various modules, the digital content and the visual perception of the real world are perfectly integrated through the transparent display screen to create an intuitive and immersive interactive space. Users can directly interact with the digital human visually and get a smooth and vivid user experience. Through the hardware and software self-check of the self-check module 701 at the start of the system, it is ensured that all modules are in the best working state, the reliability and stability of the entire system are improved, and a seamless and uninterrupted navigation experience is provided to users, reducing the inconvenience caused by system failures. Through the recognition of the user's identity by the identification module 702, the user login is completed on the transparent display screen. Combined with the AI ​​digital human generation module and the navigation information module, the system can provide personalized navigation content and recommendations based on the user's personal preferences and historical behaviors. At the same time, the facial expressions and body movements of the AI ​​digital human are adjusted to make the interaction more natural and friendly, enhancing the user's immersion and Satisfaction; the current environmental information is obtained through the sensors in the environmental perception module 703, an accurate environmental map is generated, and it is updated and maintained in real time. Combined with the moving path dynamically generated by the path planning module 707 based on the environmental data, effective obstacle avoidance can be achieved, ensuring that the AI ​​digital human can move to the designated location safely and efficiently, providing a more accurate, safe and comfortable navigation environment; the interactive module 706 in the present invention supports multiple interaction methods such as voice command recognition, digital human voice response, gesture and touch input, and users can choose the interaction method according to their preferences and habits to improve the flexibility and fun of the navigation process; through the optimization module 710, user feedback and interaction data are collected to continuously evaluate the system's satisfaction and experience. Based on these data, the system can continuously optimize the interaction algorithm and content recommendation mechanism, and then continuously adapt to user needs and changes, and improve the accuracy and personalization of the navigation.

[0124] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0125] The above description is only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in this field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. An AI digital human mobile navigation method based on a transparent display screen, characterized in that: include: S01 starts the system to perform hardware and software self-test; S02 The camera identifies the user identity and logs in the user according to the user identity; S03 transparent display screen generates digital human based on AI big model and makes execution adjustments to the digital human based on input information and interaction scenario of target user; S04 sensor acquires current surrounding environment information, obtains initial position information of the navigation device, analyzes the surrounding environment information, converts the surrounding environment information into laser information, and generates a mobile navigation map; S05 starts the guide device; S06: The digital human interacts with the user through the transparent display screen, obtains user feedback using the language model, the system analyzes the user feedback to obtain target location information, and the navigation device moves to the target location.

2. The method for mobile navigation using AI digital human based on a transparent display screen according to claim 1, characterized in that: The camera identifies the user's identity and logs in the user based on the user's identity, mainly relying on facial recognition and contactless radio frequency identification functions.

3. The method for mobile navigation using AI digital human based on a transparent display screen according to claim 1, characterized in that: The transparent display screen generates a digital human according to the AI ​​big model, and performs execution adjustments on the digital human according to the input information and interaction scenario of the target user, including: The AI ​​big model accurately customizes the appearance features and behavior patterns of the digital human based on the user's input information; Among them, the appearance features of digital humans include facial contours, hairstyle color and clothing style, and the behavioral patterns of digital humans include walking posture, communication methods and interactive reactions.

4. The method for mobile navigation using AI digital human based on a transparent display screen according to claim 1, characterized in that: The sensor acquires current surrounding environment information, obtains initial position information of the navigation device, analyzes the surrounding environment information, converts the surrounding environment information into laser information, and generates a mobile navigation map, including: The S401 depth camera obtains depth images and RGB images of the surrounding environment; S402 converts the depth information in the depth image into laser information to create a two-dimensional occupancy grid map; S403, during the navigation process of the mobile navigation device, continuously acquiring new depth images and updating the grid state of the two-dimensional occupancy grid map in real time to reflect environmental changes; S404 performs target detection on the RGB image acquired by the depth camera using a target detection network to generate an object information list including object names and pixel position information; S405 integrates the generated two-dimensional occupancy grid map and the object position information marked thereon to form a mobile navigation map.

5. The method for mobile navigation using AI digital human based on transparent display screen according to claim 1, characterized in that: The digital human interacts with the user through the transparent display screen, obtains user feedback using the language model, the system analyzes the user feedback to obtain target location information, and the navigation device moves to the target location, including: Extracting the user's target location information; The system dynamically forms a multi-path selection strategy based on current environmental data and provides the optimal movement path; Obtain the user's desired movement path and start the mobile navigation device.

6. The method for mobile navigation using AI digital human based on transparent display screen according to claim 5, characterized in that: The step of obtaining the moving path required by the user and starting the mobile navigation device further includes: During the navigation process of the mobile guide device, a real-time obstacle avoidance algorithm is integrated to update the mobile guide map and generate a moving path in real time.

7. The method for mobile navigation using AI digital human based on transparent display screen according to claim 1, characterized in that: Also included are: Analyze the user's historical behavior and preferences based on the user's target location information and historical search information, and provide personalized recommendations through the transparent display screen; According to the relevant information retrieved by the user, multimedia information display is provided through the transparent display screen and sound system; Among them, relevant information includes exhibit information, historical background, etc.

8. The method for mobile navigation using AI digital human based on a transparent display screen according to claim 1, characterized in that: Also includes: After the tour, user feedback is collected through the transparent display screen, user feedback and interaction data are analyzed, and the interaction algorithm and content recommendation mechanism are optimized.

9. An AI digital human mobile guide system based on a transparent display screen, comprising the following modules: Self-check module, used for system startup and hardware and software self-check to ensure that all modules are operating normally; Identification module, which identifies the user or logs in the user through a camera or near-field communication device; The environmental perception module uses sensors such as cameras and lidar to obtain current environmental information, perform environmental analysis, generate maps, and identify paths, obstacles, and key areas; The AI ​​digital human generation module uses the AI ​​large model to generate a digital human image for display on a transparent display screen, and adjusts the digital human's facial expressions and body movements; The fusion module is used to build, update and maintain the environment map in real time after integrating the interaction with the user, focusing on accuracy and details; The interactive module realizes the recognition of user voice commands and the voice response of the digital human, and supports gesture and touch input; Path planning module, which dynamically generates movement paths based on environmental data to avoid obstacles and ensure safety; The navigation execution module controls the mobile chassis to move along the planned path to maintain stability and safety; The navigation information module retrieves relevant information based on the user's location and interests, and provides multimedia information display through a transparent display screen and sound system; The optimization module is used to collect user feedback, evaluate satisfaction and experience, and continuously optimize the interaction algorithm and content recommendation mechanism based on user feedback and interaction data.

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