Application of computer-assisted navigation in treating congenital maxillomandibular syngnathia:A case report

BACKGROUND Congenital maxillomandibular syngnathia is an extremely rare disorder characterized by craniofacial malformations and inability to open the mouth adequately, which leads to problems with feeding, swallowing, and breathing as well as temporomandibular joint ankylosis. The main goal of the surgery is to release the ankylosis, establish functioning mandible, and prevent re-fusion.However, surgical procedures for this disease are rarely reported.CASE SUMMARY Here, we report a 7-mo-old girl with bilateral maxillomandibular syngnathia. The patient presented with difficulty in feeding, breathing, sounding, and swallowing and had developmental dysplasia. For treatment, we performed bone isolation by computer-assisted navigation and used silicone to fix the wound surface to prevent refusion of bone. To our knowledge, this is the only syngnathia case in the literature treated using computer-assisted navigation. With the guidance of precise navigation, we were able to minimize operation time by at least one hour,the patient's blood vessels, nerves, and tooth germs were well protected, and excessive bleeding was avoided. After six weeks, the patient showed improvement in mouth opening and no major issues of feeding.CONCLUSION Application of computer-assisted navigation can significantly improve accuracy,effectiveness, and surgical safety in correcting congenital maxillomandibular syngnathia.

Computer-assisted navigation systems for insertion of cannulated screws in femoral neck fractures： a comparison of bi-planar robot navigation with optoelectronic navigation in a Synbone hip model trial

Computer-assisted procedures have recently been introduced for navigated femoral neck screw placement. Currently there is little information available regarding accuracy and efficiency of the different navigated procedures. The aim of this study was to compare two fluoroscopic navigation tracking technologies, a novel bi-planar robot navigation and standardized optoelectronic navigation, versus standard freehand fluoroscopic insertion in a Synbone hip model. Methods Eighteen fixed Synbone hip models were divided into 3 groups. C-arm navigated cannulated screws （AO-ASIF, diameter 7.3 mm） were inserted using freehand targeting （control group）. A novel bi-planar robot system （TINAV, GD2000） and an optoelectronic system （Stryker OTS Navigation System） were used for the navigated procedures （robot group and optoelectronic group）. Accuracy was measured using radiographic evaluation including the measurement of screw parallelism and decentralization, and joint penetration. To evaluate the efficiency, the number of guidewire passes, operative time and fluoroscopic images taken were noted. Results The two computer-assisted systems provided significantly improved accuracy compared to the freehand technique. Each of the parameters, including guidewire passes and number of fluoroscopy images, was significantly lower when using the computer-assisted systems than for freehand-unguided insertion （P 〈0.05）, but operative time was significantly shorter when using freehand-unguided insertion than for the computer-assisted systems （P 〈0.05）. Accuracy, operative time and number of fluoroscopy images taken were similar among the two navigated groups （P 〉0.05）, but guidewire passes in the robot group were significantly less than in the optoelectronic group （P 〈0.05）. Conclusions Both bi-planar robot navigation and optoelectronic navigation were similarly accurate and have the potential to improve accuracy and reduce radiation for freehand fluoroscopic targeting for insertion of cannulated screws in femoral neck fractures. Guidewire passes in the robot group were significantly less than in the optoelectronic group. However, both navigated procedures were associated with time-consuming registration and hi.qh rates of failed matching procedures.

Lumbar spine superior-level facet joint violations： percutaneous versus open pedicle screw insertion using intraoperative 3-dimensional computer-assisted navigation

Background Percutaneous pedicle screw use has a high rate of cranial facet joint violations （FVs） because of the facet joint being indirectly visualized.Computer-assisted navigation shows the anatomic structures clearly,and may help to lower the rate of FVs during pedicle screw insertion.This study used computed tomography （CT） to evaluate and compare the incidence of FVs between percutaneous and open surgeries employing computer-assisted navigation for the implantation of pedicle screw instrumentation during lumbar fusions.Methods A prospective study,including 142 patients having lumbar and lumbosacral fusion,was conducted between January 2013 and April 2014.All patients had bilateral posterior pedicle screw-rod instrumentation （top-loading screws） implanted by the same group of surgeons; intraoperative 3-dimensional computer navigation was used during the procedures.All patients underwent CT examinations within 6 months postoperation.The CT scans were independently reviewed by three reviewers blinded to the technique used.Results The cohort comprised 68 percutaneous and 74 open cases （136 and 148 superior-level pedicle screw placements,respectively）.Overall,superior-level FVs occurred in 20 patients （20/142,14.1％）,involving 27 top screws （27/284,9.5％）.The percutaneous technique （7.4％ of patients,3.7％ of top screws） had a significantly lower violation rate than the open procedure （20.3％ of patients,14.9％ of top screws）.The open group also had significantly more serious violations than did the percutaneous group.Both groups had a higher violation rate when the cranial fixation involved the L5.A 1-level open procedure had a higher violation rate than did the 2-and 3-level surgeries.Conclusions With computer-assisted navigation,the placement of top-loading percutaneous screws carries a lower risk of adjacent-FVs than does the open technique; when FVs occur,they tend to be less serious.Performing a single-level open lumbar fusion,or the fusion of the L5-S1 segment,requires caution to avoid cranial adjacent FVs.

BDSec:Security Authentication Protocol for BeiDou-Ⅱ Civil Navigation Message

Due to the lack of authentication mechanism in BeiDou navigation satellite system(BDS),BD-Ⅱ civil navigation message(BDⅡ-CNAV) are vulnerable to spoofing attack and replay attack.To solve this problem,we present a security authentication protocol,called as BDSec,which is designed by using China’s cryptography Shangyong Mima(SM) series algorithms,such as SM2/4/9 and Zu Chongzhi(ZUC)algorithm.In BDSec protocol,both of BDⅡ-CNAV and signature information are encrypted using the SM4 algorithm(Symmetric encryption mechanism).The encrypted result is used as the subject authentication information.BDSec protocol applies SM9 algorithm(Identity-based cryptography mechanism) to protect the integrity of the BDⅡ-CNAV,adopts the SM2 algorithm(Public key cryptosystem) to guarantee the confidentiality of the important session information,and uses the ZUC algorithm(Encryption and integrity algorithm) to verify the integrity of the message authentication serial number and initial information and the information in authentication initialization sub-protocol respectively.The results of the SVO logic reasoning and performance analysis show that BDSec protocol meets security requirements for the dual user identity authentication in BDS and can realize the security authentication of BDⅡ-CNAV.

Computer-assisted three-dimensional individualized extreme liver resection for hepatoblastoma in proximity to the major liver vasculature

BACKGROUND The management of hepatoblastoma(HB)becomes challenging when the tumor remains in close proximity to the major liver vasculature(PMV)even after a full course of neoadjuvant chemotherapy(NAC).In such cases,extreme liver resection can be considered a potential option.AIM To explore whether computer-assisted three-dimensional individualized extreme liver resection is safe and feasible for children with HB who still have PMV after a full course of NAC.METHODS We retrospectively collected data from children with HB who underwent surgical resection at our center from June 2013 to June 2023.We then analyzed the detailed clinical and three-dimensional characteristics of children with HB who still had PMV after a full course of NAC.RESULTS Sixty-seven children diagnosed with HB underwent surgical resection.The age at diagnosis was 21.4±18.8 months,and 40 boys and 27 girls were included.Fifty-nine(88.1%)patients had a single tumor,39(58.2%)of which was located in the right lobe of the liver.A total of 47 patients(70.1%)had PRE-TEXT III or IV.Thirty-nine patients(58.2%)underwent delayed resection.After a full course of NAC,16 patients still had close PMV(within 1 cm in two patients,touching in 11 patients,compressing in four patients,and showing tumor thrombus in three patients).There were 6 patients of tumors in the middle lobe of the liver,and four of those patients exhibited liver anatomy variations.These 16 children underwent extreme liver resection after comprehensive preoperative evaluation.Intraoperative procedures were performed according to the preoperative plan,and the operations were successfully performed.Currently,the 3-year event-free survival of 67 children with HB is 88%.Among the 16 children who underwent extreme liver resection,three experienced recurrence,and one died due to multiple metastases.CONCLUSION Extreme liver resection for HB that is still in close PMV after a full course of NAC is both safe and feasible.This approach not only reduces the necessity for liver transplantation but also results in a favorable prognosis.Individualized three-dimensional surgical planning is beneficial for accurate and complete resection of HB,particularly for assessing vascular involvement,remnant liver volume and anatomical variations.

Effect of navigation endoscopy combined with threedimensional printing technology in the treatment of orbital blowout fractures

●AIM:To explore the combined application of surgical navigation nasal endoscopy(NNE)and three-dimensional printing technology(3DPT)for the adjunctive treatment of orbital blowout fractures(OBF).●METHODS:Retrospective analysis was conducted on the data of patients with OBF who underwent surgical treatment at the Affiliated Eye Hospital of Nanchang University between July 2012 and November 2022.The control group consisted of patients who received traditional surgical treatment(n=43),while the new surgical group(n=52)consisted of patients who received NNE with 3DPT.The difference in therapeutic effects between the two groups was evaluated by comparing the duration of the operation,best corrected visual acuity(BCVA),enophthalmos difference,recovery rate of eye movement disorder,recovery rate of diplopia,and incidence of postoperative complications.●RESULTS:The study included 95 cases(95 eyes),with 63 men and 32 women.The patients’age ranged from 5 to 67y(35.21±15.75y).The new surgical group and the control group exhibited no statistically significant differences in the duration of the operation,BCVA and enophthalmos difference.The recovery rates of diplopia in the new surgical group were significantly higher than those in the control group at 1mo[OR=0.03,95%CI(0.01–0.15),P<0.0000]and 3mo[OR=0.11,95%CI(0.03–0.36),P<0.0000]postoperation.Additionally,the recovery rates of eye movement disorders at 1 and 3mo after surgery were OR=0.08,95%CI(0.03–0.24),P<0.0000;and OR=0.01,95%CI(0.00–0.18),P<0.0000.The incidence of postoperative complications was lower in the new surgical group compared to the control group[OR=4.86,95%CI(0.95–24.78),P<0.05].●CONCLUSION:The combination of NNE and 3DPT can shorten the recovery time of diplopia and eye movement disorder in patients with OBF.

A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system

In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.

Navigation Finsler metrics on a gradient Ricci soliton

In this paper,we study a class of Finsler metrics defined by a vector field on a gradient Ricci soliton.We obtain a necessary and sufficient condition for these Finsler metrics on a compact gradient Ricci soliton to be of isotropic S-curvature by establishing a new integral inequality.Then we determine the Ricci curvature of navigation Finsler metrics of isotropic S-curvature on a gradient Ricci soliton generalizing result only known in the case when such soliton is of Einstein type.As its application,we obtain the Ricci curvature of all navigation Finsler metrics of isotropic S-curvature on Gaussian shrinking soliton.

Single-center experience with Knee+^(TM) augmented reality navigation system in primary total knee arthroplasty

BACKGROUND Computer-assisted systems obtained an increased interest in orthopaedic surgery over the last years,as they enhance precision compared to conventional hardware.The expansion of computer assistance is evolving with the employment of augmented reality.Yet,the accuracy of augmented reality navigation systems has not been determined.AIM To examine the accuracy of component alignment and restoration of the affected limb’s mechanical axis in primary total knee arthroplasty(TKA),utilizing an augmented reality navigation system and to assess whether such systems are conspicuously fruitful for an accomplished knee surgeon.METHODS From May 2021 to December 2021,30 patients,25 women and five men,under-went a primary unilateral TKA.Revision cases were excluded.A preoperative radiographic procedure was performed to evaluate the limb’s axial alignment.All patients were operated on by the same team,without a tourniquet,utilizing three distinct prostheses with the assistance of the Knee+™augmented reality navigation system in every operation.Postoperatively,the same radiographic exam protocol was executed to evaluate the implants’position,orientation and coronal plane alignment.We recorded measurements in 3 stages regarding femoral varus and flexion,tibial varus and posterior slope.Firstly,the expected values from the Augmented Reality system were documented.Then we calculated the same values after each cut and finally,the same measurements were recorded radiolo-gically after the operations.Concerning statistical analysis,Lin’s concordance correlation coefficient was estimated,while Wilcoxon Signed Rank Test was performed when needed.RESULTS A statistically significant difference was observed regarding mean expected values and radiographic mea-surements for femoral flexion measurements only(Z score=2.67,P value=0.01).Nonetheless,this difference was statistically significantly lower than 1 degree(Z score=-4.21,P value<0.01).In terms of discrepancies in the calculations of expected values and controlled measurements,a statistically significant difference between tibial varus values was detected(Z score=-2.33,P value=0.02),which was also statistically significantly lower than 1 degree(Z score=-4.99,P value<0.01).CONCLUSION The results indicate satisfactory postoperative coronal alignment without outliers across all three different implants utilized.Augmented reality navigation systems can bolster orthopaedic surgeons’accuracy in achieving precise axial alignment.However,further research is required to further evaluate their efficacy and potential.

Improving path planning efficiency for underwater gravity-aided navigation based on a new depth sorting fast search algorithm

This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.

Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

Learning curve of computer-assisted navigation system in spine surgery

Background Spine surgery using computer-assisted navigation （CAN） has been proven to result in low screw misplacement rates, low incidence of radiation exposure and excellent operative field viewing versus the conventional intraoperative image intensifier （CⅢ）. However, as we know, few previous studies have described the learning curve of CAN in spine surgery.Methods We performed two consecutive case cohort studies on pedicel screw accuracy and operative time of two spine surgeons with different experience backgrounds, A and B, in one institution during the same period. Lumbar pedicel screw cortical perforation rate and operative time of the same kind of operation using CAN were analyzed and compared using CⅢ for the two surgeons at initial, 6 months and 12 months of CAN usage.Results CAN spine surgery had an overall lower cortical perforation rate and less mean operative time compared with CⅢ for both surgeon A and B cohorts when total cases of four years were included. It missed being statistically significant,with 3.3% versus 4.7% （P=0.191） and 125.7 versus 132.3 minutes （P=0.428） for surgeon A and 3.6% versus 6.4%（P=0.058）, and 183.2 versus 213.2 minutes （P=0.070） for surgeon B. in an attempt to demonstrate the learning curve,the cases after 6 months of the CAN system in each surgeon＇s cohort were compared. The perforation rate decreased by 2.4% （P=0.039） and 4.3% （P=0.003） and the operative time was reduced by 31.8 minutes （P=0.002） and 14.4 minutes （P=0.026） for the CAN groups of surgeons A and B, respectively. When only the cases performed after 12 months using the CAN system were considered, the perforation rate decreased by 3.9% （P=0.006） and 5.6% （P 〈0.001） and the operative time was reduced by 20.9 minutes （P 〈0.001） and 40.3 minutes （P 〈0.001） for the CAN groups of surgeon A and B, respectively.Conclusions In the long run, CAN spine surgery decreased the lumbar screw cortical perforation rate and operative time. The learning curve showed a sharp drop after 6 months of using CAN that plateaued after 12 months; which was demonstrated by both perforation rate and operative time data. Careful analysis of the data showed CAN is especially useful for less experienced surgeon to reduce perforation rate and intraoperative time, although further comparative studies are anticipated.

Clinical application of improved 2D computer-assisted fluoroscopic navigation through simulating a 3D vertebrae image to guide pedicle screw internal fixation

Objective To study the effect of using improved 2D computer-assisted fluoroscopic navigation through simulating 3D vertebrae image to guide pedicle screw internal fixation.Methods Posterior pedicle screw internal fixation,distraction

Vision Navigation Based PID Control for Line Tracking Robot

In a controlled indoor environment,line tracking has become the most practical and reliable navigation strategy for autonomous mobile robots.A line tracking robot is a self-mobile machine that can recognize and track a painted line on thefloor.In general,the path is set and can be visible,such as a black line on a white surface with high contrasting colors.The robot’s path is marked by a distinct line or track,which the robot follows to move.Several scientific contributions from the disciplines of vision and control have been made to mobile robot vision-based navigation.Localization,automated map generation,autonomous navigation and path tracking is all becoming more frequent in vision applications.A visual navigation line tracking robot should detect the line with a camera using an image processing technique.The paper focuses on combining computer vision techniques with a proportional-integral-derivative(PID)control-ler for automatic steering and speed control.A prototype line tracking robot is used to evaluate the proposed control strategy.

Resilient tightly coupled INS/UWB integration method for indoor UAV navigation under challenging scenarios

Based on the high positioning accuracy,low cost and low-power consumption,the ultra-wide-band(UWB)is an ideal solution for indoor unmanned aerial vehicle(UAV)localization and navigation.However,the UWB signals are easy to be blocked or reflected by obstacles such as walls and furniture.A resilient tightly-coupled inertial navigation system(INS)/UWB integration is proposed and implemented for indoor UAV navigation in this paper.A factor graph optimization(FGO)method enhanced by resilient stochastic model is established to cope with the indoor challenging scenarios.To deal with the impact of UWB non-line-of-sight(NLOS)signals and noise uncertainty,the conventional neural net-works(CNNs)are introduced into the stochastic modelling to improve the resilience and reliability of the integration.Based on the status that the UWB features are limited,a‘two-phase'CNNs structure was designed and implemented:one for signal classification and the other one for measurement noise prediction.The proposed resilient FGO method is tested on flighting UAV platform under actual indoor challenging scenario.Compared to classical FGO method,the overall positioning errors can be decreased from about 0.60 m to centimeter-level under signal block and reflection scenarios.The superiority of resilient FGO which effectively verified in constrained environment is pretty important for positioning accuracy and integrity for indoor navigation task.

Adaptive navigation assistance based on eye movement features in virtual reality

Background Navigation assistance is essential for users when roaming virtual reality scenes;however,the traditional navigation method requires users to manually request a map for viewing,which leads to low immersion and poor user experience.Methods To address this issue,we first collected data on who required navigation assistance in a virtual reality environment,including various eye movement features,such as gaze fixation,pupil size,and gaze angle.Subsequently,we used the boosting-based XGBoost algorithm to train a prediction model and finally used it to predict whether users require navigation assistance in a roaming task.Results After evaluating the performance of the model,the accuracy,precision,recall,and F1-score of our model reached approximately 95%.In addition,by applying the model to a virtual reality scene,an adaptive navigation assistance system based on the real-time eye movement data of the user was implemented.Conclusions Compared with traditional navigation assistance methods,our new adaptive navigation assistance method could enable the user to be more immersive and effective while roaming in a virtual reality(VR)environment.

Context-Aware Practice Problem Recommendation Using Learners’ Skill Level Navigation Patterns

The use of programming online judges(POJs)has risen dramatically in recent years,owing to the fact that the auto-evaluation of codes during practice motivates students to learn programming.Since POJs have greater number of pro-gramming problems in their repository,learners experience information overload.Recommender systems are a common solution to information overload.Current recommender systems used in e-learning platforms are inadequate for POJ since recommendations should consider learners’current context,like learning goals and current skill level(topic knowledge and difficulty level).To overcome the issue,we propose a context-aware practice problem recommender system based on learners’skill level navigation patterns.Our system initially performs skill level navigation pattern mining to discover frequent skill level navigations in the POJ and tofind learners’learning goals.Collaborativefiltering(CF)and con-tent-basedfiltering approaches are employed to recommend problems in the cur-rent and next skill levels based on frequent skill level navigation patterns.The sequence similarity measure is used tofind the top k neighbors based on the sequence of problems solved by the learners.The experiment results based on the real-world POJ dataset show that our approach considering the learners’cur-rent skill level and learning goals outperforms the other approaches in practice problem recommender systems.

Scene Visual Perception and AR Navigation Applications

With the rapid popularization of mobile devices and the wide application of various sensors,scene perception methods applied to mobile devices occupy an important position in location-based services such as navigation and augmented reality(AR).The development of deep learning technologies has greatly improved the visual perception ability of machines to scenes.The basic framework of scene visual perception,related technologies and the specific process applied to AR navigation are introduced,and future technology development is proposed.An application(APP)is designed to improve the application effect of AR navigation.The APP includes three modules:navigation map generation,cloud navigation algorithm,and client design.The navigation map generation tool works offline.The cloud saves the navigation map and provides navigation algorithms for the terminal.The terminal realizes local real-time positioning and AR path rendering.

Satellite Navigation Method Based on High-Speed Frequency Hopping Signal

Global navigation satellite system has been widely used,but it is vulnerable to jamming.In military satellite communications,frequency hopping(FH)signal is usually used for anti-jamming communications.If the FH signal can be used in satellite navigation,the anti-jamming ability of satellite navigation can be improved.Although a recently proposed timefrequency matrix ranging method(TFMR)can use FH signals to realize pseudorange measurement,it cannot transmit navigation messages using the ranging signal which is crucial for satellite navigation.In this article,we propose dual-tone binary frequency shift keyingbased TFMR(DBFSK-TFMR).DBFSK-TFMR designs an extended time-frequency matrix(ETFM)and its generation algorithm,which can use the frequency differences in different dual-tone signals in ETFM to modulate data and eliminate the negative impact of data modulation on pseudorange measurement.Using ETFM,DBFSK-TFMR not only realizes the navigation message transmission but also ensures the precision and unambiguous measurement range of pseudorange measurement.DBFSK-TFMR can be used as an integrated solution for anti-jamming communication and navigation based on FH signals.Simulation results show that DBFSK-TFMR has almost the same ranging performance as TFMR.

Indoor Navigation Network Model Construction Method Based on Building Information Model

In view of the poor information integrity of the 3D model used to make the indoor road network and the lack of versatility of the constructed indoor road network, a method for building an indoor navigation network model that can be seamlessly connected with outdoor paths is proposed in this paper. First, the IFC model is converted to the CityGML model using the BIM model as the indoor data source. Then, using GIS technology and limited Delaunay triangulation refinement algorithm, the necessary elements of indoor navigate on network model such as semantic information, geometric information and topological relationship contained in CityGML model are extracted. Finally, it is visualized and verified based on experimental model data. The results show that the indoor navigation network model constructed based on the CityGML model can accurately perform indoor navigation, make the constructed road network more general, and provide reference and technical support for the integrated construction of indoor and outdoor road network models.