203 results about "Real time navigation" patented technology

The invention provides an underwater vehicle multi-source information fusion accurate navigation method and system. The method comprises the following steps: firstly, acquiring inertial navigation data, DVL data and ocean current information of an underwater vehicle and observation information of a distance between the underwater vehicle and a beacon, and preprocessing the inertial navigation data, the DVL data and the ocean current information; then, establishing a state model according to the kinematics principle of the underwater vehicle, and establishing an observation model by combining various types of information; carrying out fusion processing on the state model and the observation model by adopting a self-adaptive Kalman filtering algorithm; and finally, estimating the current position of the underwater vehicle according to the fused state vector, comparing the current position with a preset target position to calculate a deviation, and correcting the deviation by adjusting a rudder angle and the rotating speed of a propeller. According to the method, multi-source information is integrated, innovation is carried out on construction of a state model and an observation model and position estimation and deviation correction, adaptive Kalman filtering is adopted, and the method has the advantages that the navigation precision is improved, the ocean current influence is considered, adaptive adjustment is realized, and real-time navigation is realized.

The invention discloses a thyroid intraoperative real-time navigation method and a thyroid intraoperative real-time navigation system based on multi-mode optical fusion. The thyroid intraoperative real-time navigation method comprises the following steps: outputting visible light through an endoscope and coupling light waves of a narrow-band multispectral light source to irradiate an operative field, exciting parathyroid glands to generate near-infrared fluorescence, and receiving reflected visible light, split light, near-infrared fluorescence and laser speckle signals through an endoscope probe. And separating the composite optical signal into four channels, and respectively generating an anatomical structure color image, a blood vessel spectroscopic image, a parathyroid gland near-infrared fluorescence image and a laser speckle image. Performing decorrelation processing on the laser speckle image to generate a blood flow dynamic pseudo-color decorrelation speckle image; an anatomical structure, a blood vessel center line, a parathyroid gland contour and blood flow dynamic feature points are extracted through a multi-modal registration technology, after affine transformation space alignment is conducted, a comprehensive imaging map containing the anatomical structure, blood vessel distribution and parathyroid gland function marking information is generated through a wavelet fusion algorithm, and intraoperative multi-dimensional real-time tissue navigation is achieved.

The invention relates to the technical field of path planning, and discloses a real-time path data planning processing method and system based on SLAM. The method comprises the following steps: performing semantic-geometric joint feature extraction through a laser radar and an RGB camera to obtain joint observation data; performing covariance propagation on the SLAM state vector based on semantic constraint Kalman filtering to obtain a positioning covariance and a covariance ellipse; performing constraint propagation on the semantic object set to generate virtual feature points to construct an enhanced feature map; environment grid safety scoring is carried out according to the semantic risk weight and the obstacle distance; semantic cost and SLAM uncertainty processing is carried out through bidirectional A * search, and a real-time navigation path is generated. According to the method, the technical problem of insufficient comprehensive consideration of semantic security constraint and positioning uncertainty in real-time path planning based on SLAM in a feature sparse environment is solved.

The invention provides an oral implant navigation method and system and a storage medium, after an optical locator is fixedly arranged on an implant mobile phone, three-dimensional data of a rotating shaft of the implant mobile phone, the tail end of the rotating shaft and a spherical drill on an optical three-dimensional coordinate system of the optical locator are obtained, and a registration pit is used as a medium to obtain a three-dimensional coordinate system of the implant mobile phone; and positioning three-dimensional data of the three-dimensional coordinate system in the optical three-dimensional coordinate system, registering the three-dimensional data of the pits on the CT three-dimensional coordinate system to complete registration, calculating the pose of the tip of the drill point and the pose of the ideal path under the positioning three-dimensional coordinate system, and performing real-time navigation on the planted mobile phone according to the difference between the tip of the drill point and the ideal path. An optical positioning instrument is fixedly arranged on the planting mobile phone, and while the planting mobile phone is used for drilling operation, image data of the optical identification points are collected through the optical positioning instrument for real-time navigation; the optical positioning instrument and the planting mobile phone are integrally connected, so that the process of positioning the planting mobile phone in real time can be omitted, and navigation errors are effectively reduced.

The invention provides an oral surgery positioning and navigation method and system and a storage medium, and the method comprises the steps: calibrating an implanted mobile phone to obtain a unit vector of a rotating shaft of a drill bit and a three-dimensional coordinate value of the tip of the drill bit under an optical three-dimensional coordinate system, scanning to obtain a CT three-dimensional model of a patient, and segmenting to obtain a tooth CT model and an alveolar bone CT model; generating a tooth three-dimensional point cloud according to the real-time pattern of the speckle structured light on the teeth of the patient, acquiring a matrix transformation relation between a CT three-dimensional coordinate system and an optical three-dimensional coordinate system, and performing real-time navigation on the implanted mobile phone according to the real-time point position deviation and the real-time angle deviation of the drill bit. According to the technical scheme, the matrix transformation relation between the CT three-dimensional coordinate system and the optical three-dimensional coordinate system is calculated through the tooth CT feature points and the tooth point cloud feature points, and auxiliary navigation is carried out by comparing the target position of the implant with the real-time pose of the tip of the drill bit, the direction vector of the planting path and the unit vector of the rotating shaft of the drill bit. Operation is convenient and positioning precision is high.

The invention provides a method and a system for predicting idle parking spaces of a parking lot. The method comprises the steps that ramp curvature parameters extracted from topological structure data of the special-shaped parking lot and historical vehicle turning radius data are fused, and a spatial-temporal topological graph of the special-shaped parking lot is generated; aggregating the parking space occupancy state data of all the special-shaped parking lots and the special-shaped parking lot space-time topological graph through a federal transfer learning framework to obtain target feature extraction model parameters; combining the time change characteristics of the channel flow of the special-shaped parking lot in the spatial-temporal topological graph of all the special-shaped parking lots and the target characteristic extraction model parameters, and generating a dynamic parking space distribution strategy; and mapping the dynamic parking space distribution strategy to a real-time navigation path of the special-shaped parking lot space-time topological graph, so that the to-be-parked vehicle arrives at the idle parking space through the real-time navigation path. According to the invention, the dynamic parking space distribution strategy is generated by fusing the topological structure and historical data of the special-shaped parking lot and real-time navigation is carried out, so that the parking space utilization rate and the parking efficiency are optimized.

The invention discloses a surgical robot real-time image registration method based on multi-modal feature fusion. The method comprises the following steps: acquiring different modal medical images before and during an operation; respectively extracting depth features by using a first lightweight feature extractor and a second lightweight feature extractor, wherein the second extractor performs dynamic adjustment according to the real-time quality evaluation of the intraoperative image; mapping the depth features to the same submerged space to obtain submerged space representation through a semantic feature conversion module comprising a projection network of a pre-training segmentation model and contrast loss training; fusing the submerged space representation by using a cross-modal attention mechanism of uncertainty modulation to obtain a fusion feature; and based on the fusion features, the dense displacement field is regressed through a deep learning network to realize image real-time registration. According to the method, the precision and robustness of multi-modal image registration in a complex operation environment are remarkably improved, the real-time navigation requirement is met, and reliable guidance is provided for surgeons.

The invention provides an electric power optical communication positioning system and method based on a PLC, and relates to the technical field of PLC electric power optical communication. After a real-time user starts a mobile terminal camera, a real-time optical signal of a target lamp is captured through the camera; the mobile terminal obtains a real-time ID and a real-time physical coordinate by decoding the real-time optical signal; after receiving a target parking space number input by a real-time user, the mobile terminal matches a parking space lamp ID and a parking space physical coordinate pre-bound with the target parking space number; and calculating a navigation path according to the real-time physical coordinates and the parking space physical coordinates, and outputting a real-time navigation path. The technical problem that in the prior art, due to the fact that underground space positioning is high in cost, poor in precision and prone to interruption of positioning communication, sub-meter continuous positioning and intensive management are difficult to carry out in a network-free underground space is solved. The comprehensive technical effects of remarkably saving the cost, improving the positioning precision, optimizing the user experience and enhancing the management efficiency are achieved.

The invention relates to the technical field of focus positioning, in particular to a hysteromyoma focus accurate positioning method combining image analysis and data fusion, which comprises the following steps: acquiring multi-modal uterus image data, and carrying out artifact suppression and spatial registration on an original image; performing three-dimensional reconstruction on the preprocessed multi-modal image data set to generate a three-dimensional uterus model comprising anatomical structure features; lesion feature segmentation is carried out in the three-dimensional uterus model, and morphological parameters and textural features of a myoma lesion are extracted; carrying out hemodynamic analysis to obtain blood perfusion parameters and blood vessel distribution characteristics of the focus area; the blood perfusion parameters and the blood vessel distribution characteristics are fused, the three-dimensional uterus model is combined, and a focus biomechanical characteristic distribution diagram is constructed; and generating a real-time navigation path according to the biomechanical characteristic distribution diagram, and outputting a positioning report. According to the method, personalized ablation energy suggestions are made, the ablation treatment efficiency and success rate are effectively improved, the ablation energy is dynamically adjusted, and the treatment efficiency and safety are ensured.

The invention relates to the technical field of medical equipment, and provides a multi-modal lymphedema assessment and surgical navigation system based on image processing, which comprises a 3D scanning modeling module used for acquiring three-dimensional point cloud data of the body surface of a patient through structured light 3D scanning equipment, an iconography examination analysis module used for performing U-Net image segmentation on CT / MRI image data, and an image processing module used for processing the CT / MRI image data. The ultrasonic result calculation module is used for carrying out Canny edge detection on an ultrasonic image to determine the boundary of a surgical site, and the data integration and navigation generation module is used for realizing multi-modal data fusion through mutual information maximization, generating a surgical path based on FMM and carrying out real-time navigation in combination with an AR technology. According to the method, objective evaluation of lymphedema and accurate navigation of the operation are realized through accurate integration of multi-modal data and an image processing technology, the diagnosis and treatment accuracy is effectively improved, the operation risk is reduced, complications are reduced, and a scientific basis is provided for personalized treatment.

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.

Systems and methods for real-time navigation of reaming of an acetabulum are disclosed. A first tracking element is interfaced to a reamer. A second tracking element is interfaced at or near the acetabulum. The first tracking element can be interfaced to an outer casing surrounding a portion of the shaft of the reamer. A depth and a tilt angle of the reamer with respect to the acetabulum are determined, based on a location of the first and second tracking elements. Based on a surgical plan, the depth and the tilt angle, the volume of removed bone from the acetabulum can also be determined.

The invention relates to the technical field of path planning, in particular to an unmanned vehicle dynamic path optimization method and system based on artificial intelligence. The method comprises the following steps: collecting regional state data based on real-time navigation information, carrying out abnormal traffic flow fluctuation analysis, carrying out abnormal road section visual rendering, and constructing an abnormal fluctuation rendering road network; performing abnormal disturbance propagation chain reaction mining on the abnormal fluctuation rendering road network, performing dynamic risk effect modeling, and constructing a risk linkage effect prediction engine; performing user behavior intention deep analysis and riding intention situation prediction to obtain a user intention prediction situation map; and performing adjacent vehicle path pre-judgment based on the user intention prediction situation map, and performing path conflict probability calculation to obtain a multi-vehicle path conflict probability. According to the invention, the robustness of the unmanned driving system to deal with sudden situations and complex dynamic environments is improved, and the riding safety and the path accessibility are improved.

The embodiment of the invention provides a navigation state synchronization method, device and equipment and a computer storage medium, and belongs to the technical field of positioning. Receiving first GNSS satellite data, including a first timestamp; searching first IMU data corresponding to the first timestamp from an IMU data queue; carrying out fusion calculation, and determining a real-time navigation state under the first timestamp; moving a queue head position of the IMU data queue to second IMU data, and initializing an increment integral state; performing incremental integral calculation based on the second IMU data and a target IMU data set in the IMU data queue to obtain a real-time incremental pre-integral; and performing navigation state calculation according to the real-time navigation state and the real-time increment pre-integration under the first timestamp, and determining the current navigation state. According to the method disclosed by the embodiment of the invention, the purposes of accurately fusing navigation combinations and improving the navigation accuracy are achieved.

The invention discloses a stereotactic puncture path planning method based on reinforcement learning. The stereotactic puncture path planning method comprises the following steps: S1, constructing a risk weight map; s2, establishing a puncture constraint set; s3, performing global search on the frog group initial population by adopting a discrete frog leaping optimization algorithm to obtain an initial puncture path set with consistent constraints; s4, mapping the real-time navigation state vector template into a state set; s5, when Q value updating is executed, strategy smooth regularization is introduced, and state-action-award closed-loop iteration is completed; and S6, when the simulation navigation system judges that the puncture instrument reaches the target ventricle coordinate or the navigation state vector triggers the risk threshold early warning of the puncture constraint set, the final simulated refined puncture path is output to a surgical navigation interface. The probability of damaging a key structure in an operation is obviously reduced.

The invention discloses an orthopedic surgery planning and real-time navigation method and system based on artificial intelligence and multi-modal image fusion. The method comprises the following steps: receiving and fusing preoperative multi-modal image data of a patient, and automatically segmenting a key structure by using a deep learning model to generate a three-dimensional virtual model; an optimal operation path is planned through an artificial intelligence model according to the three-dimensional virtual model; the spatial positions of the surgical instrument and the target skeleton area of the patient are tracked in real time through an electromagnetic positioning system, and real-time spatial position data and the three-dimensional virtual model are registered and are fused, overlapped and displayed on a surgical navigation screen; the relative position deviation between the tip of the surgical instrument and the optimal surgical path and the key tissue safety area is calculated in real time, and an early warning is given to a surgeon according to the relative position deviation. The optimal operation path can be accurately and objectively generated so as to ensure the adaptability of the operation path and the patient. Therefore, doctors can pay attention to the operation process specifically, and the operation stability and reliability are improved.

The invention discloses a navigation system for a liver tumor resection operation, and aims to solve the problems that in the prior art, the accuracy of the liver tumor resection operation is insufficient, the risk in the operation is high, and the evaluation after the operation is incomplete. The system comprises a preoperative data acquisition module, a preoperative three-dimensional modeling module, an intraoperative positioning module, an operation navigation module, a risk prompt module and a postoperative data analysis module. Through preoperative CT or MRI image data acquisition, automatic segmentation and three-dimensional reconstruction of liver, tumor and blood vessels are carried out by using a deep learning algorithm, and a high-precision anatomical model is generated. During the operation, the position of the surgical instrument is obtained in real time by using an optical tracking or electromagnetic positioning technology, spatial precise alignment of the surgical instrument with a tumor and surrounding tissues is realized in combination with a model registration algorithm, and a surgical path is displayed through a real-time navigation interface. And the risk prompting module calculates an excision risk coefficient and prompts a doctor in real time based on the shortest distance between the tumor and the blood vessel, the relative distance between the instrument and the target area and the trajectory change.

The invention provides a multi-modal image fusion system and method for neurosurgery, and the method comprises the steps: carrying out the rigid transformation of a multi-modal magnetic resonance image and an ultrasonic image, and obtaining a preoperative magnetic resonance image and an intraoperative ultrasonic image after preliminary alignment; inputting the preoperative magnetic resonance image and the intraoperative ultrasonic image into a pre-trained lightweight deformation registration network for deformation modeling to obtain a voxel-level dense deformation field, and determining a confidence map of deformation field region registration based on the dense deformation field; according to the confidence map, multi-scale feature fusion based on confidence weighting is carried out on the deformed preoperative multi-modal labeling information and the corresponding features of the intra-operative ultrasonic image, and a three-dimensional anatomical structure chart for real-time navigation in the neurosurgery operation is obtained. Based on the scheme, brain tissue drift can be dynamically compensated in real time in a neurosurgery operation, and multi-modal image fusion is guided based on a compensation result.

The invention provides a handheld photoacoustic multi-mode vascular puncture and tissue damage diagnosis system and device, and belongs to the technical field of photoacoustic imaging. According to the handheld multispectral photoacoustic imaging device, elastic force feedback and blood vessel real-time development are integrated, and the puncture success rate is increased by 30%; by virtue of hemoglobin / collagen double-index imaging, the stress injury can be pre-warned 72 hours in advance; the 3D hematoma volume automatically calculates an error lt; and repeated puncture and missed diagnosis are remarkably reduced. The invention provides a quantitative evaluation and real-time navigation integrated scheme for vascular puncture and tissue damage, and is safe and efficient.

The invention relates to a combined navigation sensor and an optimization method thereof, the combined navigation sensor comprises a chassis plate, two roller assemblies and a plane positioning module, the two roller assemblies and the plane positioning module are installed on the chassis plate, the chassis plate is vertically provided with two assembly holes, each roller assembly comprises a U-shaped frame and an omnidirectional wheel rotatably installed in the U-shaped frame, the U-shaped frame is fixedly arranged in the assembly holes, and the omnidirectional wheel is rotatably installed in the U-shaped frame. A photoelectric encoder is arranged on a wheel shaft of the omnidirectional wheel; a main control chip, a gyroscope and an accelerometer are arranged on the plane positioning module; the IMU data of the gyroscope and the accelerometer can be effectively combined with the odometer data of the omnidirectional wheel to obtain more accurate speed estimation, the integration drift of the IMU data can be reduced through the fusion method, meanwhile, the accuracy of the odometer data is utilized, a traditional inertial sensor is combined with the orthogonal omnidirectional wheel, and the speed estimation accuracy is improved. A highly integrated sensor fusion technology is realized, the real-time navigation positioning capability of the mobile robot is improved, and the mobile robot has high real-time performance, strong anti-interference performance and high precision.

The invention provides a radar point cloud data-based mine vehicle speed estimation method and system, a storage medium and a program product, and is applied to a vehicle in a mine, the vehicle is provided with a radar to collect point cloud data in the mine, and the method comprises the following steps: obtaining point cloud data of a current frame, and preprocessing the point cloud data to obtain a pre-processed point cloud data; extracting the radial speed, azimuth angle and pitch angle of each point; a plurality of speed candidate values are generated by adopting a random sample consensus (RANSAC) algorithm, and the optimal speed is estimated; and counting the optimal estimation value of the multi-frame speed, and carrying out sliding window smoothing processing to obtain a final vehicle speed estimation value. According to the method, a plurality of speed candidate values are obtained from the point cloud data by adopting the RANSAC algorithm, the speed candidate value with the most inner points is selected as the optimal candidate speed to resist noise and abnormal point interference, the optimal candidate speed of multiple frames is smoothly processed by utilizing the sliding window averaging method, the speed estimation accuracy is ensured, and the requirement of real-time navigation of mine vehicles is met.

The invention relates to the technical field of image processing, and discloses an interventional navigation method and system based on multi-modal image fusion. The method comprises the following steps: segmenting CT angiography data to form a three-dimensional vascular skeleton model, calculating MRI perfusion data to generate a vascular flow velocity field, and constructing a vascular geometric constraint matrix; performing diffusion reconstruction on the constraint matrix and the instrument position information, and outputting an instrument motion prediction track; estimating the postures of the tips of the X-ray perspective imaging instruments to form instrument-blood vessel space correlation features; safety navigation constraint parameters are generated through distance field calculation; and generating a real-time navigation instruction containing a propulsion distance and a rotation angle by adopting a path planning algorithm. The technical problems that in a traditional interventional navigation system, multi-modal image data fusion is insufficient, instrument motion prediction is inaccurate, and a safety constraint mechanism is incomplete are solved, and the precision, safety and real-time performance of interventional operation navigation are improved.

The invention discloses a robot autonomous navigation method based on deep reinforcement learning in a dynamic environment, and relates to the field of robot navigation and artificial intelligence. The method comprises the following steps: constructing a simulation training environment; designing a state space, an action space and a multi-layer reward function; constructing a deep reinforcement learning model based on a double-delay depth deterministic strategy gradient (TD3), and innovatively introducing action constraint regularization (ACR) into an actor network loss function of the deep reinforcement learning model to form an ACR-TD3 algorithm; training the model in a simulation environment until convergence; and performing real-time navigation by using the trained model. The motion trail of the robot is effectively smoothed through action constraint regularization, the safe distance between the robot and an obstacle is guaranteed, unreasonable speed output is limited, and therefore the success rate and efficiency of navigation in the dynamic environment are remarkably improved, meanwhile, the good generalization ability is achieved, and the application prospect is wide. And an effective scheme is provided for solving the autonomous navigation problem of the mobile robot in a complex dynamic scene.

The invention relates to the technical field of medical image processing and surgical navigation, in particular to an arthroscopic surgery real-time navigation method and system based on multi-modal image fusion, and the method comprises the following steps: S1, collecting preoperative CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) data of a patient to generate a three-dimensional model, and collecting an intra-operative arthroscopic real-time video to provide input data for subsequent registration; and S2, performing image preprocessing, including denoising and enhancement, on the three-dimensional model and the arthroscope video, and extracting key anatomical features and lesion boundaries to obtain a processing result which can be used for registration. According to the method, the preoperative three-dimensional model and the intra-operative arthroscope real-time video are fused, and multi-strategy registration, closed-loop correction and dynamic updating are combined, so that continuous registration and real-time navigation of multi-modal data are realized, and the problems that the traditional arthroscope surgical navigation mostly depends on a single-modal image, and the navigation accuracy is low are solved. And the problem of insufficient intraoperative registration precision caused by lack of multi-source information fusion is solved.

The invention relates to the technical field of inertial navigation, in particular to an inertial navigation data correction method based on a neural network, which comprises the following steps: firstly, collecting original data of an inertial measurement unit and preprocessing; secondly, generating an attitude error label by using a high-precision reference system, and constructing a training data set containing historical time sequence information in a sliding window mode; then constructing a hybrid neural network model, and performing iterative training by using the training data set; and finally, in real-time navigation, obtaining an inertial data sequence at the current moment by maintaining a historical data buffer area, inputting a trained model to predict an error compensation value, correcting an original calculation attitude, and outputting the corrected original calculation attitude. The method gets rid of dependence on an accurate physical model through a data driving mode, utilizes the hybrid neural network to deeply mine time sequence accumulation characteristics of inertial data, realizes long-endurance high-precision autonomous navigation, and remarkably inhibits divergence of attitude errors.

The invention relates to a minimally invasive implantable frontal lobe brain-computer interface method and device, and the method comprises the steps: constructing an individualized brain three-dimensional model according to CT and MRI image data of a patient, presetting an optimal nasal implantation path, and carrying out the implantation of the patient through a nose under the dual guidance of a nasal endoscope and a three-dimensional navigation system, constructing a skull base passage through minimally invasive trimming of a nasal cavity / paranasal sinus structure, and performing real-time matching and overlapping on an endoscope view and the three-dimensional model by using a rigid body transformation algorithm to display the position of a surgical instrument; windowing at a preset target point, implanting the flexible electrode array into a target brain region according to a planned depth and angle through a controllable propulsion mechanism, and establishing a neural signal acquisition or stimulation interface; intelligent mode recognition is carried out on the collected neural signals, the intention or brain state of the user is decoded, and corresponding neural stimulation or feedback signals are generated. According to the method, accurate, safe and minimally invasive clinical intervention is realized through a full-chain technical scheme of individualized planning, real-time navigation, minimally invasive implantation and biological integration, and the application value of a brain-computer interface technology is remarkably improved.

The invention relates to a virtual reality and reality image fusion navigation method and system for temporal bone surgery, and the method comprises the steps: obtaining medical image data of a temporal bone region, and carrying out the three-dimensional reconstruction, thereby obtaining a temporal bone dynamic virtual model; optical tracking data and instrument space pose data are obtained, dynamic registration mapping is conducted on the temporal bone dynamic virtual model, and a real-time space fusion relation is obtained; performing navigation view construction on the instrument space pose data and the real-time space fusion relationship to obtain an augmented reality navigation view; performing structural distance analysis on the augmented reality navigation view to obtain dynamic early warning parameters; and performing display regulation and control according to the augmented reality navigation view and the dynamic early warning parameters to obtain a real-time navigation strategy. The problem of traditional static image registration lag can be effectively solved, and it is ensured that the virtual model and the actual anatomical structure are always kept in high-precision matching.

This invention discloses an AR-assisted puncture navigation spatial registration method and system based on environmental reference features, relating to the field of medical image navigation. The system includes an augmented reality navigation device, a permanent ceiling marker, and a temporary marker board. The augmented reality navigation device includes a binocular augmented reality camera group, a global tracking camera, a global spatial registration module, and a display module. The binocular augmented reality camera group constructs a binocular overlapping field of view, acquiring the pose information of the binocular augmented reality camera group relative to the temporary marker board during the calibration phase, and acquiring near-field images of the surgical area in real time during the surgical phase and displaying them on the display module. The global tracking camera acquires the pose information of the global tracking camera relative to the global coordinate system of the ceiling. The global spatial registration module solves the extrinsic parameter matrix between cameras and the environmental relationship matrix based on the pose information. During the surgical phase, the path planned by the imaging equipment is converted into a real-time navigation path and superimposed on the display module. This solves the complex calibration problem under non-overlapping fields of view.

The invention provides an intelligent terminal outdoor cooperation method and system based on an ant colony algorithm. The method comprises the following steps: acquiring outdoor navigation data, processing the outdoor navigation data into navigation data fragments, and distributing the navigation data fragments to a plurality of intelligent terminals; screening out a main relay node; when entering the target area, determining the intelligent terminal as main navigation equipment, and controlling the gas intelligent terminal to enter a low-power-consumption mode; summarizing the navigation data fragments stored in the intelligent terminals through the main relay node, forwarding the summarized navigation data fragments to the main navigation equipment, and splicing to generate complete navigation data of the target area; and the main navigation equipment obtains and generates navigation information and synchronizes the navigation information to each intelligent terminal through the main relay node. Through pheromone dynamic iteration of the ant colony algorithm and a distributed decision-making mechanism, efficient cooperation of multiple intelligent terminals on division storage and group collaborative splicing is realized, and on the premise of guaranteeing complete navigation data splicing precision and real-time navigation reliability, the overall energy consumption is remarkably reduced, and the equipment endurance is prolonged.

The application relates to the technical field of path planning, and discloses a real-time planning and visualization method and system for a fire-fighting maintenance optimal path, which comprises the following steps: superimposing a fire-fighting fault equipment occurrence site as a first position coordinate and a resource point in a maintenance team as a second position coordinate to an electronic map to obtain an initial navigation path of the maintenance team; according to real-time traffic information, the initial navigation path is constrained to obtain a path planning rule; based on the path planning rule, path optimization is performed on the initial navigation path to obtain a dynamic optimal path; according to the dynamic optimal path, a multistage path guidance instruction and a visual path layer are generated; the visual path layer and the electronic map are dynamically rendered to obtain a real-time navigation interface; and according to the real-time navigation interface and the path guidance instruction, real-time navigation guidance is provided for the maintenance team; and the application can improve the accuracy of reference information generation of real-time planning and visualization of a fire-fighting maintenance optimal path.