1109 results about "Augmented reality" patented technology

The invention provides a three-dimensional Gaussian digital human generation system and method and electronic equipment, and relates to the technical field of augmented reality, and the system comprises a data obtaining unit which is used for obtaining visual depth data, dynamic behavior data and environmental perception data, and generating point cloud data and multi-modal data according to the visual depth data, the dynamic behavior data and the environmental perception data; the rendering adjustment unit is used for monitoring the fixation area in real time and determining a rendering strategy; according to the real-time computing power parameter, determining a rendering specification; the driving unit is used for performing feature extraction on the multi-modal data to obtain multi-modal features and generating face driving parameters and limb driving parameters of the digital human model; and the modeling unit is used for generating a basic grid of the digital human model according to the point cloud data and the initial digital human model, and performing expression rendering and action rendering on the basic grid according to a rendering strategy and a rendering specification in combination with the face driving parameters and the limb driving parameters to obtain a rendered digital human model. The fluency, authenticity and naturalness of the display effect are improved.

The invention discloses an intelligent coordination control method and system for power plant equipment based on multi-source heterogeneous data, and belongs to the technical field of intelligent manufacturing and industrial automation, and the method comprises the steps: deploying a multi-mode sensor network in the power plant equipment, collecting the multi-source heterogeneous data in real time, and carrying out the real-time data preprocessing through an edge calculation node; carrying out collaborative modeling on the preprocessed data by adopting a hybrid analysis framework, predicting an equipment state trend, identifying a fault propagation path, positioning a root cause and optimizing a maintenance decision scheme; the equipment failure probability is evaluated through a fault diagnosis result, a grading early warning mechanism is triggered, and a rule base is updated and optimized in combination with a dynamic knowledge base; a three-dimensional model is constructed by using a digital twinning technology to carry out virtual simulation and remote control, and maintenance guidance is carried out through an augmented reality auxiliary technology. According to the method, efficient real-time monitoring and fault prediction are achieved, the fault diagnosis time and the operation and maintenance cost are remarkably reduced by combining the fault tree model and the digital twinning technology, and the equipment operation safety and reliability are improved.

The invention relates to a visual safety risk early warning system for pseudo-classic architecture mixed structure construction, in particular to the field of safety risk early warning of pseudo-classic architecture construction, through multi-source data fusion and intelligent algorithm cooperation, the construction safety risk management and control capability is remarkably improved, the system collects mechanical and environmental data of key nodes of a high-support formwork body in real time, and the construction safety risk early warning capability is improved. Load distribution is dynamically updated in combination with the building information model, and a high-precision space-time label data stream is generated; predicting a short-term instability risk based on a two-channel neural network, constructing a complex network model to quantify a node failure linkage effect, and generating a visual risk propagation thermodynamic diagram; finally, a grading alarm strategy is triggered through a dynamic threshold value, augmented reality visual warning and equipment linkage control is achieved, the system breaks through the limitation of traditional manual monitoring, full-process closed-loop management of risk perception, prediction, positioning and response is achieved, the occurrence rate of safety accidents is effectively reduced, and the safety and reliability of construction of the complex structure of the pseudo-classic architecture are guaranteed.

The invention discloses a single-view large-scale outdoor scene three-dimensional reconstruction method based on three-dimensional Gaussian splashing, and the method comprises the steps: collecting a pseudo aerial image, and constructing a panoramic multi-mode supervision end-to-end single-view three-dimensional reconstruction model; meanwhile, panoramic consistency supervision, semantic constraint depth regularization and a radial weighted luminosity loss and Gaussian cutting mechanism are introduced, so that the defect of insufficient geometric constraint of traditional single-view three-dimensional reconstruction is effectively overcome, and high-efficiency and high-fidelity three-dimensional modeling of a large-scale outdoor scene under single image input is realized; the method is suitable for various actual scenes such as smart city construction, automatic driving simulation, virtual reality / augmented reality, digital twinning and the like.

The invention belongs to the technical field of three-dimensional scene modeling, and discloses a dual-branch diffusion three-dimensional scene generation method based on a multi-modal semantic graph, which comprises the following steps of: firstly, receiving multi-modal data such as sketches, texts, automatic completion instructions and scene general knowledge, extracting features and fusing the features into a unified multi-modal semantic graph; utilizing a graph neural network and an attention mechanism to enhance semantic graph features, and optimizing physical constraints through a physical engine; complementing the missing visual modality and graph structure relationship; performing quality scoring on the scene based on semantics, spatial relationships and physical constraints; and finally, respectively generating a spatial layout and a geometric shape through a double-branch diffusion model, and ensuring the coordination of the layout and the shape. The method has the advantages of multi-modal information fusion, physical rationality guarantee, high structure complementation capability, high-quality score optimization and efficient generation process, and is suitable for three-dimensional scene modeling requirements in the fields of virtual reality, augmented reality, robots and the like.

The invention relates to a visual transformer substation intelligent inspection system and method based on a multi-mode large language model, and belongs to the technical field of power system intelligence. The system obtains image, temperature, vibration and noise data of substation equipment in real time through a multi-modal data acquisition module, and performs preprocessing and fusion. A high-precision three-dimensional semantic model is constructed by using a three-dimensional dynamic modeling module, and the device attributes are automatically labeled by fusing LLM semantic understanding capability. A multi-modal large language model (LLM) engine is combined with cross-modal feature extraction, a dynamic knowledge base and a self-adaptive reasoning unit to realize accurate diagnosis of equipment faults. An augmented reality (AR) interaction module displays the real-time state of equipment through AR glasses and supports natural language interaction. The self-interpretation decision support module generates interpretable fault reports and maintenance suggestions, and the communication and feedback module is responsible for data uploading and remote alarm. According to the method, multi-dimensional perception, dynamic knowledge reasoning and self-adaptive decision support of the equipment state are realized, the intelligent level of substation inspection is remarkably improved, the inspection efficiency is improved by more than 40%, the omission ratio is reduced to less than 1%, and rapid diagnosis of more than 95% of novel faults is supported.

Example implementations are directed to recapturing or realigning a room or scene in an artificial reality (XR) environment as a three dimensional (3D) space. To initially capture a room, a user manually annotates, using an XR system, one or more walls around the XR system. The XR system then aligns or localizes itself relative to the room. Once a room is captured and stored, and the user in the future enters the room again, the XR system may not be able to align itself in the room due to, for example, lighting conditions. Rather than require the user to manually recapture every wall captured during the initial room capture, the XR system can select one wall for recapture and, after receiving an annotation or marking of the one wall from the user, use the selection to realign the XR system relative to the room.

The invention provides a multifunctional inspection device detection system based on a distribution network mobile operation terminal, and relates to the technical field of electric power detection, and the multifunctional inspection device detection system comprises a portable main terminal of a dynamic collaborative architecture, a wearable terminal for augmented reality interaction and a distributed heterogeneous sensing cluster, which form a closed-loop data chain through an electric power dedicated low-delay wireless communication network; the portable main terminal is integrated with a heterogeneous computing unit with adaptive computing power distribution, can perform real-time fusion analysis on multi-dimensional sensing data, and outputs a visual result containing fault location and confidence; the wearable terminal superposes fault information to a real scene in a three-dimensional marking form through a virtual-real fusion positioning technology, and supports eye movement and voice collaborative interaction; multi-module collaborative acquisition of the distributed heterogeneous sensing cluster is combined with a nanosecond timestamp synchronization mechanism, so that the limitation of traditional single parameter detection is broken through, rich and synchronous basic data is provided for subsequent analysis, and the comprehensiveness of routing inspection is greatly improved.

The invention relates to the technical field of artificial intelligence and data analysis processing, and provides a smart home complex scene object analysis method based on multi-modal fusion. The method specifically comprises the steps of performing standardization processing on input data, and extracting multi-scale features of local textures and global semantics; generating a candidate box and a category score by a YOLO model, and adaptively generating a box prompt, a point prompt and a category / text prompt according to the confidence coefficient and the target scale; and inputting the prompt information and the multi-scale features into a mask decoder together, generating a high-precision instance mask in the candidate region, and checking to obtain a final output. According to the method, repeated coding is avoided, the performance of a small object and the performance of a complex boundary target are effectively distinguished, the real-time performance and the resource efficiency are considered at the same time, and the method is suitable for scenes of smart home, indoor navigation, security monitoring, augmented reality and the like.

The invention discloses a large-span truss hoisting and splitting system and method based on digital twinning, and belongs to the technical field of building construction, and the system comprises a physical entity unit, a data acquisition and transmission unit, a digital twinning model unit, a function service and data analysis unit and an application and interaction unit. According to the invention, through real-time sensing of a physical entity state, multi-source data fusion transmission, high-precision digital twinning modeling, intelligent simulation analysis and decision optimization, and fusion of multi-modal man-machine interaction, a virtual control system which is in whole-course synchronous mapping and bidirectional interaction with a physical entity is constructed; according to the method, real-time visual monitoring, trend prediction and risk early warning of the hoisting and splitting process can be achieved, scheme preview and dynamic optimization are supported, virtual-real fusion operation guidance is achieved through the AR technology, and the safety, precision and efficiency of hoisting and splitting operation of the large-span truss are improved.

The invention relates to the technical field of auxiliary training, and discloses an AR auxiliary training system for improving the diagnosis and treatment capability of general practitioners on undifferentiated diseases, and an immersive training environment is constructed by adopting an augmented reality technology. The system comprises an environment sensing module, a space positioning module, a case data module, a virtual rendering module, an interactive acquisition module, an intelligent response module, a state control module and an evaluation calculation module. The environment sensing module adopts an RGB-D camera and an inertial measurement unit to collect environment and head movement data of a user; the spatial positioning module determines a virtual patient placement position based on an SLAM algorithm; the virtual rendering module renders a three-dimensional virtual patient in a real environment; the interaction acquisition module supports voice and gesture multi-mode interaction; the intelligent response module generates an intelligent patient answer; the evaluation calculation module carries out comprehensive evaluation from three dimensions. The invention provides a highly immersive and intelligent training environment, and has the advantages of low cost, reusability and high standardization degree.

The invention relates to the technical field of augmented reality, in particular to an AR real-time scene reconstruction and illumination matching system and method based on neural rendering, and the system comprises a real-time scene understanding module, a real-time neural radiation field module and a real-time reflection inference and enhancement module. Comprising a forward network, a feature transformation layer and a backward network, the forward network maps a high-dimensional rendering space to a feature manifold, the feature transformation layer executes mapping from the feature manifold to a rendering manifold, and the backward network performs rendering calculation based on a Riemannian metric driven adaptive ray tracing mechanism; the real-time reflection inference and enhancement module performs material prediction and illumination information calculation based on an illumination dynamic adaptation system on a differential manifold, real-time application of a neural radiation field technology in an AR scene is realized through an innovative differential geometry framework, and a real-time rendering frame rate of 30-60 fps is achieved while a high-quality rendering effect is kept.

The invention relates to the field of electric power systems, in particular to an electric power facility remote intelligent maintenance method and system. The method comprises the following steps: collecting three kinds of heterogeneous monitoring data of vibration spectrum, infrared thermal imaging and partial discharge signals; mapping the data to a three-dimensional feature fusion space, and calculating a mahalanobis distance to generate a fusion feature matrix; extracting spatio-temporal features by using a convolutional long-short-term memory network, and outputting a triple diagnosis result including a fault type, a severity level and an evolution trend; searching a dynamic maintenance scheme in a maintenance strategy knowledge graph based on the diagnosis result; solving an optimal resource scheduling scheme by adopting an improved Hungary algorithm in combination with the geographic topology and the resource state; the maintenance operation is remotely guided through the augmented reality terminal, and real-time verification is carried out; and collecting the maintained data, carrying out residual analysis, and reversely optimizing the knowledge graph. The method realizes full-process intelligent management, improves timeliness and reliability of operation and maintenance of electric power facilities, and is suitable for a remote intelligent maintenance scene of an electric power system.

A system and method for generating and updating a posegraph for multi-user augmented reality experiences. The system receives initial pose data from multiple client devices and generates a posegraph based on this data. When client devices come within proximity of each other, the system detects this and receives relative pose observations from the devices. The system then updates the posegraph based on these observations, assigning confidence values to improve accuracy. This approach enables efficient synchronization of spatial information across devices, allowing for seamless shared AR experiences in large-scale environments without the need for complete map sharing or pre-mapped areas.

The invention relates to the technical field of forest steppe fire emergency command, and discloses a forest steppe fire comprehensive monitoring and emergency command method and system. The method comprises the following steps: acquiring multi-source monitoring data of a satellite, an unmanned aerial vehicle and a ground sensor, and constructing a fire scene multi-dimensional feature vector through cooperative training and feature fusion; inputting the feature vectors into a physical simulation model to generate fire scene spreading speed and temperature gradient data; analyzing a terrain obstacle coefficient based on the spreading speed data and generating a helicopter no-fly zone coordinate and a passing attenuation factor; and solving and outputting a rescue unit deployment instruction through the scheduling matrix, and projecting a holographic image by using an augmented reality terminal to realize dynamic closed-loop feedback. Through deep fusion of a physical mechanism and reinforcement learning, the problem of separation of traditional fire prediction and resource scheduling is solved, intelligent decision-making of fire accurate prediction and emergency response is realized, and the accuracy and timeliness of fire prevention and control are remarkably improved.

The invention belongs to the technical field of augmented reality, and discloses an AR scenario furniture identification and dynamic removal system based on artificial intelligence, and the system comprises the steps: carrying out the multi-view image registration, furniture entity segmentation and shielding completion analysis based on the obtained hotel scene AR image sequence data, and forming a complete furniture contour feature; the style similarity of the furniture multi-dimensional feature vectors is analyzed, and a furniture style recognition result is obtained; the method comprises the following steps: acquiring AR scanning data of a home environment, performing furniture removal priority ranking through space conflict analysis and style coordination evaluation, generating a dynamic removal strategy, establishing furniture three-dimensional model data based on the dynamic removal strategy, and performing material texture mapping and shadow fusion to obtain a realistic rendering effect; an interactive optimization adjustment scheme is generated, and scene parameter real-time adjustment and optimization and visual effect improvement are realized through user feedback; the reality sense of virtual home display and the user experience effect are remarkably improved.

The invention relates to the technical field of landscape design, and provides a landscape design data processing method based on artificial intelligence, which comprises the steps of multi-source heterogeneous data acquisition and fusion, knowledge graph driven design constraint extraction, dynamic demand perception and weight distribution, generative adversarial design of a coupling physical model, multi-objective optimization and scheme decision. And virtual-real fusion scheme verification can be carried out. The method comprises the following steps of: constructing a multi-modal data set by acquiring geographic information, real-time environment monitoring and other data, identifying constraint generation boundary conditions by using a knowledge graph, analyzing requirements and adjusting weights by using natural language processing and a reinforcement learning model, inputting constraint conditions and weight parameters into a generative adversarial network to generate a candidate scheme set, and constructing a multi-modal data set; and adopting a Pareto frontier algorithm to optimize and output an optimal solution set, and finally importing the optimal solution set into an augmented reality terminal for verification and adjustment. According to the method, landscape design data can be efficiently processed, a scheme meeting multi-aspect requirements is generated, and the design quality and efficiency are improved.

The embodiment of the invention discloses augmented reality equipment and a corresponding equipment calibration method. The method comprises the steps of obtaining a calibration request, displaying a virtual mark on a target display device, outputting matching prompt information to prompt a user to watch an entity mark and the virtual mark by using target side eyes, and changing a relative posture relationship between the entity mark and the head of the user to enable the entity mark and the virtual mark to be in a matching state in the eyes of the user, and after the matching is determined, calling the target live-action camera assembly to obtain a real scene image containing the entity mark, determining a target offset according to the first position of the virtual mark on the target display device and the second position of the entity mark in the real scene image, and calibrating the augmented reality device according to the target offset. According to the method, equipment calibration is carried out based on the inherent display device of the augmented reality equipment, the live-action camera assembly and the entity marks easily obtained in the external environment, a user can carry out calibration anytime and anywhere, the equipment calibration threshold is lowered, and the method is simple and easy to implement.

Systems, methods, and other embodiments described herein relate to superimposing computer-generated exterior vehicle lights over asynchronous real-world exterior vehicle lights to reduce a sensory overload of a vehicle driver. In one embodiment, a method includes assessing a sensory environment of a vehicle driver. The method also includes determining that the vehicle driver is in a sensory-overloaded state based on 1) a characteristic of the sensory environment, 2) physiological sensor data for the vehicle driver, and 3) driving behavior sensor data. The method also includes superimposing an augmented reality (AR) overlay of computer-generated synchronized exterior vehicle lights over asynchronous real-world exterior vehicle lights viewed through an AR display device of the vehicle based on a determination that the vehicle driver is in the sensory-overloaded state.

The invention discloses a dynamic rendering method and system for virtual reality, a storage medium and electronic equipment, and relates to the technical field of virtual reality, augmented reality and computer graphics. Therefore, the frequency and time sequence change of the sight focus of the user hitting the surface of the virtual object in the virtual scene are analyzed, so that the relative motion trend and observation intention of the user and the object are pre-judged, predictive and adaptive scheduling of rendering resources is realized, and optical feedback conforming to the physical law, namely, dynamic material, is triggered at the sight focus, so that the real-time performance of the user is improved. Therefore, the interaction fineness in the process of interaction between the user and the VR system is improved.

The invention discloses a PICC (Peripherally Inserted Central Catheter) tip precise navigation fixing method and system based on electrocardiogram real-time positioning. High-precision positioning and safe fixing of a catheter tip are realized through a multi-modal data fusion and deep learning technology. The method comprises the following steps: collecting intracavity electrocardiosignals (ECG) in real time through a catheter built-in electrode, and obtaining blood vessel wall contact pressure and temperature data in combination with an optical fiber sensor; an improved wavelet threshold algorithm is adopted to dynamically suppress motion artifacts, and P-wave features are enhanced; the preprocessed ECG signals are input into a spatial-temporal feature fused Transformer model, a time attention layer is used for analyzing P-wave time sequence changes, a space attention layer integrates multi-lead space distribution features, and the positioning precision is optimized in combination with preoperative blood vessel anatomical data; the ECG positioning result and the optical fiber sensing data are fused through Kalman filtering, three-dimensional position information of the tip end of the catheter is generated, and real-time navigation is conducted on an augmented reality interface; and when the P wave amplitude reaches a CAJ threshold value, the contact pressure is safe and no abnormal temperature exists, a shape memory alloy (SMA) fixing ring is triggered to contract, and accurate fixing is achieved. The method solves the problems that a traditional method depends on X rays and is poor in anti-interference performance, has the advantages of being free of radiation, high in real-time performance and adaptive to blood vessel deformation, and is suitable for clinical P catheter implantation.

A system and method for contextual three-dimensional messaging in augmented reality (AR) environments is disclosed. The system receives chat messages with specified real-world destinations and stores them associated with those locations. When a user wearing an AR device enters a destination location, the system detects their presence using techniques like GPS, Wi-Fi positioning, or computer vision. It then generates a 3D visual representation of the message and determines an appropriate spatial position within the physical environment based on environmental analysis and object detection. The 3D message is displayed at the determined position in the AR view. The system can analyze message content to identify topics and match them to detected real-world objects for contextual placement. Users can interact with displayed messages through gestures or voice commands to reply, forward, delete, or reposition messages. This enables immersive, location-aware messaging experiences that seamlessly blend digital content with the physical world.

The invention relates to the technical field of augmented reality glasses optical correction, and specifically provides an eye movement distortion detection method. The method comprises the following steps: acquiring an AR glasses playing image and identifying a visual saliency region to establish an attention priority order; detecting an eyeball movement track direction vector and an instantaneous speed in real time; determining a predicted attention target according to the motion direction and the attention priority; generating a distortion correction parameter set in combination with eyeball arrival time and spatial distribution information; performing pre-distortion compensation rendering on the candidate area in a pre-generation period before eyeballs reach the actual attention area to form a pre-corrected image buffer area; and finally, outputting a pre-corrected image matched with the actual stay area. Space-time synchronization of eyeball movement and image compensation is achieved through predictive rendering, the image distortion and color separation phenomena in the glancing process are eliminated while the low-delay characteristic is maintained, and the visual definition and comfort in a dynamic scene are remarkably improved.

The invention discloses a mirror image display image overturning processing method and system for AR equipment. The method comprises the steps that layered mirror image overturning is carried out; performing unified horizontal flipping processing on the input image of the physical camera and the virtual rendering layer through a GPU shader; independently rendering the UI channel; in a UI channel independent of the main image channel, drawing a UI layer according to the original space coordinates; calibrating interactive coordinates; performing reverse mapping on the position coordinate of the user operation event through a coordinate reverse mapping algorithm, so that the position coordinate is matched with the logic position of the UI control which is not overturned; optimizing dynamic performance; and monitoring a system load index in real time, and dynamically adjusting an image processing parameter according to a performance threshold so as to maintain a stable frame rate. The invention provides an efficient integrated solution, and the consistency of vision and interaction is realized through a cooperative processing mechanism of Shader image flipping and multi-channel rendering decoupling design. And the image direction logic consistency, the operation interface readability and the user experience real-time performance are effectively considered.

The invention relates to the technical field of virtual simulation, in particular to an AR (Augmented Reality)-based medical-seeing whole-process guiding system and method and a medium, the system is accessed to a hospital management system and an electronic medical record system, and the system comprises a cloud server used for acquiring a current medical-seeing demand of a target user based on medical-seeing information of the electronic medical record system and sending the current medical-seeing demand to the target user; based on the treatment demand and the current positioning, generating a guide line, and transmitting the guide line to the terminal equipment; the AR equipment comprises a camera and is used for acquiring a field image and transmitting the field image to the terminal equipment; the terminal equipment is used for generating a virtual guidance picture based on the guidance line and the field image and sending the virtual guidance picture to the AR equipment; and the AR equipment is also used for presenting the virtual guiding picture, so that the target user sees a doctor according to the virtual guiding picture, the guiding picture is realized in a virtual enhancement mode, the patient can reach the doctor seeing position according to the guiding picture, the doctor seeing efficiency is improved, and the doctor seeing experience is also improved.

A computer-implemented system and method for pupil-directed retinal projection in near-eye displays are disclosed. The computer-implemented system provides smart glasses with directed physical pixels that project light beams / signals directly onto user's retina based on pupil position and size. The glasses comprise frame, lenses with directed pixel layers, sensors for tracking pupil movement. Each directed pixel generates multiple virtual pixels by rapidly changing its emission angle. Each directed pixel with pupil's real-time tracking, provides automatic adjustments to virtual contents, ensuring accurate alignment of images with field of view of users while identifying vergence-accommodation conflict. The glasses function as prescription lenses, virtual reality displays, augmented reality devices without traditional optical systems. Additional features include depth sensors, cameras, connectivity to peripheral devices. The glasses enable seamless blend of virtual and real-world experiences, creating immersive “Mixverse” environment. Various input methods, including gesture recognition and brain-computer interfaces, allow for intuitive control and interaction.

Disclosed are a three-dimensional reconstruction method and apparatus based on augmented reality. The method comprises: displaying at least one virtual closed auxiliary line surrounding a target object, and a movable cursor; in response to the movable cursor moving along the virtual closed auxiliary line, determining in real time whether the real-time pose of an image collection device matches a panoramic capture reference point adjacent to the movable cursor; in response to the real-time pose of the image collection device matching the panoramic capture reference point, acquiring a target object image frame corresponding to the panoramic capture reference point and the real-time pose of the image collection device, so as to form image frame-pose pair data; and at least on the basis of the image frame-pose pair data corresponding to each panoramic capture reference point, executing three-dimensional reconstruction for the target object. The three-dimensional reconstruction method based on augmented reality according to some embodiments of the present application can effectively guide the panoramic capture process of an image, thereby improving the quality, efficiency, angle coverage rate, overlap rate, etc. of image collection for three-dimensional reconstruction.

The invention discloses infrared night vision AR (Augmented Reality) intelligent glasses based on multispectral fusion, and relates to the technical field of infrared intelligent application. High-precision scene perception in a low-light / light-free environment is realized by fusing dual-channel data of low-light imaging and infrared thermal imaging and combining cross-modal feature matching and dynamic pose compensation; an environment detail structure is restored by a low-light image enhancement technology, thermal feature targets such as organisms are accurately recognized through thermal imaging target segmentation, and a three-dimensional environment model with space geometric information and target attributes is constructed through heterogeneous feature fusion; and dynamically adjusting the display transparency of the key target in the AR view field through a virtual information layer adaptive mixing mechanism driven by a hot target attribute, and finally outputting a virtual-real fused enhanced view, thereby breaking through the illumination limitation of the traditional AR glasses, and improving the visual effect of the AR glasses. And immersive augmented reality experience with panoramic detail perception and hot target accurate positioning is provided for the user in a dark environment.

The invention discloses an intraoperative pulmonary nodule positioning method and system based on fusion of a CT image and an endoscope video. The method comprises the following steps: firstly, constructing a three-dimensional lung model containing a pulmonary nodule position based on preoperative high-resolution CT data; generating a real-time lung surface model by using an endoscope video stream through a three-dimensional reconstruction technology during the operation; a feature point extraction and matching algorithm is adopted, and a non-rigid registration technology is combined to realize accurate registration of the preoperative model and the intraoperative dynamic model; projection display of pulmonary nodules in a real-time endoscope visual field is established through space coordinate mapping, and a dynamic compensation algorithm is developed to solve the problem of tissue deformation caused by respiratory movement and instrument operation. Meanwhile, the virtual nodule position is overlaid to an endoscope video picture through the augmented reality technology, and visual intraoperative navigation is provided for surgeons. The method effectively solves the technical bottleneck that a traditional method depends on a metal marker and cannot adapt to intraoperative tissue deformation and the like, and has clinical practical value.

A navigation system and method are disclosed for operation in GPS-denied environments using quantum-inspired sensor fusion, dynamic virtual anchor points (VAPs), and predictive environmental modeling. The system represents multiple position hypothesis using wavefunction-like expansions and integrates VAP-based triangulation for drift correction. A predictive modeling module ingests solar, geomagnetic, and environmental data to proactively adjust sensor weighting. A cybersecurity module employs quantum-algebraic key generation and location-derived ephemeral keys to secure inter-device communication. The system includes an augmented reality (AR) interface to visualize and edit anchor references, and a neurofeedback module that adapts the AR interface based on real-time physiological signals from the user. The method further enables anchor optimization via AI-driven repositioning and supports low-power edge execution using approximate amplitude filtering. Additional modules may include fractal antennas, neuromorphic processors, and adaptive forecasting layers to maintain positional accuracy and user experience in subterranean, multi-floor, or magnetically complex environments.